ai research assistant

Analyze research papers at superhuman speed

Search for research papers, get one sentence abstract summaries, select relevant papers and search for more like them, extract details from papers into an organized table.

Find themes and concepts across many papers

Don't just take our word for it.

Tons of features to speed up your research

Upload your own pdfs, orient with a quick summary, view sources for every answer, ask questions to papers, research for the machine intelligence age, pick a plan that's right for you, get in touch, enterprise and institutions, custom pricing, common questions. great answers., how do researchers use elicit.

Over 2 million researchers have used Elicit. Researchers commonly use Elicit to:

• Speed up literature review
• Find papers they couldn’t find elsewhere
• Automate systematic reviews and meta-analyses
• Learn about a new domain

Elicit tends to work best for empirical domains that involve experiments and concrete results. This type of research is common in biomedicine and machine learning.

What is Elicit not a good fit for?

Elicit does not currently answer questions or surface information that is not written about in an academic paper. It tends to work less well for identifying facts (e.g. “How many cars were sold in Malaysia last year?”) and theoretical or non-empirical domains.

What types of data can Elicit search over?

Elicit searches across 125 million academic papers from the Semantic Scholar corpus, which covers all academic disciplines. When you extract data from papers in Elicit, Elicit will use the full text if available or the abstract if not.

How accurate are the answers in Elicit?

A good rule of thumb is to assume that around 90% of the information you see in Elicit is accurate. While we do our best to increase accuracy without skyrocketing costs, it’s very important for you to check the work in Elicit closely. We try to make this easier for you by identifying all of the sources for information generated with language models.

What is Elicit Plus?

Elicit Plus is Elicit's subscription offering, which comes with a set of features, as well as monthly credits. On Elicit Plus, you may use up to 12,000 credits a month. Unused monthly credits do not carry forward into the next month. Plus subscriptions auto-renew every month.

What are credits?

Elicit uses a credit system to pay for the costs of running our app. When you run workflows and add columns to tables it will cost you credits. When you sign up you get 5,000 credits to use. Once those run out, you'll need to subscribe to Elicit Plus to get more. Credits are non-transferable.

How can you get in contact with the team?

Please email us at [email protected] or post in our Slack community if you have feedback or general comments! We log and incorporate all user comments. If you have a problem, please email [email protected] and we will try to help you as soon as possible.

What happens to papers uploaded to Elicit?

When you upload papers to analyze in Elicit, those papers will remain private to you and will not be shared with anyone else.

How accurate is Elicit?

Training our models on specific tasks, searching over academic papers, making it easy to double-check answers, save time, think more. try elicit for free..

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Top 10 Best AI Research Assistants in 2024 (Free + Paid)

21 min read

Feeling overwhelmed by the ever-growing ocean of academic literature? Drowning in research papers and struggling to find the information you need? In this guide, we explore the exciting world of AI research assistants, your secret weapon for conquering research challenges.

AI research assistants are intelligent tools that streamline the research process, saving you time and effort. Imagine having a personal research companion by your side, summarizing complex papers, answering your questions, and even explaining tricky concepts.

This guide dives deep into the top 10 AI research assistants available in 2024, exploring their strengths, weaknesses, and pricing options. Whether you're a student swamped with assignments, an academic conducting in-depth studies, or a professional needing to stay up-to-date on industry research, there's a perfect AI assistant waiting to transform your research experience. So lets get started. 

Top 10 AI Research Assistants at a Glance 

Best ai research assistant for different fields , key features of elephas for research, elephas pricing , elephas reviews , scispace key features , scispace pricing , scispace reviews , key features of elicit , elicit reviews , chatpdf key features , chatpdf pricing , chatpdf reviews , explain paper key features , explain paper pricing , explain paper reviews , connected papers key features , connected papers pricing , connected papers reviews , lex ai key features , lex ai pricing .

• Lex AI Reviews 

Consensus Key Features 

Consensus pricing .

• Consensus Reviews 

Semantic Scholar Key Features 

Semantic scholar pricing , semantic scholar reviews , system key features .

• System Pricing 

System Reviews 

Consider your research style:, what is an ai research assistant , what are the advantages of using ai research assistants , our selection criteria to pick the top 10 ai research assistants, why elephas is the best ai research assistant .

• Conclusion 
• 1. What does an AI research assistant do?

2. What is the best AI research assistant?

3. how can ai assist in research.

Elephas: AI research assistant with multi-AI integration and offline mode for customized writing.

Scispace: It provides in-depth explanations and multilingual support.

Elicit: It excels at literature review and summarization.

Explain Paper: It simplifies complex research papers with customizable explanations.

Connected Papers: Creates a visual map to explore connections between research papers.

Lex AI: It streamlines research writing with formatting and content generation.

Consensus: Delivers evidence-based answers from scientific research with summaries and in-depth analysis.

ChatPDF: It helps in summarizing PDFs, answering questions, and translating languages.

Semantic Scholar: It has a massive paper library, advanced search, and summaries.

System: It provides summaries of relevant scientific literature and visualizations.

1. Elephas 

Elephas is an advanced AI research assistant designed to enhance productivity and streamline the research process. This powerful tool integrates seamlessly with your devices, providing context-aware assistance for various tasks. Elephas can summarize content, rewrite text, and interact with multiple platforms, making it an indispensable companion for researchers. With its user-friendly interface and customizable features, Elephas ensures that you can focus on your research while it handles the tedious tasks, saving you valuable time and effort.

Context-Aware AI Assistance: Access Elephas anywhere on your Mac with a simple shortcut, providing custom use cases based on the current screen, such as summarizing YouTube videos or web pages.

Multi-AI Provider Integration: Elephas allows users to leverage multiple AI providers, including Claude, OpenAI, Gemini, and Groq. This enables customization based on specific writing styles, project requirements, and personal preferences.

Robust Offline Mode: Elephas introduces an offline mode, allowing users to harness AI capabilities without an internet connection, ensuring seamless writing regardless of location.

Integrated Web Search: The enhanced Super Chat feature now includes integrated web search, enabling users to access and incorporate relevant online information directly within the interface.

Smart AI Keyboard: The AI-powered keyboard for iOS devices automates the writing process, offering modes like Professional, Friendly, and Viral to suit different research contexts.

Super Brain Feature: Sync and chat with your personalized AI brains across iOS devices, ensuring your research data is always accessible and organized.

Audio Processing: Record and transcribe audio notes or upload audio files from meetings and podcasts to create comprehensive research brains .

Customisable Snippets and Tones: Define repetitive tasks and set personalized writing styles, allowing Elephas to assist with tasks in a way that matches your unique research needs.

Elephas is one of the best chatgpt apps on the market right now.

It works locally and it's 100% privacy friendly!

If you own a Mac, you should definitely try it out.

2. Scispace

SciSpace Copilot is an innovative AI research assistant who acts as your friendly guide through the challenging world of academic research . It helps you to understand complex topics, and SciSpace Copilot goes beyond summaries. This innovative AI research assistant acts like a friendly study buddy, breaking down complex research papers into easy-to-understand summaries and explanations. It analyzes text, formulas, and data visualizations within research papers, providing clear explanations and answers to your questions in real time.

Breakthrough Comprehension: Copilot goes beyond summaries. It deciphers complex text, equations, and tables, providing clear explanations tailored to your needs. Ask questions directly within your research papers, and receive instant, contextual answers – all without leaving the document.

Multilingual Mastery: Converse with Copilot in 13 languages, including Chinese, Japanese, and French. This removes language barriers and opens doors to a world of scientific knowledge.

Seamless Summarization: Turn mountains of text into manageable molehills. Copilot condenses lengthy sections into concise summaries, allowing you to grasp key points quickly and efficiently. This frees up valuable time for deeper analysis.

Effortless Literature Evaluation: Shortlist relevant papers faster than ever. Pose in-depth questions to Copilot and assess the paper's applicability to your research without relying solely on abstracts.

Personalized Learning Experience: Annotate your research for future reference. Copilot allows you to create your own notes alongside its insightful responses. This personalized learning approach ensures a deeper understanding and streamlines future review.

Premium Plan Starts at $7.79/month 

Some reported the tool has been charging without their consent, and they have to cancel their card to stop making payments. The customer support of the tool is not great. Few other users reported that the tool publishes fake articles in the name of well known authors on their site.

3. Elicit 

Elicit is a free research tool that helps you find relevant academic papers and gain insights from them. It uses natural language processing to understand your questions and find papers that match your needs, even if they don't use the exact keywords. Elicit summarizes key information and provides helpful metrics to assess paper quality. You can upload your own PDFs and explore them with ease. Elicit is a great way to save time and streamline your research workflow.

Effortless Literature Search: Ask your research question in plain English and Elicit, the AI research assistant, will scour vast academic databases to find relevant publications in a matter of minutes.

Intelligent Paper Summarization: No more sifting through endless papers! Elicit analyzes top results and generates concise summaries highlighting key observations. Gain valuable insights quickly and stay on top of the latest research.

Customizable Research Organization: Tailor your research experience. Elicit allows you to filter by study type and personalize how information about each paper is displayed. Organize your findings for efficient analysis and easy reference.

Data-Driven Insights: Gain a deeper understanding of research methods and outcomes. Elicit unveils the datasets used and results measured by different authors, enriching your research perspective.

Elicit Pricing 

• It is free to use 

Some users have reported that they cannot go back to the homepage once they start the search on the tool. Additionally, if you want to modify your search a little, the previously started papers won't remain and need to be searched for again in order to get their info.

ChatPDF is an innovative web tool that acts like your personal AI research assistant for all things PDF. Forget clunky software and confusing interfaces. ChatPDF lets you chat with your PDFs in plain English, making it a breeze to unlock the information you need. Whether you're a student analyzing research papers, a lawyer reviewing contracts, or a busy professional summarizing reports, ChatPDF streamlines your workflow and saves you valuable time.

Effortless Summarization: Get concise summaries of your PDFs to grasp key points and information quickly.

AI-powered Q&A: Have questions about the document's content? Ask ChatPDF, and it will use its AI capabilities to provide insightful answers.

Multilingual Marvel: ChatPDF breaks down language barriers. Upload PDFs in any language, and it will process and respond in multiple languages for your convenience.

Cited Sources for Credibility: Answers generated by ChatPDF are backed by references to the original PDF, allowing you to easily verify the information and find the source within the document.

Multitasking Made Easy: ChatPDF lets you manage multiple PDFs simultaneously, making research and information gathering a breeze.

Free Plan ( 3 PDFs Daily and 50 Questions Per day ) 

Premium Plan Starts $5 Per month 

5. Explain Paper  

Explain Paper is an AI research assistant to simplify and explain those head-scratching concepts. Explain Paper utilizes cutting-edge AI technology to break down dense research papers into easy-to-understand explanations. Simply upload your paper (PDF or URL) and highlight any confusing sections. Explainpaper, your AI research assistant, will analyze the text and provide clear explanations right on the page, eliminating the need to jump between countless websites

Highlight & Explain: Struggling with a specific passage? Highlight it, and Explainpaper will provide a clear explanation using advanced AI.

AI-Powered Insights: Don't get bogged down by technical jargon. Explainpaper leverages sophisticated AI to simplify complex concepts in research papers.

Save for Later: Don't lose track of those valuable explanations! Save your uploaded papers for future reference and revisit them anytime.

Customization is Key: Explainpaper tailors explanations to your needs. Choose the difficulty level, from basic explanations suitable for a 5-year-old to in-depth analyses for experts.

Dive Deeper: Gain a more comprehensive understanding with related resources provided alongside each explanation, allowing you to delve deeper into specific topics.

Premium Plan starts at $12 per month

We couldn’t find any public reviews on the internet about the tool. We suggest readers proceed with caution while using the tool.

6. Connected Papers 

Connected Papers is your AI-powered research assistant, designed to revolutionize the way you explore scientific literature. Imagine a vibrant map where each point represents a research paper, and the closer they are, the more the ideas connect. It is a visual playground for researchers to uncover hidden connections and spark groundbreaking discoveries. Also, the size of the map reflects its influence, and connecting lines showcase the thematic bridges between them. That's the magic of Connected Papers!

Visualize the Conversation: Ditch the endless lists! Connected Papers creates a dynamic map of related research, using circles to represent papers and lines to depict their connections.

Beyond Citations: Sure, citations are important, but Connected Papers goes deeper. It analyzes the meaning and ideas within papers, connecting those that share similar concepts – a far richer way to explore your field.

See the Forest and the Trees: Dive into a single paper or explore a broader topic. Connected Papers lets you input multiple starting points, building a comprehensive map that reveals the connections between different research areas.

Explore from Multiple Angles: Dive deeper by feeding Connected Papers with several starting points. It will then craft a unified map, highlighting the relationships between your chosen papers.

Save for Later: Don't lose track of your research journey. Connected Papers lets you save interesting papers and their connections for future reference.

Paid Plan starts at $10 Per month

7. Lex AI 

Lex Ai is an AI research assistant who acts like a smart companion by your side, streamlining the research writing process so you can focus on what matters most – groundbreaking discoveries. Lex goes beyond a simple word processor. It's a powerful AI tool trained on a massive dataset to understand the nuances of academic and scientific writing. Whether you're crafting a research paper, grant proposal, or technical report, Lex can significantly boost your productivity.

Effortless Formatting: Say goodbye to tedious formatting! Lex uses simple prompts to handle references, headers, tables, and lists, freeing you to concentrate on your content.

AI-powered Content Generation : Lex can generate relevant and accurate content based on your specific prompts, saving you precious time.

Side-by-Side Comparison: Maintain complete control over your research. Track and compare your input with the AI-generated text to ensure seamless integration and top-notch quality.

Real-time Research Support: No more research roadblocks! Ask Lex quick questions directly within the platform. No need to switch tabs or lose your train of thought.

Intelligent Learning: The more you use Lex, the smarter it gets. As you write, Lex learns your style and preferences, continuously improving the quality of its suggestions.

Free to use 

Lex AI Reviews  

8. consensus .

Consensus cuts through the noise by delivering evidence-based answers straight from scientific research. This innovative platform leverages the power of artificial intelligence to analyze millions of peer-reviewed papers, providing you with trustworthy, up-to-date findings. Gone are the days of sifting through mountains of unverified sources. Leveraging the power of artificial intelligence, Consensus dives deep into a vast collection of over 200 million scientific papers to surface insights and summaries you can rely on.

Trustworthy Results: Focus on findings, not fluff. Every answer in Consensus is meticulously sourced from credible scientific publications, ensuring the information you receive is dependable and verifiable.

AI-powered Summaries: Consensus utilizes advanced AI to generate concise summaries, saving you valuable time and effort.

AI-Powered Insights: Unleash the power of AI. Consensus utilizes cutting-edge technology to analyze and summarize complex research papers, delivering clear and concise summaries that save you valuable time and effort.

Effortless Navigation: Experience a breeze with Consensus' user-friendly interface. The intuitive design streamlines the search process, allowing you to find the information you need quickly and efficiently.

In-Depth Analysis: Gain a deeper understanding of the "Synthesize" feature. This powerful tool analyzes the top research papers on your topic, providing a comprehensive overview of the key findings.

Premium Plan Starts at $8.99/month 

Consensus Reviews  

9. semantic scholar .

Semantic Scholar is an AI-powered research assistant. This innovative tool helps researchers of all levels to navigate the vast ocean of academic literature with ease.  This AI research assistant helps you to find exactly what you need when you need it. Semantic Scholar boasts a staggering collection of over 207 million scientific papers, meticulously categorized across diverse fields.

Massive Paper Library: Explore over 207 million research papers across various scientific disciplines.

Laser-Focused Search: Refine your research with advanced filters like journals, authors, publication dates, and more.

AI-powered Recommendations: Never miss a relevant study again. Semantic Scholar suggests related papers based on your search, keeping you on the cutting edge of your field.

TLDR Time Savers: Short on time? Semantic Scholar offers concise summaries (think "Too Long; Didn't Read") for millions of papers, allowing you to grasp key concepts quickly.

Organize Your Research: Build a personalized library to store and categorize your favourite papers. Access them from any device and create custom folders for better organization.

10. System  

System is an innovative AI research assistant that simplifies the research process, saving you time and effort. System acts as your personal research companion, using advanced AI to understand your queries and deliver insightful summaries of relevant scientific literature. No more sifting through endless papers – System efficiently gathers and synthesizes information, providing you with a clear and concise overview of the latest research in your field.

• Effortless Research: Simply enter your topic and System delivers a fast, up-to-date summary of relevant research, saving you hours of searching.
• Crystal Clear Insights: System doesn't just provide information, it clarifies it. Each summary is accompanied by transparent citations, ensuring you understand the source of the information.
• Always Current: System stays ahead of the curve by constantly refreshing its knowledge base with the latest research from trusted sources.
• Uncover Hidden Connections: System's unique visualization tools help you see the bigger picture, revealing connections and insights you might have missed.

System Pricing  

Free: Basic search.

Premium Plans start at $6/month 

How to Choose the Right AI Research Assistant for your Day to Day Activities? 

AI Research Assistants are powerful tools that can streamline your daily tasks, but with a plethora of options, choosing the right one can be tricky. Here's how to pick the perfect AI research assistant for your specific needs:

Power User: If you juggle various projects and need an all-in-one tool, consider Elephas. It integrates with multiple AI providers, letting you customise writing styles and tackle diverse tasks.

Free Spirit: For those on a budget, Elicit and Lex AI offer valuable features for free. Elicit excels at summarizing and finding relevant papers, while Lex AI assists with academic writing.

Language Learner: Researching in multiple languages? Scispace Copilot provides multilingual support and in-depth explanations, breaking down language barriers.

Decoding Complex Papers: Then try out the Explain Paper tool that excel at simplifying dense concepts.

Need Massive Library: Semantic Scholar has a massive library of 207 Million research papers. 

Elephas: Your Customizable Research Powerhouse

Elephas stands out for its versatility and user-friendliness. Its unique features include:

Offline Mode: Work seamlessly without an internet connection.

AI Integration: Choose from multiple AI providers to fit your writing style.

Smart Summarization: Get clear, concise summaries of research papers.

Customisable Snippets: Automate repetitive tasks and personalise writing styles.

While exploring different options, keep Elephas on your radar. This versatile AI assistant acts like a Swiss Army knife for researchers. Need summaries, rewrites, or help with specific writing styles? Elephas has you covered. Plus, its unique offline mode allows you to access AI help anywhere, anytime.

By following these steps and considering Elephas, you'll be well on your way to finding the perfect AI research assistant. Remember, the best research assistant depends on your specific needs and will help you conquer your research challenges, transforming your daily grind into a breeze. Explore free trials and various features to find your ideal solution.

Before we move on to the advantages of research assistants, let's look at what exactly an AI research assistant is.

Think of an AI research assistant as your own personal research librarian on steroids. It saves you time, simplifies complex information, and even explains tricky concepts. It helps you focus on the most important parts of your research.

These are powerful tools powered by artificial intelligence (AI) that help researchers navigate the ever-growing ocean of academic literature. They act like smart companions, helping you with various tasks such as:

Slicing Through Text Mountains: AI assistants can quickly summarize lengthy research papers, saving you hours of reading time.

Finding the Perfect Papers: Struggling to find relevant research? AI assistants can search vast databases to pinpoint studies that align with your topic.

Understanding the Jargon: AI can break down complex concepts and explain them in clear, easy-to-understand language.

Supercharge Your Writing: Some AI assistants can help with academic writing tasks like formatting references and generating content prompts.

Here's the best part: AI research assistants come in all shapes and sizes. Some are free to use, while others offer paid plans with more advanced features.

Who can benefit from an AI research assistant?

Students swamped with research papers

Academics conducting in-depth studies

Professionals need to stay up-to-date on industry research

Research can feel like quicksand sometimes - the more you struggle, the deeper you sink. But what if there was a helpful tool to pull you out? That's where AI research assistants come in!

So, what exactly can these AI helpers do?

Save Time & Effort: AI assistants can summarize research papers, find relevant articles, and even answer your questions about them. This frees you up to focus on the important stuff - understanding the research and making cool discoveries!

Understand Complex Concepts: AI can break down tough research papers into easy-to-grasp chunks. No more head-scratching over confusing jargon!

Write Like a Pro: Some AI assistants can even help you write your research papers or reports. They can suggest citations, improve formatting, and even rephrase sentences for better clarity.

Stay Organized: Keep track of all your research in one place! Some AI assistants let you store and organize your findings, making it easy to find what you need later.

Work Offline: No internet connection? No problem! Some AI assistants work even without wifi such as Elephas, so you can keep researching on the go.

More Efficient Workflow: Organize your research materials and streamline the process.

Less Stress: Free up mental space by letting AI handle repetitive tasks.

Write Smarter, Not Harder: From suggesting citations to helping with formatting, AI assistants can streamline your academic writing, making it faster and more efficient.

Basically, AI research assistants are like having a personal research buddy who can:

Save you time and effort

Boost your research productivity

Make research less stressful and more enjoyable

Picking the perfect AI research assistant can feel overwhelming. But fret no more! Here's a peek behind the curtain at how we select the AI assistants to bring you the top 10 list.

Accuracy is King: We prioritize assistants with an impressive track record of delivering accurate information and completing tasks flawlessly. Imagine a research partner that gets your facts straight every time!

Knowledge Powerhouse: The best assistants boast vast knowledge bases, able to answer your questions on nearly any topic. Whether it's obscure historical details or cutting-edge science, a top contender will have it covered.

Understanding Your Needs: We value assistants that can decipher your intent and respond accordingly. Imagine an assistant that anticipates what kind of information you need, saving you tons of time and effort.

Multilingual Mastery: Research shouldn't have language barriers! Top assistants can understand and respond in multiple languages, making them ideal for global research projects.

We also looked into the Reputation and Reliability of each Tool:

User Reviews and Ratings: What do actual researchers have to say about the assistant's effectiveness?

Data Source Credibility: Does the assistant rely on trustworthy sources for its information (e.g., peer-reviewed journals)?

Transparency and Explainability: Does it provide clear explanations for its findings and avoid presenting AI-generated content as absolute truth?

By applying these stringent criteria, we've curated a diverse selection of AI research assistants, each catering to specific research needs and budgets. From the comprehensive summaries of Elephas to the visual exploration offered by Connected Papers, there's a perfect companion waiting to transform your research experience.

Conclusion  

Choosing the right AI research assistant depends on your specific needs and research style. If you're a busy researcher juggling multiple projects, consider Elephas, a versatile tool with features like multi-AI integration, customizable writing styles, and an offline mode. For those on a budget, free options like Elicit and Lex AI offer valuable functionalities.

No matter your needs, there's an AI research assistant waiting to transform your research experience. Explore free trials and different features to find your perfect match. Elephas stands out for its comprehensive features and customizability, making it a powerful companion for researchers of all levels. Try out Elephas today and see how AI can supercharge your research journey!

1. Wha t does an AI research assistant do?

An AI research assistant tackles tedious tasks like summarizing complex papers, finding relevant articles through vast databases, and even explaining mind-bending scientific jargon in clear language. This frees you up to focus on the analysis and discovery that make research exciting.

While several AI research assistants offer valuable features, Elephas stands out for its versatility and customizability. Elephas integrates with various AI providers, letting you tailor writing styles to your needs. It can even work offline, making it a reliable companion wherever research takes you.

AI research assistants are like supercharged research partners. They can slash through time spent summarizing lengthy papers and pinpoint the most relevant studies from massive databases. AI can break them down into clear explanations. Some AI assistants can even help with formatting and citations.

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14 Best AI Research Assistants to Save Hundreds of Person-Hours

Artificial Intelligence (AI) is everywhere and has quickly become integral to daily living. Besides handsome robots like M3gan or Ex Machina, we’re talking about over 26,000 virtual assistants, chatbots, and applications that have transformed our lives and made them easier in innumerable ways.

Whether drafting emails or conducting in-depth research, internet-based AI tools have been designed to handle thousands of other diverse tasks. 

If you’re like most people, foraging through the forest of thousands of AI research assistants to find what fits your needs can be like trying to look for a needle in a haystack. Fortunately, we have compiled a list of the best AI research assistants that will save you hundreds of person-hours of work. Our comprehensive list will help you eliminate pesky busy work so you can concentrate on your other human issues.    

How AI Research Assistants Work?

According to an Infosys survey , over 76% of businesses already use or are considering using AI tools for their everyday processes. This makes it essential for everyone to learn about this nascent technology and how it works.

AI research assistants use machine learning (ML) and other tools that leverage natural language processing (NLP) to comb through tons of data and process information. These tools help ease the otherwise cumbersome and snail-paced research process, allowing you to get results faster and more confidently. 

AI research assistants are ideal for anyone with a stack and need to grasp complex research materials quickly – including students, researchers, and other professionals.

These automated tools are designed to help you quickly summarize data so you can understand the main points without necessarily reading to the last iota of the document. The applications can extract insights from reports by identifying key findings and trends from reviews, surveys, and industry reports.

Benefits of Using AI Research Assistants 

The foremost benefit of using AI-based research tools is their potential to save users time and money. Automating repetitive tasks such as manual data entry frees up your time for more strategic and creative work.

Better still, you also minimize the risks associated with human error, such as duplicates, typos, or missing data, which could compromise the reliability and quality of your desired outcomes. Moreover, AI research assistants can handle voluminous data and different formats, including handwritten or scanned documents, which can quickly tire you.        

Anyone who’s done research knows that much of the time will be spent writing reports. The good news is that AI research tools can be trusted here, too, as they’re designed with algorithms designed to make judgments and assumptions from the gathered data.

Once the system has analyzed the data, the algorithms will quickly generate reports, saving you time for other tasks. With AI research assistants, you don’t have to physically go through mounds of data to understand trends or make predictions.     

Whether screening candidates, gathering answers, analyzing data, or generating reports, AI research tools help streamline the market research process and help deliver faster than manual processes.

The most significant benefit of AI is the ability to eliminate errors and enhance precision and accuracy significantly. The decision to use AI is your answer to providing more accurate work but with more fantastic results without wearing yourself out altogether.

Finally, unlike humans, who are driven mainly by emotions, AI tools are highly rational and practical since they lack feelings in their approach. As a result, you can be guaranteed unbiased views that will lead to more accurate decision-making.  

Are you a professional researcher, scholar, or student devoting countless hours to struggling with research, sorting, writing, and organizing sources and overwhelmed with the abundance of information you must deal with?

Moreover, you’ll still be required to write informative, engaging, and well-written reports within a limited time. If that describes you and you’re struggling to find the right AI research tools, we present a list of the market leaders to make your work easier.      

Elicit is an AI research assistant using language models similar to GPT-3 to locate seed articles, mine keywords and subject headings, and automate researchers’ workflows.

Researchers mostly use Elicit for parts of literature review workflows where it returns alternate questions, relevant papers, and summaries that lead to other seed articles when you enter a question. 

Elicit shows the critical information contained in research papers in an easy-to-use table. Besides answering questions, the tool excels in brainstorming, text classification, and summarization tasks.

You need Elicit if you want to locate papers on a research topic quickly, analyze and organize multiple papers, summarize evidence from leading cited papers on a given topic, define terms, and define identity search terms.         

ResearchAIde

ResearchAIde is an AI-based tool specifically designed for students, researchers, and business people looking to quickly and efficiently extract and synthesize information from research papers.

With this tool, finding the information you need is hassle-free, and you don’t have to read entire research papers. Moreover, you can organize your work in one location and navigate through different documents using the tool’s seamless file feature.   

With ResearchAIde, you can access valuable insights within seconds using the tool’s power data extraction feature from over 5,000 research papers and at least 20,000 insightful answers to common questions. ResearchAIde’s most prominent benefits include time-saving, chatting to multiple files, and high-speed data extraction.    

Wizdom.ai is comprehensive research management software for researchers, academics, and students. The freely available Android-based app helps you search, add and manage an extensive library of publications available in the Wizdom.ai library as you move. Moreover, the app can be synced instantly across gadgets via the Wizdom.ai web and desktop.  

Wizdom.ai takes collaborative research writing to a new level as it enables users to create citations in a single click in more than 7,000 styles, including MLA, APA, Harvard, IEEE, Chicago, Vancouver, and others.

Whether you’re looking for books, journal articles, conference documents, newspaper articles, or webpage references, Wizdom.ai provides a rapidly expanding research landscape offering new and better solutions that are expanding the AI-based research landscape.

HyperWrite is an AI-enabled writing assistant designed to enhance writing speeds by finishing your sentences, thereby speeding up the entire process.

With HyperWrite, users can generate emails, blog posts, summaries, or rewrite large chunks of text. The tool’s newest feature is HyperChat, an additional AI-enabled chatbot that knows about anything you ask.   

Designed by OthersideAI, the tool facilitates more straightforward and effective communication by improving a user’s writing style through intuitive suggestions.

HyperWrite is built on a GPT-3 foundation and offers relevant suggestions and feedback on writing styles.

After analyzing your style, the app provides tailor-made recommendations besides offering a wide range of other features that facilitate research, organizing, analysis, and editing.    

What’s a scientific researcher in a new field to do when scanning over 30 million research papers online and over 3,000 others being published daily?

You can only enhance your chance around them using the award-winning  Iris.ai , a world-leading AI engine designed for scientific text research.

The comprehensive app is chock-full of research-related knowledge and provides several smart filters, auto-generated summaries, reading list analyses, systemized data, and autonomous extraction capabilities.        

Iris.ai performs specialized, interdisciplinary analyses that can save you over 75% and deliver results that weigh above human accuracy. The app’s top-of-the-range algorithms offer the best tabular data extraction, test similarity, entity disambiguation, and domain-specific entity representation learning and linking.

Moreover, it builds a comprehensive knowledge graph comprising all linkages and entities that facilitate its use and learning while giving feedback. 

Advanced data analytics tool  Minerva by AcademicID  is an AI-based research assistant targeting students, academics, and researchers. The tool employs advanced ML and NLP to offer accurate and insightful responses to various prompts and queries.

Once it receives a request, AcademicID reviews over 200 million academic papers to produce verifiable and up-to-date answers. 

Unlike other research assistants and chatbots, Minerva has access to the latest research papers, and since it’s available as a browser extension, it offers its users innovative tools anywhere.

Interested users can sign-up for the free-to-use tool on the AcademicID website to enjoy the personal research assistant that can enable a user to spend seconds on tasks that would otherwise take hours to accomplish. 

AI-powered research assistant  Typeset.io  is designed to provide simple answers and explanations to help users read, understand and learn more efficiently from research papers.

The tool facilitates searching relevant papers by connecting you to a network of related and relevant papers in one place without specifying keywords.

Moreover, the tool also offers a dedicated English Editing Service that improves and clarifies your writing, sharpens language, enhances clarity, and fixes errors to maximize impact without changing its meaning.  

Typeset.io also enables users to make their papers 100% compliant with required author guidelines – users can choose any journal format that pleases them.

With Typeset.io, you can easily access research papers, learn more efficiently and format your report easily, besides having direct access to numerous templates from leading publishers. 

Scholarcy is an online AI-powered article summarizing tool that scans articles, reports, research papers, and book chapters in seconds. The tool then automatically breaks them down into smaller sections so users can assess the relevance to their work.

Suppose you’re a student, researcher, journalist, or librarian. In that case, Scholarcy will help you identify critical information such as data analyses, study participants, and main findings, thereby reducing the time to evaluate a study by 70%. 

You can use Scholarcy to generate summary flashcards in Word or PDF formats in a well-structured and easily digestible form. The tool’s prominent features include table, figure, image extraction, access to source linking, and automatic reference extraction.

The app comes with Chrome and Edge browser extensions you can integrate with open-access repositories or create a collection of searchable summary cards accessible from multiple devices.   

Semantic Scholar

Semantic Scholar is an AI-enabled alternative to Google Scholar that gives access to millions of academic scholarly articles relevant to different topics. While its content focuses on journals, the tool integrates AI, ML, and NLP with semantic analytic research to facilitate more accurate search results. 

Semantic Scholar is an easy-to-use tool since you only need to enter your query in the search box, and you’re good to go. Users can research by author, keyword, paper, or topic, but they can still filter the search by date range, field of study, and publication type. 

Research Pal

This AI-enabled research assistant for Google Docs uses Natural Language Generation to generate high-quality text on Google Docs. 

Research Pal  is ideal for students, writers, and researchers to streamline their research, writing, and editing of documents. The tools feature multi-lingual supports, customizable settings, and advanced algorithms to improve the writer’s experience.

Whether you’re an individual or a business that must produce content regularly, you can avail of this tool for only $19 and save enormous amounts of time generating quality texts fast.     

MirrorThink

Powered by GPT-4, MirrorThink is designed to improve scientific research by offering researchers fast answers to their questions and methods. This single user-friendly research tool affords unlimited scientific research using advanced technology, which makes it an ideal partner for scientific research. 

MirrorThink users can perform numerous tasks, including exploring and analyzing existing academic journals to better understand specific research questions or topics.

Better still, there’s room for performing mathematical calculations to understand the logic behind them besides availing the latest trends in the scientific market. MirrorThink integrates Wolfram and Pubmed AI tools to deliver answers within seconds of sending queries.        

Scite is renowned for using the power of AI to help researchers locate and evaluate scientific publications using Smart Citation. The app displays the context of a citation besides showing whether it provides supporting or contrasting evidence to an article.

Designed to improve the discoverability of articles and raise their profile by indexing with Scite, the tool is used by researchers from numerous countries. Scite attracts thousands of new users weekly and generates a sizeable amount of traffic from authors providing new data for publishers, reporting whether it’s supported, contrasted, or its overall context.

The  OpenRead  platform offers users a comprehensive and intuitive solution for organizing, interacting with, and analyzing different literature formats, including research documents, journals, and papers.

The AI-powered tool features a question-and-answer system that quickly responds to questions about papers, saving researchers much time.   

The platform leverages AI technology to extract tables, figures, formulas, and any other significant details from research papers so users don’t have to do the tedious reading. Besides providing a system that enhances efficient note-taking and backlinking, OpenRead offers thousands of pre-built journal templates to make publishing easier for users. 

vLex is an intelligent AI-powered platform targeting legal professionals by giving them access to a wide range of legal and regulatory information on a single platform.

The tool uses cutting-edge technology such as data analytics to help individuals, small and large law firms, investigators, librarians, in-house counsels, and government departments access the most relevant and accurate information.  

Final Words

AI research assistants are changing how we research as students, scholars, or professional researchers. Besides allowing us to automate tedious, repetitive tasks, generating high-quality content, boosting productivity, and saving lots of time is now possible. Our list of AI tools above is only the tip of the iceberg.

Next, check out the best citation checker tools to improve your research.

Ask a question, get an answer backed by real research

1.2b citation statements extracted and analyzed

187 m articles, book chapters, preprints, and datasets.

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Read what research articles say about each other

scite is an award-winning platform for discovering and evaluating scientific articles via Smart Citations. Smart Citations allow users to see how a publication has been cited by providing the context of the citation and a classification describing whether it provides supporting or contrasting evidence for the cited claim.

Extracted citations in a report page

Never waste time looking for and evaluating research again.

Our innovative index of Smart Citations powers new features built to make research intuitive and trustworthy for anyone engaging with research.

Search Citation Statements

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Reference Check

Evaluate how references from your manuscript were used by you or your co-authors to ensure you properly cite high quality references.

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Explore pre-built journal dashboards to find their publications, top authors, compare yearly scite Index rankings in subject areas, and more.

Large Language Model (LLM) Experience for Researchers

Assistant by scite gives you the power of large language models backed by our unique database of Smart Citations to minimize the risk of hallucinations and improve the quality of information and real references.

Use it to get ideas for search strategies, build reference lists for a new topic you're exploring, get help writing marketing and blog posts, and more.

Assistant is built with observability in mind to help you make more informed decisions about AI generated content.

Here are a few examples to try:

"How many rats live in NYC?"

"How does the structure of a protein affect its function?"

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scite is an incredibly clever tool. The feature that classifies papers on whether they find supporting or contrasting evidence for a particular publication saves so much time. It has become indispensable to me when writing papers and finding related work to cite and read.

Emir Efendić, Ph.D

Maastricht University

As a PhD student, I'm so glad that this exists for my literature searches and papers. Being able to assess what is disputed or affirmed in the literature is how the scientific process is supposed to work, and scite helps me do this more efficiently.

Kathleen C McCormick, Ph.D Student

scite is such an awesome tool! It’s never been easier to place a scientific paper in the context of the wider literature.

Mark Mikkelsen, Ph.D

The Johns Hopkins University School of Medicine

This is a really cool tool. I just tried it out on a paper we wrote on flu/pneumococcal seasonality... really interesting to see the results were affirmed by other studies. I had no idea.

David N. Fisman, Ph.D

University of Toronto

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scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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I love using upword as a user; I use it for a mix of work & studying. The design is also like the cherry on the cake - it really reflects the brand and makes reading through boring PDF's much better.

I have tested Upword for several months and the results are impressive. I shared some of the output with colleagues who couldn't believe that the text had been created using a solution.

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Bringing Generative AI to the Web of Science

Francesca Buckland

VP, Product Management, Academia & Government

Generative AI presents enormous opportunities to transform how scientific and scholarly research is carried out. Faced with the pressure to publish, a more complex research environment to navigate, and growing administrative demands, researchers need better tools available to them. To meet these challenges, Clarivate™ is developing cutting-edge AI technology that will remove roadblocks in the research and publishing process and ultimately contribute to the betterment of research. We previously shared plans to develop and embed market-leading generative AI, including conversational discovery, into our academic solutions, and are delighted to announce that the Web of Science™ AI Research Assistant will be available for beta testing this December.

While generative AI’s potential to save researchers time and reduce workload is clear, there are concerns with employing the technology in a research setting. When generative AI fabricates scholarly references , for example, it demonstrates the potential to undermine research integrity and erode trust in scientific output without considered use. Researchers may rightly question whether they can trust the technology at this early stage in its lifecycle. Generative AI must be developed and implemented in research tools responsibly, which calls for a measured yet agile product development approach that includes input and guidance from the research community.

Partnering with the community to innovate

This is why our approach to implementing AI in the Web of Science is to partner with researchers and libraries to ensure the features we implement solve the most pertinent problems in ways that deliver trust in the technology and its application.

Current AI innovations already implemented in the Web of Science Core Collection™, the world’s only publisher-neutral, multidisciplinary citation index, were heavily guided by user feedback; enriched cited references provide a good example of this. In 2021 product teams and data scientists, guided by the Institute for Scientific Information™ , enriched cited reference data with additional facets to help users understand how and why an author cited a paper.

To ensure that we were capturing and presenting the most useful information for researchers, we consulted institutional development partners and carried out extensive user testing early in the process. To ensure accuracy and correctness, we collaborated with these partners to curate reliable, trustworthy data from the ground up. The outcome is a suite of features that help users conduct more targeted searches, locate must-read papers and delve into the ‘why’ behind citation counts.

Delivering useful information that improves the research process

We develop our products with the goal of serving up helpful insights along the user journey. Recommendations, enhanced data points and research indicators assist research stakeholders in determining their next step. Technology cannot make decisions for researchers, publishers, or organizational leaders, but it can greatly reduce manual effort spent on gathering and synthesizing information for further review.

To save time gathering information, AI is frequently leveraged to simplify the search experience for users. AI-enabled topic and keyword suggestions in the Web of Science help users quickly and efficiently narrow their searches and improve the relevancy of their results. Additional AI search improvements on the roadmap will help Web of Science users improve their queries with minimal effort, including semantic search, typeaheads, autocorrect, and personalized experiences.

When it comes to synthesizing information, literature reviews are an area with high potential for AI implementation. Literature reviews are valuable to the community because they provide a guide to a discipline or research topic—a helpful input for determining how to take research forward. There are many ways to summarize the research landscape on a topic with no single method being correct. Employing generative AI to automate literature reviews means that these helpful inputs into the research process can be delivered on a much larger scale.

While AI is well-positioned to improve research, researchers must feel confident in AI-delivered insights to consider them useful. The utility of generative AI responses ultimately depends on the trustworthiness of the data source used to generate them. Relying on the carefully curated, meticulously indexed Web of Science Core Collection dataset mitigates some risks posed by generative AI. Our selection and indexing policies ensure that users are discovering research from trusted, reliable sources evaluated by our independent, in-house editorial experts. Our consistent, accurate and complete indexing has created a thorough record of over a century of research.

Supporting researchers with smarter tools

We are implementing AI in the Web of Science with a focus on automating tasks that are labor intensive for researchers but do not require expertise, such as extracting, restructuring, summarizing, and presenting requested information from our meticulously structured metadata. The next step in our AI journey is the Web of Science AI Research Assistant, a generative-AI-powered tool that opens new modes of utility for users. Researchers can ask questions and more easily uncover the right answers from Web of Science data, with the AI Research Assistant cutting through the complexity of data and making connections between articles, as well as helping them to browse concise summaries of articles and results sets. With this new conversational capability, the Web of Science user will be more agile than ever, freeing up valuable time for activities that add new knowledge to the ecosystem.

We are consulting with our university development partners to ensure that we maximize the strength and suitability of generative AI for researchers. We are focused on ensuring the quality of the Web of Science AI Research Assistant before releasing it widely.

“We’re happy to be part of the Web of Science Development Partner Program, it will allow us to know deeply the new AI Research Assistant and how it can help our researchers.” Camila Gamba, Universidade de São Paulo

Combining our high-quality, reliable data and expertise, we partner with our customers to help them navigate the opportunities and risks that generative AI poses in a way that ensures confidence and value. Our collaboration with the research community is well underway to further develop this new capability. Let us know if you want to join the conversation.

Interested in becoming a beta tester? Let us know [email protected] .

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Introducing Copilot: Your AI assistant that helps explain papers

Here's one thing most of us agree on, processing information in research papers takes work. But wouldn't it be great if you could have AI explain papers to you no matter what the topic is, as you read, whenever you want?

Picture this: every time you see a complicated equation in research papers, you’d get an explanation of it right there on the same screen. Even better, imagine you can ask any number of follow-up questions and get answers to them instantly. That's exactly what you get with SciSpace Copilot !

Use this AI assistant to get explanations and answers on any research paper as you read. Works for tables, equations, diagrams, jargon, and even lengthy blocks of text. You don't have to pause and search for it elsewhere. And your learning flow won't be disrupted.

Critical thinking and problem-solving are the bedrock of research. Copilot provides all the contextual information you ask for in real-time. It gives you more time to think about the research and focus more on making inferences and drawing meaningful conclusions.

What is SciSpace Copilot?

Copilot is like your own personal research assistant. It is powered by artificial intelligence (AI), and sits on top of our research repository .

Whenever you need help, the AI research assistant is there to explain the paper, answer your queries, and provide you with the context you need within the same page.

How to use SciSpace Copilot to explain papers?

For starters, the AI assistant is available across all the 200 million+ papers on the SciSpace repository. So, you can simply search for the paper or topic you want to look up to get started.

Or, if you have the PDF stored on your device, you can sign up to SciSpace and then upload the same. Either way, Copilot explains papers and provides the answers you need.

It can assist you whether you're working on your literature review, catching up on the latest in your field, or just reading for fun.

Let's look at how SciSpace Copilot explains papers and helps you to read, break down, and understand them effectively.

1. Highlight text to understand them better

Came across unfamiliar terms or acronyms while reading a research paper? With Copilot, simply highlight it to get an explanation on the same screen.

It works for paragraphs too. So, next time you're stuck while reading a paper, just select the text which requires further elaboration. Get background information about what is being discussed in the passage — concepts, theories, methods and learn how they are relevant to the paper.

Use the summarize feature to get a condensed version of lengthy paragraphs, helping you grasp the main points quickly and efficiently. Employ the same feature to quickly figure out if a paper is worth reading.

2. Crop formulas and tables to learn their implications

Comprehending the math in a paper can be challenging. You can skim through and read the results, but what if there was a better option?

Now just clip every equation you see in a paper to get Copilot to explain the math to you. Glean more insights by breaking equations down step-by-step and making sense of their implications.

You can also crop tables for an overview of the data. It should help you analyze and examine the data more closely and gain more context into the conclusions drawn by the author.

3. Ask questions to get more context and clarity

Learning cannot be complete without questions. Asking questions is how you connect your existing knowledge with new information. You can, of course, refer to another text or reach out to authors or peers with your queries. But what if you need a quick answer so that you can keep reading?

Copilot makes that easy and instant. Just type in your query as you're reading, and the AI research assistant provides a relevant answer on the same page. Be it a technical question or something related to the theory or methodology. Ask any number of questions regarding the research paper.

On top of that, if Copilot's initial answer to a question fails to clarify your doubt completely, you can zero in on it with follow-up questions. You can also do the same if you want to dig deeper into the explanations you receive for excerpts and equations.

If you are unsure what to ask, Copilot provides preset questions for you to explore the paper. These pre-generated questions cover various aspects of the research and are designed to help you understand the topic comprehensively.

Besides generic questions like "What is the research question?" or "What are the key findings?", you'll get specific questions drawn from the paper you're reading. These questions are tailor-made to address key points in the research, facilitating a deeper understanding and encouraging critical thinking.

These are the three key ways you can use Copilot. In addition to this, you can converse with the AI research assistant in multiple languages. It can explain papers and provide answers in any language you choose. We currently support 75+ languages and plan to add many more.

And please know that your conversation with Copilot on a particular paper is automatically saved. This way, you can refer back to it anytime you need.

New additions to SciSpace Copilot

Since we released Copilot in November 2022, we have added many new features to improve your research reading workflow.

Here are some of the key changes:

Now connect your SciSpace Library with your Zotero Library. You can directly import PDFs of any research paper, conference proceeding, or preprint into your SciSpace Library and use Copilot to gain a deeper understanding.

You can also highlight key sections and add notes to the PDF as you read. And top it off by turning helpful explanations and answers from Copilot into notes — making it easy to review the paper in the future.

SciSpace Copilot is now available as a Chrome extension . It works everywhere, from Elsevier and Medium to YouTube.

New SciSpace Copilot feature update

In September 2023, we added a citation interlinking feature to ensure the answers Copilot generates are from an original source.

What is citation interlinking feature?

Now, SciSpace Copilot gives a citation backed answer to your every query!

First select the focus by clicking the '+' icon at the bottom left. Then, choose the source from which Copilot should fetch information.

• "Only this paper" — To get answers from your current PDF.
• "All SciSpace papers" — To get answers from our 270M+ papers.
• "My Library" — To get answers from your own PDF collection.

Next step is to ask a question to the Copilot about the paper you are reading.

Every answer the Copilot provides includes citations of the PDF the answer is extracted from. You can click the citation and see the exact section of the PDF the answer is extracted from.

By providing direct citations, you can immediately verify the accuracy and relevance of the answer, ensuring that the AI hasn't just generated a random or inaccurate response.

You can use SciSpace ResearchGPT – your new go-to tool for exploring research effortlessly!

Wrapping up

Copilot is still very much a work in progress. We are continuously working to enhance the features and make Copilot even more helpful for researchers and other research readers. The aim is to make research papers more interactive so that you get contextual help while reading.

We at SciSpace are working to make every published paper utilized to its optimum. Copilot is just the beginning; join us on our journey.

We’d love you to try it out and tell us about your experience. You can join our Discord Community , write to us on Twitter , or email us at [email protected] .

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SciSpace is an AI research assistant that simplifies researching papers through AI-generated explanations and a network showing connections between relevant papers. It aims to automate repetitive tasks in order to help researchers, publishers, and institutions collaborate more efficiently. SciSpace offers four main tools: Literature Review, PDF Data Extraction, AI Reading Co-pilot, and a Text Paraphraser. Together, these tools can make research much easier – allowing you to do things like ask the AI to simplify terms and explain complex concepts.

SciSpace’s free plan gives you access to the basic AI copilot chat, while the other tools have limitations in place (such as only being able to extract data from 10 PDFs). The monthly premium plan gives you full access to all of the tools, and also uses a more advanced AI model allowing the copilot chat to give better answers.

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Introducing Hotjar AI

The AI-powered research assistant that helps you find the insights you need.

Last updated

Reading time.

Before we get to all the exciting AI stuff, we should mention that we’ve recently added groan- and eye roll-detection to our existing rage click and u-turn features, making it easier than ever to identify when a user has heard it all before and simply isn’t buying it…

Okay, that’s not a real feature—we promise! But we’re still pretty sure we detected some eye-rolling at the prospect of yet another software company jumping on the artificial intelligence (AI) bandwagon.

Don’t worry, we’re not here to generate even more hype about AI. We want to show you the first AI-powered features we’re adding to Hotjar , and talk about the opportunities we’re exploring to solve real user problems with our new AI assistant, Hotjar AI.

AI-generated TL;DR

Given our topic, it seemed appropriate to ask an AI assistant to summarize the rest of this post into four short bullet points. This is its unedited summary:

Say 'hi' to Hotjar AI

We’ve already begun adding AI-powered features to Hotjar, with the initial focus on our Surveys tool.

Let’s take a look at the first tasks Hotjar AI can help you with:

Create surveys in a click

Hotjar Surveys is a great tool for gathering feedback from your users, but the insights you get are only as good as the questions you ask. 

With the new survey generator , you can simply tell Hotjar AI what your research goal is—say, 'measure user satisfaction', for example. It will create the survey for you and ensure you’re asking the right questions to get the actionable insights you need.

The AI-powered Hotjar survey generator is live and available to try for free

Instantly summarize survey findings

User insights collected in open-ended survey responses can be incredibly valuable, but it can also be extremely time-consuming to analyze them all and extract actionable insights. 

With automated summary reports , Hotjar AI will analyze your open-ended survey responses and provide you with a summary of the findings, quotes to support those findings, and actionable recommendations for next steps.

The BETA version of automated summary reports is now available in our free Basic plan.

The AI opportunity

While we’re very excited about the value these first applications of Hotjar AI will bring to our users, we know that we’re only scratching the surface.

We’re building Hotjar to inspire change through empathy. But it’s difficult to develop genuine empathy with your users if you feel like you’re adrift in a sea of data, and lacking the time and resources to turn that data into genuine insight. That’s exactly where Hotjar AI comes in.

Your AI-powered research assistant

A few years ago, you might have been forgiven for thinking that AI was just another tech fad. But recent advances have unlocked a huge number of practical applications.

AI assistants have developed the ability to:

Refer to specific domain expertise, as well as general knowledge

Follow complex instructions and solve difficult problems

Create, collaborate, and iterate on writing tasks

Accept images as inputs and generate analyses

Handle large volumes of text

Recent advancements in AI have transformed marketing, product management, and user research, enabling businesses to analyze extensive data and understand consumer behavior. This has unlocked new possibilities and made it essential to leverage AI's power for customer-centric innovation.

In the Hotjar context, we like to think of Hotjar AI as a 'research assistant', here to help our users find the insights they need. The kicker is that this particular research assistant is immensely intelligent, and works around the clock at lightning speed. ⚡

Now, imagine giving that super research assistant access to Hotjar’s already-powerful user research tools—Heatmaps, Recordings, Funnels, Trends, Surveys, Feedback, and Interviews—with the ability to create, analyze, summarize, and make recommendations.

You can see why we’re just a little excited to bring AI to Hotjar.

We're only scratching the surface of what is possible with Hotjar AI. 

We want Hotjar AI to be your assistant, helping you become a champion in your job. With Hotjar AI doing all the heavy lifting, you'll save precious time that you can spend on the people who matter the most: your customers.

What’s next for Hotjar AI?

You’ll start to see Hotjar AI popping up to offer its help in more places across our platform in the near future. From speaking with our users, we identified some quick wins for AI in Surveys, but we’re already working on introducing it in other areas. 

Our team will continue to evaluate potential AI-powered features based on what adds the most value to the largest number of our users , and aim to get those features into your hands as quickly as possible.

If you’d like to learn more about the emergence of AI, as well as our plans for Hotjar AI, we’ll be hosting a free webinar with Hotjar CEO, Mohannad Ali, on Thursday, June 15th, at 4pm CET / 10am EST.

In the meantime, why not give the Hotjar AI-powered survey generator a spin?

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Merlin - Ask AI to Research, Write & Review

8.7K ratings

26-in-1 Chrome extension to Research, Re-write, and Summarise content on any website

Merlin is an All-in-One AI Assistant powered by GPT-4 that helps in: 1. Summarize: Get a jist of blogs, YouTube videos, research papers, and websites 2. AI Writer: Make content for social media, emails, art, code and more 3. Plugins: Get the best AI plugins on the browser (like AI Chat, Chat with PDFs, Chat with web access) It's free to download and use. We are keeping user privacy as the priority and we are in the process of getting SOC, GDPR, and ISO compliance as well. 🚀 How to use ? 🔸Click the "Add to Chrome" button and pin it to your toolbar. 🔸Log into your account. 🔸Press Cmd/Ctrl+M to activate Merlin. 🔸Get started with AI! 💻 Feature Highlights: 💡 AI Chat: Open the Sidebar to start chat & ask about anything easily. 💡 Copywriting: Easily create social content, blogs, and ad copies. 💡 ChatPDF: Summarize or Chat with any PDF to get concise information & save time. 💡 WebChat: Summarize or Chat with any website content to read what matters. 💡 Grow your audience on LinkedIn & Twitter - Generate unique social media content and comments to increase engagement 💡 Search Enhance: Get concise AI answers next to search tools like Google, Bing, Baidu, or Yahoo. 💡 Web Access: Get the right content with real-time internet access. 💡 AI replies on Emails- enabling you to send appropriate responses with just a click, no typing needed. 💡 YouTube Video summary: Quickly summarize video content without wasting time watching long videos. 💡 AI Art: Convert your words into visuals. ❓ Frequently Asked Questions: 📌 What search engines are supported by you? Currently, we supports Google, Bing, DuckDuckGo, Baidu, and more search engines. 📌 Do I need a ChatGPT/OpenAI account? No, you do not need to have a Chat GPT account to use this extension. You can create an account for free on our website. 📌 Chat GPT is banned in my country. Does this extension work in my country? Yes. we are available in all countries. 📌 Is it free to use? Yes, we offers 102 queries every day for free. For unlimited access, you can choose the Pro Plans when you wish to scale. 📌 What is the relationship between this extension and ChatGPT? This AI tool is built on the ChatGPT API model. 📪 Contact us: Any questions or suggestions? Please contact us at 💌 [email protected] Try Merlin AI now and experience the powerful AI assistants.

4.8 out of 5 8.7K ratings Google doesn't verify reviews. Learn more about results and reviews.

fisiha firdie Jun 9, 2024

the perfect of all ai that is god to her! I think the cast is quite good as well: Colin Morgan is charmingly dorky as the title character; Anthony Head milks a surprising amount of emotion All in one solution for AI tools. Very great and helpful extension. I use it always for everything from doing research to get advice. Oh Merlin. Four years since I finished my last re-watch and you're still breaking my heart. You are quite terrible in many ways, with some of the cheesiest special effects I... Show more

Adam Ratajczyk Jun 7, 2024

Merlin - Ask AI to Research, Write & Review handles the following:

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IBM® watsonx™ AI and data platform includes three core components and a set of AI assistants designed to help you scale and accelerate the impact of AI with trusted data across your business. Enterprises are turning to watsonx because it is:

• Open : Based on open technologies that provide a variety of models to cover enterprise use cases and compliance requirements.
• Targeted : Targeted to specific enterprise domains like HR, customer service or IT operations to unlock new value. 
• Trusted : Designed with principles of transparency, responsibility and governance so you can manage legal, regulatory, ethical and accuracy concerns.
• Empowering : Go beyond being an AI user and become an AI value creator, owning the value your models create.

Get personalized insights in seconds with your AI-powered business analyst and advisor

Book a meeting with watsonx.ai product specialists

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Explore what you can do with watsonx to deploy and embed AI across your business. 

The watsonx platform has three components, allowing you to customize your AI solution. Choose one or more components that align with your needs.

Train, validate, tune and deploy foundation and machine learning models with ease.

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Accelerate responsibility, transparency and explainability in your data and AI workflows with watsonx.governance. 

AI assistants are applications powered by watsonx. Deploy them to automate workflows and implement AI across a variety of business and technical functions such as customer service, HR and code development. 

Read the complete 2024 buyer’s guide: IBM generative AI assistants

Designed to create exceptional customer service experiences, IBM watsonx™ Assistant™ empowers everyone in the organization to build and deploy AI-powered virtual agents without writing a line of code.

IBM watsonx™ BI Assistant answers your business questions in seconds, guiding you toward the most impactful decisions. Get personalized insights in seconds with your AI-powered business analyst and advisor.

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AI agents for the smart home

Back in the day, the saying was computers don’t lie . They were deterministic, zeros and ones executing the rules we gave them. With AI, this is the opposite. AI models hallucinate and their output cannot be completely trusted – yet the current hype is to infuse AI into every product imaginable. Home Assistant doesn’t jump on the latest hype, instead we focus on building a lasting and sustainable smart home. We do have thoughts on the subject, so let’s talk about AI in the smart home.

Home Assistant is uniquely positioned to be the smart home platform for AI. As part of our Open Home values , we believe users own their own data (a novel concept, we know) and that they can choose what happens with it. That’s why Home Assistant stores all user data locally, including rich history, and it offers powerful APIs for anyone to build anything on top – no constraints. Empowering our users with real control of their homes is part of our DNA , and helps reduce the impact of false positives caused by hallucinations. All this makes Home Assistant the perfect foundation for anyone looking to build powerful AI-powered solutions for the smart home - something that is not possible with any of the other big platforms.

As we have researched AI ( more about that below ), we concluded that there are currently no AI-powered solutions yet that are worth it. Would you want a summary of your home at the top of your dashboard if it could be wrong, cost you money, or even harm the planet ?

Instead, we are focussing our efforts on allowing anyone to play with AI in Home Assistant by making it easier to integrate it into existing workflows and run the models locally. To experiment with AI today, the latest release of Home Assistant allows you to connect and control devices with OpenAI or Google AI. For the local AI solutions of the future, we are working with NVIDIA, who have made amazing progress already. This will unleash the power of our community, our collective intelligence, to come up with creative use cases.

Read more about our approach, how you can use AI today, and what the future holds. Or jump straight in and add Google AI , OpenAI to your Home Assistant installation (or Ollama for local AI without the ability to control HA yet).

Huge thanks for contributing: @shulyaka , @tronikos , @allenporter , @synesthesiam , @jlpouffier and @balloob .

The foundation for AI experimentation in the smart home

We want it to be easy to use LLMs together with Home Assistant. Until now, Home Assistant has allowed you to configure AI agents powered by LLMs that you could talk with, but the LLM could not control Home Assistant. That changed this week with the release of Home Assistant 2024.6 , which empowered AI agents from Google Gemini and OpenAI ChatGPT to interact with your home. You can use this in Assist ( our voice assistant ) or interact with agents in scripts and automations to make decisions or annotate data.

Using agents in Assist allows you to tell Home Assistant what to do, without having to worry if that exact command sentence is understood. Even combining commands and referencing previous commands will work!

And because this is just Assist, it works on Android , iOS , classic landline phones , and $13 voice satellites 😁

The architecture that allows LLMs to control Home Assistant is, as one expects from us, fully customizable. The default API is based on Assist, focuses on voice control, and can be extended using intents defined in YAML or written in Python ( examples below ).

The current API that we offer is just one approach, and depending on the LLM model used, it might not be the best one. That’s why it is architected to allow custom integrations to provide their own LLM APIs . This allows experimentation with different types of tasks, like creating automations. All LLM integrations in Home Assistant can be configured using any registered custom APIs.

The options screen for an AI agent allows you to pick the Home Assistant API that it has access to.

Cloud versus local

Home Assistant currently offers two cloud LLM providers with various model options: Google and OpenAI. Both integrations ship with a recommended model that balances price, accuracy, and speed. Our recommended model for OpenAI is better at non-home related questions but Google’s model is 14x cheaper, yet has similar voice assistant performance.

We see the best results with cloud-based LLMs, as they are currently more powerful and easier to run compared to open source options. But local and open source LLMs are improving at a staggering rate. This is important because local AI is better for your privacy and, in the long term, your wallet. Local models also tend to be a lot smaller, which means a lot less electricity is used to run them.

To improve local AI options for Home Assistant, we have been collaborating with NVIDIA’s Jetson AI Lab Research Group , and there has been tremendous progress. They have published text-to-speech and speech-to-text engines with support for our Wyoming Protocol , added support for Ollama to their Jetson platform and just last week showed their progress on making a local Llama 3 model control Home Assistant:

The first 5 minutes, Dustin shows his prototype of controlling Home Assistant using a local LLM.

What is AI?

The current wave of AI hype evolves around large language models (LLMs), which are created by ingesting huge amounts of data. When you run these models, you give it text and it will predict the next words. If you give it a question as input, the generated next words will be the answer. To make it a bit smarter, AI companies will layer API access to other services on top, allowing the LLM to do mathematics or integrate web searches.

One of the biggest benefits of large language models is that because it is trained on human language, you control it with human language. Want it to answer in the style of Super Mario? Just add “Answer like Super Mario” to your input text and it will work.

There is a big downside to LLMs: because it works by predicting the next word, that prediction can be wrong and it will “hallucinate”. Because it doesn’t know any better, it will present its hallucination as the truth and it is up to the user to determine if that is correct. Until this problem is solved, any solution that we create needs to deal with this.

Another downside is that depending on the AI model and where it runs, it can be very slow to generate an answer. This means that using an LLM to generate voice responses is currently either expensive or terribly slow. We cannot expect a user to wait 8 seconds for the light to be turned on when using their voice.

Last January, the most upvoted article on HackerNews was about controlling Home Assistant using an LLM. I commented on the story to share our excitement for LLMs and the things we plan to do with it. In response to that comment, Nigel Nelson and Sean Huver, two ML engineers from the NVIDIA Holoscan team, reached out to share some of their experience to help Home Assistant. It evolved around AI agents.

AI agents are programs that run independently. Users or other programs can interact with them to ask them to describe an image, answer a question, or control your home. In this case, the agents are powered by LLM models, and the way the agent responds is steered by instructions in natural language (English!).

Nigel and Sean had experimented with AI being responsible for multiple tasks. Their tests showed that giving a single agent complicated instructions so it could handle multiple tasks confused the AI model. One didn’t cut it, you need multiple AI agents responsible for one task each to do things right. If an incoming query can be handled by multiple agents, a selector agent approach ensures the query is sent to the right agent.

The NVIDIA engineers, as one expects from a company selling GPUs to run AI, were all about running LLMs locally. But they had a point: running LLMs locally removes the constraint on what one can do with LLMs. You start to consider different approaches if you don’t have to be concerned about raking up a cloud bill in the thousands of dollars.

For example, imagine we passed every state change in your house to an LLM. If the front door opens at night while everyone is home, is that suspicious? Creating a rule-based system for this is hard to get right for everyone, but an LLM might just do the trick.

It was this conversation that led us to our current approach: In Home Assistant we want AI agents. Many AI agents.

Defining AI Agents

As part of last year’s Year of the Voice , we developed a conversation integration that allowed users to chat and talk with Home Assistant via conversation agents. Next to Home Assistant’s conversation engine, which uses string matching, users could also pick LLM providers to talk to. These were our first AI agents.

Set up Google Generative AI , OpenAI , or Ollama and you end up with an AI agent represented as a conversation entity in Home Assistant. For each agent, the user is able to configure the LLM model and the instructions prompt. The prompt can be set to a template that is rendered on the fly, allowing users to share realtime information about their house with the LLM.

The conversation entities can be included in an Assist Pipeline, our voice assistants. Or you can directly interact with them via services inside your automations and scripts.

As a user, you are in control when your agents are invoked. This is possible by leveraging the beating heart of Home Assistant: the automation engine. You can write an automation, listen for a specific trigger, and then feed that information to the AI agent.

The following example is based on an automation originally shared by /u/Detz on the Home Assistant subreddit . Every time the song changes on their media player, it will check if the band is a country band and if so, skip the song. The impact of hallucinations here is low, the user might end up listening to a country song or a non-country song is skipped.

We’ve turned this automation into a blueprint that you can try yourself. It allows you to configure the criteria on when to skip the song.

Researching AI

One of the weird things about LLMs is that it’s opaque how they exactly work and their usefulness can differ greatly per task. Even the creators of the models need to run tests to understand what their new models are capable of. Given that our tasks are quite unique, we had to create our own reproducible benchmark to compare LLMs.

To make this possible, Allen Porter created a set of evaluation tools including a new integration called “Synthetic home” . This integration allows us to launch a Home Assistant instance based on a definition in a YAML file. The file specifies the areas, the devices (including manufacturer/model) and their state. This allows us to test each LLM against the exact same Home Assistant state.

We’ve used these tools extensively to fine tune the prompt and API that we give to LLMs to control Home Assistant. The reproducibility of these studies allows us to change something and repeat the test to see if we can generate better results. We are able to use this to test different prompts, different AI models and any other aspect.

Defining the API for LLMs

Home Assistant has different API interfaces. We have the Home Assistant Python object, a WebSocket API, a REST API, and intents. We decided to base our LLM API on the intent system because it is our smallest API. Intents are used by our sentence-matching voice assistant and are limited to controlling devices and querying information. They don’t bother with creating automations, managing devices, or other administrative tasks.

Leveraging intents also meant that we already have a place in the UI where you can configure what entities are accessible, a test suite in many languages matching sentences to intent, and a baseline of what the LLM should be able to achieve with the API.

Home Assistant already has different ways for you to define your own intents, allowing you to extend the Assist API to which LLMs have access. The first one is the intent script integration . Using YAML, users can define a script to run when the intent is invoked and use a template to define the response.

We haven’t forgotten about custom components either. They can register their own intents or, even better, define their own API.

Custom integrations providing their own LLM APIs

The built-in LLM API is focused on simplicity and being good at the things that it does. The larger the API surface, the easier AI models, especially the smaller ones, can get confused and invoke them incorrectly.

Instead of one large API, we are aiming for many focused APIs. To ensure a higher success rate, an AI agent will only have access to one API at a time. Figuring out the best API for creating automations, querying the history, and maybe even creating dashboards will require experimentation. When all those APIs are in place, we can start playing with a selector agent that routes incoming requests to the right agent and API.

To find out what APIs work best is a task we need to do as a community. That’s why we have designed our API system in a way that any custom component can provide them . When configuring an LLM that supports control of Home Assistant, users can pick any of the available APIs.

Custom LLM APIs are written in Python. When a user talks to an LLM, the API is asked to give a collection of tools for the LLM to access, and a partial prompt that will be appended to the user prompt. The partial prompt can provide extra instructions for the LLM on when and how to use the tools.

Future research

One thing we can do to improve AI in Home Assistant is wait. LLMs, both local and remotely accessible ones, are improving rapidly and new ones are released regularly (fun fact, I started writing this post before GPT4o and Gemini 1.5 were announced). Wait a couple of months and the new Llama, Gemini, or GPT release might unlock many new possibilities.

We’ll continue to collaborate with NVIDIA to enable more local AI functionalities. High on our list is making local LLM with function calling easily accessible to all Home Assistant users.

There is also room for us to improve the local models we use. We want to explore fine-tuning a model for specific tasks like voice commands or area summarization. This would allow us to get away with much smaller models with better performance and reliability. And the best thing about our community? People are already working on this .

We also want to see if we can use RAG to allow users to teach LLMs about personal items or people that they care about. Wouldn’t it be great if Home Assistant could help you find your glasses?

We hope that you’re going to give our new AI tools a try and join us on the forums and in the #voice-assistants channel on our Discord server . If you find something cool, share it with the community and let’s find that killer use case!

College & Research Libraries News  ( C&RL News ) is the official newsmagazine and publication of record of the Association of College & Research Libraries,  providing articles on the latest trends and practices affecting academic and research libraries.

C&RL News  became an online-only publication beginning with the January 2022 issue.

Leo S. Lo is dean of the College of University Libraries and Learning Sciences at the University of New Mexico, email: [email protected] .

Victoria Anderson is administrative assistant at the University of New Mexico, email: [email protected] .

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Leo S. Lo and Victoria Anderson

AI Reskilling in Libraries

When the Dean’s Assistant Gets an AI Assistant

Leo S. Lo is dean of the College of University Libraries and Learning Sciences at the University of New Mexico, email: [email protected] . Victoria Anderson is administrative assistant at the University of New Mexico, email: [email protected] .

©2024 Leo S. Lo and Victoria Anderson

T he rapid advancement of generative AI represents a pivotal moment for libraries. With powerful systems like ChatGPT gaining widespread adoption, libraries face both opportunities and an urgent need to reskill staff. Recent analyses by the Boston Consulting Group predict that within two decades more than 30% of activities across most jobs could be handled by machines, while more than 15% of jobs could be fully automated. 1 According to the World Economic Forum’s “The Future of Job Report 2023,” training workers to use AI tools is considered one of the top priorities for many companies. 2 A 2023 survey of academic library employees revealed enthusiasm for professional development around generative AI, yet fewer than 7% of respondents currently use premium versions of leading systems. 3 This discrepancy risks leaving library workers unprepared for AI-assisted workflows and roles forecast to be pervasive within the next decade. 4 As libraries undergo their digital transformation, developing AI literacy among staff at all levels is becoming a matter of competitive survival rather than just innovation.

To proactively spearhead closing this emerging literacy and capability gap, the University of New Mexico College of University Libraries and Learning Sciences launched the pioneering GPT-4 Exploration Program in summer 2023. This initiative provided 10 faculty and staff with funded access to GPT-4, the premium iteration of ChatGPT. By facilitating hands-on experience with leading-edge AI, we sought to cultivate deeper technological literacy and equip our community to reenvision library services, research, and instruction for an AI-assisted era.

Crucially, the program spotlighted reskilling as an urgent priority. As AI systems grow more advanced, all library workers must have opportunities to better understand and use these technologies to enrich their careers. This access gap hinders professional capability and innovation. By detailing the dean’s vision in creating this pilot and the firsthand insights of the dean’s assistant, this article illuminates the profound need to expand AI literacy and upskilling programs across libraries. Equipping staff at all levels with premium generative AI will drive progress in realigning skill sets for the future.

Dean’s Perspective on Designing the Pilot Program—Leo S. Lo

In developing the GPT-4 Exploration Program, we turned to proven adult education practices to maximize reskilling outcomes. Aligning with Malcolm Knowles’ principles, 5 we emphasized hands-on, self-directed learning driven by professional needs and interests. Rather than lectures on AI, participants chose personalized projects to actively upskill through practice. This immersive approach spurs more active reskilling.

The program comprises three phases: Introduction and Training (two weeks), Exploration and Experimentation (eight weeks), and Evaluation and Sharing (two weeks). This arc builds community and enriches learning. Training provides baseline knowledge before the heart of exploration. Participants then reconvene in reflection, cementing gains through peer sharing. Central to our vision was an interdisciplinary community advancing together. The cohort model breeds collaboration beyond silos, enriching perspective and buy-in. United by curiosity despite divergent backgrounds and skill levels, participants enhanced both their personal capabilities and our college’s broader culture of innovation.

Among the 10 members from varied roles, my assistant Victoria Anderson brought critical administrative representation. Her participation modeled cross-functional reskilling. Beginning as an AI novice, Victoria flourished over 12 weeks, attaining hard skills and perspective to steward administrative adoption of AI systems. Her journey typified the immense reskilling potential in our untapped workforce once given access and community.

Administrative Assistant’s Experience Using AI—Victoria Anderson

As the dean’s assistant, I eagerly joined the GPT-4 Exploration Program despite my limited prior AI experience. Over 12 weeks, integrating ChatGPT and its premium version, GPT-4, fundamentally upgraded my workflow. I honed skills in using prompts to have GPT-4 assist me with a variety of administrative tasks. For clarity and simplicity throughout this piece, I will refer to both versions of the tool collectively as GPT-4.

The Evolving Role of Administrative Support

Administrative assistants and coordinators play an integral role in the operations of any organization. As institutions evolve to meet strategic priorities, so too must administrative support roles. Increasingly, the responsibilities encompass managing schedules, travel logistics, documentation, correspondence, and critical support services for leadership figures like deans or executives. This multifaceted and dynamic position requires adaptability, critical thinking, and efficiency even as responsibilities shift over time.

Integrating AI by administrative personnel can enhance workflows by automatically handling time-intensive coordination tasks and improving productivity in written communications. However, to unlock this potential, universities and companies must invest in reskilling programs tailored to support staff needs in understanding leading-edge technologies like generative AI. Organizations that equip administrative teams with the latest automation tools and skills training will gain tremendous advantage.

Enhancing Daily Workflow with GPT-4 Integration

One major time saver was using GPT-4 to take meeting minutes. By recording meetings, uploading the audio to a transcription tool, then copying the text into GPT-4, I could prompt it to “create detailed meeting minutes in a bulleted format summarizing the key discussion points and action items from this meeting transcript.” This condensed hours of work into a polished 2–3-page summary showcasing the most relevant details and decisions ready for distribution in less than 30 minutes. I estimate this saved me 3–5 hours per week of manual notetaking and write-up.

However, it is important to note that we were careful in considering what information was provided to the system, as we are still learning about how these AI tools use and potentially retain data. For example, I would always redact all personal details, sensitive information, or proprietary organizational data in the transcript before uploading it to GPT-4. By taking steps around responsible data use, libraries can use the immense time-savings of AI tools like GPT-4 safely and ethically.

GPT-4 also streamlined communications. Whether helping craft emails to reschedule a series of complex meetings for the dean or summarizing lengthy documents into digestible briefing papers (reducing a 12-page report to 2 pages), GPT-4 boosted productivity. For example, to condense a long text, I would prompt “Please summarize the key points from this 12-page report in 2 pages in a bulleted format covering the main recommendations.” Additionally, GPT-4’s integration with tools like Kayak’s travel booking functionality automated logistics coordination. By describing the dean’s upcoming conference travel needs in chat, the Kayak bot would automatically find flight options, saving me hours of searching.

I learned prompting is a skill requiring practice—initial outputs might not match the tone or depth needed. However, each week I gained more proficiency in getting useful content quickly. I also heeded guidance from the dean on responsible data use—we ensured no sensitive information was uploaded to GPT-4 given uncertainties around OpenAI’s data policies.

Challenges and Adjustments

While integrating GPT-4 into my workflows yielded significant time savings and productivity gains, the process was not without some needed adjustments. As I was learning how to best prompt the AI, I noticed some key challenges emerge.

GPT-4’s initial responses would sometimes lack the specificity, creativity, or tone that aligned with my communication style and needs. When asking it to generate emails to reschedule meetings, the language was often overly formal or verbose. Additionally, when seeking input on contributing to strategic goals around open education resources, the examples provided did not demonstrate a deep understanding of my administrative coordinator role.

I realized that mastering use of AI requires learning how to properly frame questions and prompt responses. Through trial and error and guidance from the dean on prompt formulation, I was able to improve results over time. However, it became clear that GPT-4 serves more as an augmentation tool, providing supportive content that almost always requires some degree of revision. The back-and-forth to refine responses also introduced some inefficiencies.

To address these challenges, I focused on shifting my mindset when using GPT-4. Rather than expecting fully formed solutions from the AI, I started to view it as a collaborative tool—asking it to “assist me with” tasks rather than relying on it to complete things independently. This helped set proper expectations and in turn improved my prompts and post-processing of its outputs.

While integrating AI did require conquering a learning curve, doing so has unlocked immense potential for upgrading my productivity and contribution. My experience shows that with the right support and training, administrative professionals at all skill levels can overcome initial challenges and thrive with the assistance of leading-edge AI.

Conclusions and Next Steps

The success of our inaugural GPT-4 Exploration Program confirms the immense value of hands-on AI reskilling initiatives. More than 70% of participants achieved expanded fluency with GPT-4, drastically exceeding baseline proficiency. As participants become ambassadors sharing insights with peers, our broader culture of AI readiness strengthens.

Building on this momentum, we will launch an evolved version of the program focused on an alternate leading AI system. Our consistent vision remains experiential, community-based learning in an emergent technology. Enhanced content on ethics and specialized projects tailored to academic applications will enrich the next iteration.

Additionally, we will catalyze wider adoption by collaborating with other campus departments on AI literacy programs. Inspired by Victoria’s transformative journey, we also advocate concentrated reskilling for administrative staff as an immense opportunity. Victoria’s agility in deploying GPT-4 for coordinating events and communications revealed automation’s sizable efficiency potential in critical support roles.

However, her experience also highlighted AI’s practical limitations regarding creativity and judgment. As powerful as these tools are, responsible implementation in both administrative and academic realms requires recognizing AI as an assistive rather than completely autonomous solution. By transparently conveying both potentials and pitfalls, our expanded programs will empower the wider university community to evaluate and integrate AI with care and confidence.

Our pilot program has evidenced the value of equipping learners at all levels with premium access and training for emergent technologies like GPT-4. We urge institutions globally to prioritize on-ramping communities to AI through hands-on, ethically grounded learning programs proven to unlock incredible capability.

• Sagar Goel and Orsolya Kovács-Ondrejkovic, “Reskilling for a Rapidly Changing World,” BCG Global, September 22, 2023, https://www.bcg.com/publications/2023 /reskilling-workforce-for-future .
• World Economic Forum, “The Future of Jobs Report 2023,” May 2023, https://www.weforum.org/publications/the-future-of-jobs-report-2023/digest/ .
• Leo S. Lo, “Evaluating AI Literacy in Academic Libraries: A Survey Study with a Focus on U.S. Employees,” University of New Mexico Digital Repository, 2024, https://digitalrepository.unm.edu/ulls_fsp/203 .
• Kweilin Ellingrud, Saurabh Sanghvi, Gurneet Singh Dandona, Anu Madgavkar, Michael Chui, Olivia White, and Paige Hasebe, “Generative AI and the Future of Work in America,” McKinsey & Company, July 26, 2023, https://www.mckinsey.com/mgi/our -research/generative-ai-and-the-future-of-work-in-america .
• Malcolm S. Knowles, Elwood F. Holton III, and Richard A. Swanson, The Adult Learner: The Definitive Classic in Adult Education and Human Resource Development (Milton Park, UK: Routledge, 2014).

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Adobe (ADBE) Boosts Generative AI Offerings With AI Assistant

Adobe ( ADBE Quick Quote ADBE - Free Report ) is benefiting from strengthening generative AI capabilities. The solid momentum of its family of creative, generative AI models, Firefly, is a major positive. In order to deliver enhanced experiences to various enterprises and customers, the company is constantly making efforts to bolster its generative AI-backed offerings. The latest move of making Adobe Experience Platform (“AEP”) AI Assistant generally available is a testament to the same. AEP AI Assistant is capable of answering technical questions, automating tasks, simulating outcomes, and generating new audiences seamlessly. It enables enterprises to boost their productivity through its conversational interface, which provides a deeper understanding of data and an ability to streamline workflows. It also helps in generating entire marketing assets, such as emails and web pages with copy, design and images via Adobe Firefly. The underlined AI assistant is integrated into Adobe Experience Cloud applications, such as Real-Time Customer Data Platform, Adobe Journey Optimizer and Customer Journey Analytics. Hence, the latest move is expected to contribute to the Digital Experience segment performance and Experience Cloud subscriptions in the near term. In first-quarter fiscal 2024, the segment generated revenues of $1.29 billion, up 10% on a year-over-year basis. Experience Cloud subscription revenues were $1.16 billion, rising 12% from the year-ago quarter. Strengthening the Digital Experience segment will, in turn, aid Adobe’s overall financial performance. The Zacks Consensus Estimate for fiscal 2024 total revenues is pegged at $21.42 billion, indicating year-over-year growth of 10.4%. The same for fiscal 2024 earnings is pegged at $17.96 per share, implying a year-over-year rise of 11.8%.

Adobe Inc. Price and Consensus

Adobe Inc. price-consensus-chart | Adobe Inc. Quote

Growing Generative AI Solutions Aid Prospects

Per a Grand View Research report, the generative AI market size is expected to witness a CAGR of 36.5% between 2024 and 2030. The Zacks Rank #3 (Hold) company is well-poised to capitalize on this growth prospect on the back of its strengthening generative AI-powered portfolio of solutions. You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here .

Adobe’s unveiling of the Firefly Image 2 Model, Firefly Vector Model and Firefly Design Model to mark a significant advancement in its creative generative AI model family, enhancing creative control, image quality and illustrator capabilities, remains noteworthy. The company recently unveiled Generative Remove in Adobe Lightroom, which is a powerful Firefly-backed tool that helps remove unwanted objects from any photo in a single click in a non-destructive manner. The launch of Adobe Express for Enterprise, which is powered by Firefly Image Model 3, is a positive. It offers features, namely Brand Controls, Bulk Create, Generate and Firefly Custom Models. The company also launched Photoshop’s web version, which is available via Firefly-powered AI tools, generative expand and generative fill. The editing tool enables file collaboration through sharing links, even without subscriptions, and provides a web version with desktop tools like the contextual taskbar for workflow suggestions.

Intensifying Competition: A Risk

Adobe has lost 23.2% year to date against the Zacks Computer & Technology sector’s growth of 16.8%. In the same time frame, the company has underperformed Amazon ( AMZN Quick Quote AMZN - Free Report ) , Alphabet ( GOOGL Quick Quote GOOGL - Free Report ) and Meta Platforms ( META Quick Quote META - Free Report ) , from which it faces stiff competition in the generative AI market. Amazon, which has gained 21.8% year to date, is benefiting significantly from the solid adoption of Amazon Bedrock, which has provided it with a breakthrough in the generative AI space. Amazon Bedrock offers seamless access to high-performing foundation models from AI companies through an API. Growing momentum in the Amazon Titan model is a plus. The addition of Meta’s Llama 2 to Amazon Bedrock as a new model remains noteworthy. Alphabet’s Google is capitalizing on the increasing demand for large language models (LLMs) with its most powerful AI model, Gemini. Solid momentum in Google’s Vertex AI, which enables developers to train, tune, augment and deploy applications using generative AI models, is another positive. Alphabet, which has rallied 26.6% year to date, is also gaining strong momentum across its second generation of image generator model, Imagen 2, which offers an improved image quality to help organizations create brand-specific images with enterprise-grade reliability and governance, ensuring customer satisfaction. Meanwhile, Meta Platforms, which has returned 39.6% year to date, recently introduced generative AI features to assist businesses in creating and editing new ad content, making the process quicker and more efficient. These features include image and text generation capabilities, image variation, and the ability to create alternate iterations based on original creative, helping businesses reach their target audiences more effectively.

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Frequently asked questions

What is artificial intelligence.

Artificial intelligence (AI) is a system that is able to perceive its environment and take actions to maximize the chance of successfully achieving its goals as well as interpret and analyze data in such a way that it learns and adapts as it goes.

What is generative AI?

Generative AI is a form of artificial intelligence that can produce text, images, and varied content based on the data it is trained on.

What is AI in sales and marketing?

The lead-to-cash process covers all activities related to marketing and selling products and services, managing and fulfilling sales orders, providing after-sales services, and finally, invoicing customers, managing accounts receivable, and collecting payment. It also covers the management of customers and channels as foundational elements of the process.

The process varies mainly based on the type of customer (such as B2B versus B2C), the channels through which the products and services are being offered (such as direct sales, digital commerce, and physical stores), and the type of products and services that are sold (such as simple, tangible products, configurable products, engineered products, intangible products, one-time or recurring services, complex solutions, or projects).

What is AI in supply chain?

The design to operate (D2O) process includes the entire lifecycle of products in an end-to-end, connected, and interoperable supply chain process from how a product is designed, planned, manufactured, delivered, to how it operates and is maintained.

The planning stage of the process involves defining supply chain, manufacturing and service-fulfillment strategies; planning demand, inventory, and supply; aligning plans through sales and operations planning; and finally, managing supply chain performance. The planning process culminates in the initiation of operational procurement.

The production stage of the process includes production planning, production operations, quality management, and production performance management – for both tangible and intangible goods.

The delivery-and-fulfillment stage of the process differs for tangible goods versus services. For tangible goods, it covers inbound or outbound deliveries in any context as well as order promising, warehouse and inventory management, dock and yard logistics, transportation management, and logistics performance management. For services, it involves service planning and scheduling, service execution and delivery, and service performance management.

The process concludes with enabling and foundational activities, such as data management, collaboration, identifying and tracking material, and sustainable manufacturing operations.

What is AI in procurement?

The source-to-pay (S2P) process includes all activities associated with managing the comprehensive sourcing and procurement of goods and services. It starts with procurement planning and managing spend, followed by sourcing and supplier selection, negotiating and managing supplier contracts, and preparing and executing operational procurement. The next steps are goods receipt, initiating potential returns and claims, processing supplier invoices and accounts payable, including final payment to the supplier, and managing supplier data.

The source-to-pay process varies mainly based on the type of product or service being purchased. Variations of S2P cover, for example, procurement of indirect and direct products, services, and solutions (such as a combination of products and services), as well as field service materials.

What is AI in human resources?

The recruit-to-retire (R2R) process includes all activities associated with hiring the internal and external workforce and managing their lifecycle in the organization. It involves strategizing and planning human resource requirements, identifying and onboarding new talent, developing talent to enable growth, and retaining talent through appropriate reward-and-recognition strategies, as well as managing all recurring and administrative tasks throughout the workforce lifecycle. The latter includes the management of workforce-related data and lifecycle events such as promotions, relocations, or final offboarding, managing travel and expenses, and periodic payroll and expense payments.

The R2R process will vary depending on whether internal employees or the external workforce is being managed. The entire travel-to-reimburse process is embedded within R2R as well.