Exploring the Frontiers of Generative AI Tools Part II— Tools for Empowering Research, Note Taking, and Beyond
This post is contributed by Shuo Jiang, Elijah Kim, and Ayako Yachie, from SBX BioSciences, Inc.
As technology continues to advance at an unprecedented pace, we find ourselves on the brink of a new era where artificial intelligence (AI) seamlessly integrates into our daily lives, enhancing our experiences and productivity. From analyzing hundreds of pages to generating unique text, the world of generative AI is growing exponentially through the constant improvement of large language models (LLMs). In this article, we will explore this ever-expanding world of generative AI and LLMs through the use of some fascinating tools.
To provide you with a visual representation of these innovative tools, we have created a quad chart that showcases their rankings in terms of their purpose. These tools take full advantage of generative AI models and combine them with other processes, such as GPT-4 and natural language processing, to produce various unique programs tailored to all types of people.
Throughout our exploration, we will discuss each tool in detail, highlighting their unique features, functionalities, and the ways they empower users in their respective domains. By the end of this article, you will have gained a comprehensive understanding of these tools and their roles in shaping the future of AI-driven user interfaces across platforms.
To better understand these tools, we have split the four sections into two parts: Text Generation Tools and Summarization Tools in the first part, Searching Tools and Note Taking Tools in the second part. The section titles reveal the types of tools that will be explored in each section. In our previous article “Exploring the Frontiers of Generative AI Tools Part I — Tools for Empowering Reading, Writing, and Beyond”, we have already gained valuable insights on reading and writing tools in the field of generative AI. In this phase of our AI exploration, I will present to you the searching and note-taking tools. Each tool is unique in its own way and is worth going over.
Searching Tools
Consensus is a web-based search engine that leverages AI to extract and distill findings directly from scientific research, simplifying the process of finding rigorous answers. By utilizing vector search and a custom language model for question answering, Consensus effectively addresses user queries and provides concise and informative summaries of research findings using GPT-4.
Key features include evidence-based answers from peer-reviewed studies, instant analysis, and synthesized results. Consensus caters to students, workers, researchers, and healthcare professionals, aiding them in finding targeted papers or articles with relevant and high-quality information.
Pros of Consensus include providing unbiased information from leading scholarly articles and enabling users to quickly grasp key findings. However, Consensus has a paywall for free users, limiting access to summaries and other features, and some limitations exist, such as text issues, abstract label removal, and imprecise findings.
In conclusion, Consensus serves as a valuable tool for users seeking evidence-based answers from scientific research. Despite some limitations, it simplifies the search process and offers reliable scientific results and instant analysis, supporting individuals across various domains in their pursuit of knowledge.
EvidenceHunt is a clinical web-based search engine specialized in extracting population and intervention details from user questions to match them with relevant evidence. This platform supports various search methods, including simple or advanced searches, categorical searches based on medical specialties, and custom queries on PubMed.
After asking a question, a summarized answers will appear with blue numbers associated with each sentence. Clicking on one of the string of numbers provides the source of that sentence, allowing users to quickly find more information. Here is an example usage of EvidenceHunt:
Users can sort results by study type, sample size, recency, and impact factor, empowering users to find precise and targeted information. The platform’s easy-to-understand search methods, along with PICO analysis, streamline the process of locating clinical evidence.
Although EvidenceHunt has limitations, such as the importance of selecting specific keywords for relevant results, it remains a reliable tool for accessing and analyzing clinical evidence from various sources. Overall, EvidenceHunt enhances evidence-based decision-making and fosters a more informed approach to medical research and practice.
Huma.AI is a powerful tool catering to healthcare providers, designed to manage and enhance patient care. With features like virtual care management, patient monitoring, and data analysis, the platform aims to simplify real-world data analysis and provide valuable insights. Using biomedical natural language processing, Huma.AI performs topic summarization, sentiment analysis, and uncovers unknown trends across customers, geography, and time.
Medical affairs professionals, regulatory affairs professionals, and biomedical experts are among the target users, benefiting from improved data analysis, meaningful engagement with key opinion leaders, safety surveillance, and interdepartmental collaboration.
Although specific tool extensions or modifications are not detailed, Huma.AI’s pros include advanced data analysis, explainable AI, and the ability to analyze both structured and unstructured data. However, as the tool requires payment and access is restricted, interested users should request a demo or reach out to the company for further information.
System is an innovative tool that utilizes large language models (LLMs) and statistical relationships from peer-reviewed studies to offer users key statistical findings from scientific articles. Designed for students, workers, and researchers in the biomedical field, the tool ensures extraction accuracy, relevance, and validation, organizing the extracted relationships into a large-scale graph for users to explore connections and synthesize information.
Key features of System include statistical relationship extraction, search relevance and clustering, context and significance recognition, and a graph organization of relationships. It provides reliable and accurate syntheses based on peer-reviewed scientific articles and employs high-quality models with continuous performance monitoring.
While System excels in health and life sciences, focusing on peer-reviewed scientific articles, it lacks an API or browser extension. Users are advised to verify the tool’s features and capabilities by referring to the official documentation or reaching out to the System/System Pro team for the most accurate and up-to-date information.
CancerGPT is an advanced tool focused on cancer research, leveraging large pre-trained language models (LLMs) to extract predictive information from scientific literature. By transforming the prediction task into a natural language inference task, CancerGPT predicts drug pair synergies in rare tissues, overcoming limited structured data and discrepant features in various cancer types.
CancerGPT utilizes fine-tuned GPT-2 and GPT-3 models and incorporates domain-specific knowledge from text corpora to achieve high accuracy in drug pair prediction. The predictive model is based on LLMs and a few-shot learning approach, adapting to each rare tissue with minimal training data. The tool integrates tabular input into natural language text and prompts the LLMs for predictions. Using the ChatGPT API and architecture, researchers can input relevant information to generate answers from CancerGPT.
Pros of CancerGPT include its ability to accelerate cancer research, achieve high accuracy in rare tissues, and use an innovative LLM-based approach for drug pair synergy prediction. However, the few-shot learning approach and limited availability of data for rare tissues beyond cancer are areas that may require further analysis.
Searching Tools Comparison
Consensus:
- Utilizes GPT-4, vector searches, and a custom fine-tuned language model to address user queries.
- Offers powerful capabilities for research.
- Free to use.
EvidenceHunt:
- Provides PICO analysis to extract information from articles beyond just the titles.
- Completely free to use.
Huma.AI:
- Uses explainable AI, self-service, and data silo connections to serve users effectively.
System:
- Focuses on statistical findings to provide accurate results, prioritizing preciseness over clarity.
CancerGPT:
- Specializes in cancer-related information and uses cancer-specific training data.
- Ensures in-depth information on cancer-related research.
Note Taking Tools
Lateral is a research tool that allows users to explore related topics and concepts. With advanced features and visual mapping of ideas, Lateral helps users analyze relationships between different topics, expand knowledge, and find new information and connections. Ideal for students, workers, researchers, and professionals, Lateral accelerates research and enhances organization.
Users are able to upload multiple documents and see related concepts between them. This is best utilized by students and researchers, who may need to analyze many documents at once.
Using natural language processing (NLP) and machine learning (ML) techniques, users can organize and search across multiple documents, extract insights, and identify connections, making it valuable for medical researchers, educators, and healthcare professionals.
Lateral also offers extensions and APIs, such as the Lateral Intelligence Platform (LIP) API for building fast ML text recommendations and the Article Extractor API for pulling data from article URLs.
Some highlights of Lateral include personalized recommendations, quick citation generation, and optical character recognition (OCR) for enhanced searchability. However, there are limitations, such as suboptimal processing for research papers with multiple paragraphs per page and constraints on the free version.
ClioVis is a web-based platform offering intuitive visualization capabilities to explore complex datasets, facilitating data analysis and synthesis. With features like citation support, collaboration tools, and presentation capabilities, ClioVis provides a comprehensive solution for working with intricate data.
Key features include importing large datasets in various formats, establishing connections, and supporting data integration from multiple sources. ClioVis caters to students, educators, researchers, professionals, and individuals across different.
Pros of ClioVis include detailed exporting features, efficient image uploading, and seamless communication through the chat feature. However, certain collaborative features are limited behind a paywall.
ClioVis offers a user-friendly platform for visualizing complex datasets, making it valuable for researchers, educators, and professionals looking to analyze and present intricate information effectively. Despite some limitations, ClioVis’ capabilities contribute to a productive and engaging user experience.
Meet Glasp, the social web highlighter tool that enables users to highlight, add notes, and share their learning experiences. With features like YouTube and PDF highlighting, Kindle integration, and AI-powered summaries, Glasp offers a comprehensive platform for organizing and managing annotations effectively.
Key features include tagging specific sections of web pages, sharing highlights through URLs, and embedding highlights in blog posts. Glasp caters to students, workers, bloggers, researchers, and medical professionals, facilitating collaboration and knowledge-sharing.
Pros of Glasp include showing connections between users’ interests, free and quick exporting to multiple platforms, and seamless integration with notetaking and workspace applications. However, the interface may sometimes interfere with webpages, and accurate transcription is required for YouTube video highlights.
In conclusion, Glasp provides a valuable tool for users to highlight, annotate, and share their learning experiences. While some minor issues exist, Glasp’s seamless integration and AI-powered summary feature enhance the learning process and make it a convenient choice for users seeking an efficient and engaging annotation tool.
Comparison
Lateral:
- Ideal for sorting through multiple files, especially PDFs.
- Unique feature: Visualizing connections between PDFs through related concepts.
- Although not up to date, offers API
- Allows users to retrieve, filter, and modify documents and document tags.
- Provides options to create, delete, and retrieve user information.
- Allows retrieval of preferences and recommendations.
- Code samples are available in various languages like Go, Java, Node.js, and Python on Lateral website.
ClioVis:
- Excellent for visualizing historical events and creating timelines with event descriptions and connections.
- Doubles as a great teaching tool.
Glasp:
- Best for highlighting and storing found information from webpages.
- Allows users to view their own highlights and community highlights for valuable information
One More Look at the Tools
Before this article comes to a close, it would be best to take a look at some technicalities with the tools. Take a look at this quad chart below:
The chart above illustrates how each of the above-mentioned tools compares to one another in terms of how much AI/user interface each tool uses and if the tool is single or multiple platforms. This is a great comparison as it shows how different kinds of generative AI tools can be compared to one another even though the purpose of each individual tool differs. As seen in the chart, many of the tools mentioned are single platform but vary greatly in the amount they depend on AI. However, some tools, such as Huma.AI, Lateral, and Paperpal are all multiple platform tools. Looking at generative AI tools this way can help individuals better understand that even though some tools have similar underlying mechanisms, the tools can vary greatly depending on how those mechanisms are being put to use.
Conclusion
In conclusion, the world of generative AI and large language models has brought about a transformative shift in our daily lives, enhancing productivity and reshaping industries. Through the exploration of these fifteen cutting-edge tools, we have witnessed the incredible potential of generative AI in text generation, summarization, searching, and note-taking. From assisting writers with contextually appropriate suggestions to enabling researchers to extract evidence-based insights, these AI-driven tools offer invaluable support and efficiency.
As we embrace these technological advancements, it is essential to remain mindful of responsible AI usage, acknowledging potential biases, and ensuring ethical practices. By harnessing the power of generative AI and LLMs, we can build a future where human-machine collaboration leads to groundbreaking discoveries and advancements. The journey towards a more innovative and productive future relies on staying updated with the latest advancements and maximizing the potential of AI-driven user interfaces. Together, we can usher in an era where technology empowers us to achieve unprecedented creativity, efficiency, and knowledge-sharing.
