正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Two big steps towards our vision for @NotebookLM as the ultimate research platform: • Integrating Deep Research, with a set of only-at-Notebook features that let you explore the retrieved sources • Launching a series of Featured Notebooks curated by Google Research These developments are designed to enhance the full... life cycle of research and scholarship: using the power of AI to assemble the knowledge base you need to advance your understanding, and then making your work accessible and intelligible to a wider audience using all the explanatory tools that Notebook offers. If you've used DeepResearch in the Gemini app, you already know that it's a pioneering advance in assembling complex, grounded information on any topic imaginable—collecting an entire trove of material for you and writing a nuanced research report that summarizes the findings. But because NotebookLM is designed to manage and explore potentially hundreds of sources, the Deep Research report is only the beginning of your journey. In our integration, Deep Research gives you an overview all of the sources it found during its research phase, with annotated commentary explaining how each source related to your original query. You can then choose to import some or all of the sources to the notebook, along with the report itself, which you can then explore or transform using the full suite of tools that Notebook offers: grounded chat with citations, Mind Maps, Audio/Video overviews, and much more. And it's that suite of tools that make the Google Research Featured Notebooks so compelling as well. Each notebook contains a curated collection of articles on a specific topic, published by the Google Research team. Think of them as a kind of knowledge base of Google's best thinking on a series of compelling research questions: How do scientists link genetics to health? How will quantum computing be useful? If you're a specialist in these fields, you can read the original papers or ask nuanced questions in chat and advance your understanding of the latest developments. But these notebooks can also make the complex but important topics understandable to non-specialists or students. Each notebook comes with pre-generated audio and video overviews, flashcards, and other Studio artifacts designed to make the scientific and technological concepts accessible and interesting. And you can always explore the material with our new "Learning Guide" chat mode that effectively gives you a personal tutor to enhance your understanding. There's much more to come on this front, but you can see in these two announcements how we see Notebook as both a workbench for conducting research and a publishing platform for sharing the results of that research once you're ready to make it public. Deep Research is rolling out this week to all users. The first two Google Research notebooks are live now, both of them deep dives into our most recent discoveries involving genetics and health. (Links in the following tweets.) We'll be publishing new notebooks in the series every other week or so for the next few months.show more

Steven Johnson

1,046,192 subscribers

104,833 次观看 • 9 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

One of our favorite ways to use the Audio Overviews feature is to pair it with Deep Research. Now, with just a click, you can turn your Deep Research reports into a lively conversation for learning on-the-go. Your AI hosts will summarize the material, draw connections between topics, and engage in a dynamic back-and-forth to help you make sense of complex information in a new way.

One of our favorite ways to use the Audio Overviews feature is to pair it with Deep Research. Now, with just a click, you can turn your Deep Research reports into a lively conversation for learning on-the-go. Your AI hosts will summarize the material, draw connections between topics, and engage in a dynamic back-and-forth to help you make sense of complex information in a new way.

Google Gemini

14,793 次观看 • 1 年前

PhD Students – How to identify related papers for your research paper? 1. Go to 2. Paste your DOI or title of your research paper 3. ResearchCollab will display the network of papers 4. Explore the network in following ways → Filter the network of papers based on research field → Filter the network based on thematic clusters → Filter the network based on keywords → and much more As you find related papers, keep saving them. This use case has multiple advantages. ➟ You won’t miss a related paper to cite in your paper ➟ You can identify related papers for your lit review ➟ You can explore new research directions and trends ➟ You can visualize the entire collection of papers As a researcher, work smarter not just harder. For this, try ResearchCollab:

PhD Students – How to identify related papers for your research paper? 1. Go to 2. Paste your DOI or title of your research paper 3. ResearchCollab will display the network of papers 4. Explore the network in following ways → Filter the network of papers based on research field → Filter the network based on thematic clusters → Filter the network based on keywords → and much more As you find related papers, keep saving them. This use case has multiple advantages. ➟ You won’t miss a related paper to cite in your paper ➟ You can identify related papers for your lit review ➟ You can explore new research directions and trends ➟ You can visualize the entire collection of papers As a researcher, work smarter not just harder. For this, try ResearchCollab:

Faheem Ullah

46,809 次观看 • 2 个月前

PhD Students - How to write a research proposal in minutes? 1. Go to 2. Click on method design & enter your research topic 3. Novix will generate a proposal for you. This proposal contains the following. - The research problem - Experimental protocols to conduct this research - Detailed statistical approaches to apply - A summary of your entire research methodology - A built-in peer review of your proposed methods Treat this proposal only as a draft. Work on it and refine it as per your research You can continue using Novix for refinement.

PhD Students - How to write a research proposal in minutes? 1. Go to 2. Click on method design & enter your research topic 3. Novix will generate a proposal for you. This proposal contains the following. - The research problem - Experimental protocols to conduct this research - Detailed statistical approaches to apply - A summary of your entire research methodology - A built-in peer review of your proposed methods Treat this proposal only as a draft. Work on it and refine it as per your research You can continue using Novix for refinement.

Faheem Ullah

57,042 次观看 • 3 个月前

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

Santiago

20,837 次观看 • 8 天前

Morgan Housel will never use AI to write. To him, it defeats the whole purpose of writing. "The process of writing is what gets the author thinking. When they write a book, they didn't have all that knowledge in their head. They started out with one brave sentence, and then that taught them something. If you're using any kind of LLM to do any of the broad structure for you, you're not actually thinking. You stripped out everything that was good about writing." He'll use it for research, as a "Google on steroids." But even then he argues that the research process is different: "When you're doing the reps of research, it's gonna hit you in a different way."

Morgan Housel will never use AI to write. To him, it defeats the whole purpose of writing. "The process of writing is what gets the author thinking. When they write a book, they didn't have all that knowledge in their head. They started out with one brave sentence, and then that taught them something. If you're using any kind of LLM to do any of the broad structure for you, you're not actually thinking. You stripped out everything that was good about writing." He'll use it for research, as a "Google on steroids." But even then he argues that the research process is different: "When you're doing the reps of research, it's gonna hit you in a different way."

David Perell Clips

13,721 次观看 • 2 个月前

Claude Code cannot read 300 files at once. So someone built a system that lets it control NotebookLM from the terminal instead. The results are wild. Here is the full workflow nobody is talking about: The Setup → Claude Code connects to NotebookLM via a command line interface → Claude searches YouTube, finds relevant videos, uploads them as sources automatically → NotebookLM processes up to 300 sources simultaneously and returns cited, grounded answers → Everything syncs back into your Obsidian vault with passage-level citations you can click to verify Why This Changes Research Forever → No more 20 browser tabs you never close → No more copy-pasting outputs into random notes → No more hallucinated answers with no sources to back them up → 60% of citations verified as strong matches in accuracy audits - answers are grounded in real data What Claude Can Do From the Terminal → Search YouTube for relevant videos on any topic and rank by relevance → Create a new NotebookLM notebook and add 20 sources in parallel automatically → Ask questions and export cited answers directly into Obsidian with wikilinks → Set custom personas per notebook - concise, no filler, no preamble → Generate audio overviews and save them as MP3 files into your vault → Build mind maps, flashcard decks, and research dashboards from your sources → Search arXiv for academic papers and feed them directly into NotebookLM → Upload competitor blog posts, podcast episodes, PDFs, and your own vault notes The Obsidian Output → Every answer arrives with clickable citations that link to the exact passage in the source video or article → Graph view shows connections between all 20 sources and the topics they share → Q&A log tracks every question asked and the grounded response received → Source dashboard shows citation frequency, topics extracted, and which questions each source answered Use Cases Worth Building Today → Academic research with arXiv papers, full citation traceability → Competitor analysis from their YouTube channels and blog posts → Company knowledge base for onboarding, new employees ask NotebookLM instead of interrupting teammates → Podcast research, feed 4-hour Lex Fridman episodes and ask what's new in AI this week → Personal second brain, 300 daily notes uploaded and queryable in one notebook Before this system existed you needed 20 tabs, hours of manual reading, and no guarantee the answers were real. Now you type one prompt in the terminal and Claude does all of it for you. The research stack of 2026 is not a browser. It is a terminal connected to everything

Claude Code cannot read 300 files at once. So someone built a system that lets it control NotebookLM from the terminal instead. The results are wild. Here is the full workflow nobody is talking about: The Setup → Claude Code connects to NotebookLM via a command line interface → Claude searches YouTube, finds relevant videos, uploads them as sources automatically → NotebookLM processes up to 300 sources simultaneously and returns cited, grounded answers → Everything syncs back into your Obsidian vault with passage-level citations you can click to verify Why This Changes Research Forever → No more 20 browser tabs you never close → No more copy-pasting outputs into random notes → No more hallucinated answers with no sources to back them up → 60% of citations verified as strong matches in accuracy audits - answers are grounded in real data What Claude Can Do From the Terminal → Search YouTube for relevant videos on any topic and rank by relevance → Create a new NotebookLM notebook and add 20 sources in parallel automatically → Ask questions and export cited answers directly into Obsidian with wikilinks → Set custom personas per notebook - concise, no filler, no preamble → Generate audio overviews and save them as MP3 files into your vault → Build mind maps, flashcard decks, and research dashboards from your sources → Search arXiv for academic papers and feed them directly into NotebookLM → Upload competitor blog posts, podcast episodes, PDFs, and your own vault notes The Obsidian Output → Every answer arrives with clickable citations that link to the exact passage in the source video or article → Graph view shows connections between all 20 sources and the topics they share → Q&A log tracks every question asked and the grounded response received → Source dashboard shows citation frequency, topics extracted, and which questions each source answered Use Cases Worth Building Today → Academic research with arXiv papers, full citation traceability → Competitor analysis from their YouTube channels and blog posts → Company knowledge base for onboarding, new employees ask NotebookLM instead of interrupting teammates → Podcast research, feed 4-hour Lex Fridman episodes and ask what's new in AI this week → Personal second brain, 300 daily notes uploaded and queryable in one notebook Before this system existed you needed 20 tabs, hours of manual reading, and no guarantee the answers were real. Now you type one prompt in the terminal and Claude does all of it for you. The research stack of 2026 is not a browser. It is a terminal connected to everything

Dami-Defi

252,693 次观看 • 2 个月前

PhD Students – How to identify a research gap in seconds? Use this FREE tool to identify research gap in seconds. 1. Go to 2. Click on 𝑇𝑜𝑝𝑖𝑐 𝐸𝑥𝑝𝑙𝑜𝑟𝑒𝑟 ---> 𝐶𝑟𝑒𝑎𝑡𝑖𝑣𝑒 𝑇𝑜𝑜𝑙 3. Enter your topic e.g., deep learning for healthcare 4. Now click on 𝑔𝑒𝑛𝑒𝑟𝑎𝑡𝑒 𝑖𝑑𝑒𝑎𝑠 5. ResearchCollab will give you the following 7 gaps ➝ Research that combines multiple existing research ➝ Research that adapts a new approach/technology ➝ Research that modifies existing variables in research ➝ Research that incorporates new variables ➝ Research that eliminates variables from research ➝ Research that re-arrange existing variables Pick the gap you think has the most potential. Then click on 𝑡𝑜𝑝𝑖𝑐 𝑎𝑛𝑎𝑙𝑦𝑠𝑖𝑠 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐂𝐨𝐥𝐥𝐚𝐛 will dive deeper into the selected topic It gives you different angles of the chosen research gap. It is very helpful and at the same time very easy to use Try 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐂𝐨𝐥𝐥𝐚𝐛 today:

PhD Students – How to identify a research gap in seconds? Use this FREE tool to identify research gap in seconds. 1. Go to 2. Click on 𝑇𝑜𝑝𝑖𝑐 𝐸𝑥𝑝𝑙𝑜𝑟𝑒𝑟 ---> 𝐶𝑟𝑒𝑎𝑡𝑖𝑣𝑒 𝑇𝑜𝑜𝑙 3. Enter your topic e.g., deep learning for healthcare 4. Now click on 𝑔𝑒𝑛𝑒𝑟𝑎𝑡𝑒 𝑖𝑑𝑒𝑎𝑠 5. ResearchCollab will give you the following 7 gaps ➝ Research that combines multiple existing research ➝ Research that adapts a new approach/technology ➝ Research that modifies existing variables in research ➝ Research that incorporates new variables ➝ Research that eliminates variables from research ➝ Research that re-arrange existing variables Pick the gap you think has the most potential. Then click on 𝑡𝑜𝑝𝑖𝑐 𝑎𝑛𝑎𝑙𝑦𝑠𝑖𝑠 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐂𝐨𝐥𝐥𝐚𝐛 will dive deeper into the selected topic It gives you different angles of the chosen research gap. It is very helpful and at the same time very easy to use Try 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐂𝐨𝐥𝐥𝐚𝐛 today:

Faheem Ullah

106,224 次观看 • 4 个月前

I built a Claude Code skill that allows it to generate a deep research report over any collection of complex docs (PDFs, Word, Pptx)….and generate word-level citations and bounding boxes directly back to the source! 📝 Check out “/research-docs”. 1. It parses out text and bounding boxes from every doc with liteparse, in seconds. 2. It then generates a full HTML report of the outputs that let you see word-level citations in each page. Raw Claude obviously has deep research capabilities, but it lacks an audit trail back to the source. This skill gives you a researched report that can be audited by others. Check it out: LiteParse:

I built a Claude Code skill that allows it to generate a deep research report over any collection of complex docs (PDFs, Word, Pptx)….and generate word-level citations and bounding boxes directly back to the source! 📝 Check out “/research-docs”. 1. It parses out text and bounding boxes from every doc with liteparse, in seconds. 2. It then generates a full HTML report of the outputs that let you see word-level citations in each page. Raw Claude obviously has deep research capabilities, but it lacks an audit trail back to the source. This skill gives you a researched report that can be audited by others. Check it out: LiteParse:

Jerry Liu

77,259 次观看 • 4 个月前

PhD Students – How to identify trends in research? First, let’s understand why trends are important. Identifying trends in research can help you ➝ To see if a research area is active or saturated ➝ To find research gaps ➝ To understand how a research field has evolved ➝ To identify emerging R&D opportunities 𝐇𝐨𝐰 𝐭𝐨 𝐢𝐝𝐞𝐧𝐭𝐢𝐟𝐲 𝐭𝐫𝐞𝐧𝐝𝐬 𝐢𝐧 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡? Very simple. Use the following 3 steps. 1. Go to 2. Enter your question or research area 3. @PatsnapEurekaIP provide you with trend analysis. The trend analysis contains the following ✓ 𝐑𝐞𝐜𝐞𝐧𝐜𝐲: The number of papers in the past 3 years ✓ 𝐈𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞: The number of citations in the past 3 years ✓ 𝐓𝐫𝐞𝐧𝐝: Trend of papers in the past 10 years Eureka shows trends analysis for the following ↳ Research papers ↳ Patents ↳ News articles Find research trends in seconds with Eureka. — A free AI powered search engine for research — It helps researchers to track research trends — It uses insights from 210M+ research papers Try Eureka for FREE

PhD Students – How to identify trends in research? First, let’s understand why trends are important. Identifying trends in research can help you ➝ To see if a research area is active or saturated ➝ To find research gaps ➝ To understand how a research field has evolved ➝ To identify emerging R&D opportunities 𝐇𝐨𝐰 𝐭𝐨 𝐢𝐝𝐞𝐧𝐭𝐢𝐟𝐲 𝐭𝐫𝐞𝐧𝐝𝐬 𝐢𝐧 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡? Very simple. Use the following 3 steps. 1. Go to 2. Enter your question or research area 3. @PatsnapEurekaIP provide you with trend analysis. The trend analysis contains the following ✓ 𝐑𝐞𝐜𝐞𝐧𝐜𝐲: The number of papers in the past 3 years ✓ 𝐈𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞: The number of citations in the past 3 years ✓ 𝐓𝐫𝐞𝐧𝐝: Trend of papers in the past 10 years Eureka shows trends analysis for the following ↳ Research papers ↳ Patents ↳ News articles Find research trends in seconds with Eureka. — A free AI powered search engine for research — It helps researchers to track research trends — It uses insights from 210M+ research papers Try Eureka for FREE

Faheem Ullah

73,369 次观看 • 6 个月前

Last year, we integrated into the Google Gemini by allowing you to upload your notebooks as sources. Now, we’re taking our relationship to the next level 🏠 ♥️ Starting today, you can now: — Access all of your personal, unshared notebooks directly inside the Gemini App — Use your chats with Gemini as sources in new or existing unshared notebooks We're rolling out notebooks in Gemini today, starting with Google AI Ultra, Pro, and Plus subscribers on the web. In the coming weeks, we'll expand access to mobile, more countries across Europe, and to free users.

Last year, we integrated into the Google Gemini by allowing you to upload your notebooks as sources. Now, we’re taking our relationship to the next level 🏠 ♥️ Starting today, you can now: — Access all of your personal, unshared notebooks directly inside the Gemini App — Use your chats with Gemini as sources in new or existing unshared notebooks We're rolling out notebooks in Gemini today, starting with Google AI Ultra, Pro, and Plus subscribers on the web. In the coming weeks, we'll expand access to mobile, more countries across Europe, and to free users.

Gemini Notebook

1,091,686 次观看 • 4 个月前

🔥 Our latest LangChain Academy course – Deep Research with LangGraph – is now live! 🔥 Deep research agents are taking off – from major AI labs to companies building their own. Research is inherently open-ended. You can't always predict whether a question needs broad exploration or deep analysis. Agents excel here because they adapt on the fly, using each finding to decide where to dig next. Building these systems ourselves and with customers, we've learned that structure matters. The best research agents scope problems with users first. Then, they coordinate multiple specialists instead of overwhelming one generalist. LangGraph is built for these types of long-running, multi-agent workflows. Its persistence layer tracks progress across agents. LangSmith gives you the observability and evaluation tools you need to track and improve performance. In this course, you'll build and evaluate: - A user scoping agent to define research parameters - A multi-agent research team with supervisor - And add tool integration via MCP Enroll for free ➡️

🔥 Our latest LangChain Academy course – Deep Research with LangGraph – is now live! 🔥 Deep research agents are taking off – from major AI labs to companies building their own. Research is inherently open-ended. You can't always predict whether a question needs broad exploration or deep analysis. Agents excel here because they adapt on the fly, using each finding to decide where to dig next. Building these systems ourselves and with customers, we've learned that structure matters. The best research agents scope problems with users first. Then, they coordinate multiple specialists instead of overwhelming one generalist. LangGraph is built for these types of long-running, multi-agent workflows. Its persistence layer tracks progress across agents. LangSmith gives you the observability and evaluation tools you need to track and improve performance. In this course, you'll build and evaluate: - A user scoping agent to define research parameters - A multi-agent research team with supervisor - And add tool integration via MCP Enroll for free ➡️

LangChain

61,205 次观看 • 1 年前

🔥 RFK Jr. says his goal is to give medical freedom and choice back to the people. “We’re fighting not to put ourselves in a position to tell you what to do.” “That was the old way of doing things at HHS.” “Right now, our philosophy is we’re going to provide the best information to the American public, but people need to do their own research and people need to be the CEOs of their own health and their children’s health.” “What we know after COVID is that governments are corruptible, that people in authority lie, that there’s all kinds of incentives that lead them to tell noble lies for your own good, which turn out not to be for your good.” “We have to do our own research, protect our family, and protect our own health.” “The same way that you research an automobile before you buy it or a baby carriage or a car seat … you look on consumer reports, you do your own research, you make up your own mind about what’s good for you and your family.” Secretary Kennedy HHS Isabel Brown

🔥 RFK Jr. says his goal is to give medical freedom and choice back to the people. “We’re fighting not to put ourselves in a position to tell you what to do.” “That was the old way of doing things at HHS.” “Right now, our philosophy is we’re going to provide the best information to the American public, but people need to do their own research and people need to be the CEOs of their own health and their children’s health.” “What we know after COVID is that governments are corruptible, that people in authority lie, that there’s all kinds of incentives that lead them to tell noble lies for your own good, which turn out not to be for your good.” “We have to do our own research, protect our family, and protect our own health.” “The same way that you research an automobile before you buy it or a baby carriage or a car seat … you look on consumer reports, you do your own research, you make up your own mind about what’s good for you and your family.” Secretary Kennedy HHS Isabel Brown

Children’s Health Defense

12,859 次观看 • 6 个月前

PhD Students – How to easily understand a complex research topic? Meet Ponder – a tool for understanding complex research. 𝐇𝐨𝐰 𝐏𝐨𝐧𝐝𝐞𝐫 𝐰𝐨𝐫𝐤𝐬? 1. Go to and log in 2. Enter your research topic or research question 3. Ponder will start building a knowledge map 4. This knowledge map breaks down complex ideas into structured cards 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐲𝐨𝐮 𝐝𝐨 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞𝐬𝐞 𝐜𝐚𝐫𝐝𝐬? → You can add your own thoughts, questions, and insights. → Ask follow-up questions and deepen your exploration. → You can color the cards for better understanding → You can drag & organize them freely across the infinite canvas. 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐩𝐚𝐩𝐞𝐫𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐜𝐚𝐫𝐝𝐬? — You can search for relevant papers with built-in discovery. — Ponder will identify all relevant papers — You can then add or upload research papers — You can also attach papers to specific cards. 𝐀𝐟𝐭𝐞𝐫 𝐲𝐨𝐮𝐫 𝐩𝐨𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐢𝐬 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝: ➟ You can change the view to document, browser, or full screen. ➟ You can also download your knowledge map as a PDF ➟ You can ask further questions and refine with Ponder’s Agent. 𝐖𝐡𝐚𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐭𝐡𝐢𝐬 𝐰𝐚𝐲 𝐢𝐬 𝟏𝟎𝐱 𝐛𝐞𝐭𝐭𝐞𝐫? ↳ It brings discovery and analysis of research into one workspace ↳ It makes ideas branch and evolve naturally, just like your brain ↳ It helps you to easily identify research gaps ↳ It connects knowledge from all sources such as papers and web ↳ It enables you to export knowledge as maps, reports, or data. ↳ Designed for PhD students & researchers, who think deeply. Try Ponder here: Anything you'd like to add?

PhD Students – How to easily understand a complex research topic? Meet Ponder – a tool for understanding complex research. 𝐇𝐨𝐰 𝐏𝐨𝐧𝐝𝐞𝐫 𝐰𝐨𝐫𝐤𝐬? 1. Go to and log in 2. Enter your research topic or research question 3. Ponder will start building a knowledge map 4. This knowledge map breaks down complex ideas into structured cards 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐲𝐨𝐮 𝐝𝐨 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞𝐬𝐞 𝐜𝐚𝐫𝐝𝐬? → You can add your own thoughts, questions, and insights. → Ask follow-up questions and deepen your exploration. → You can color the cards for better understanding → You can drag & organize them freely across the infinite canvas. 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐩𝐚𝐩𝐞𝐫𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐜𝐚𝐫𝐝𝐬? — You can search for relevant papers with built-in discovery. — Ponder will identify all relevant papers — You can then add or upload research papers — You can also attach papers to specific cards. 𝐀𝐟𝐭𝐞𝐫 𝐲𝐨𝐮𝐫 𝐩𝐨𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐢𝐬 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝: ➟ You can change the view to document, browser, or full screen. ➟ You can also download your knowledge map as a PDF ➟ You can ask further questions and refine with Ponder’s Agent. 𝐖𝐡𝐚𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐭𝐡𝐢𝐬 𝐰𝐚𝐲 𝐢𝐬 𝟏𝟎𝐱 𝐛𝐞𝐭𝐭𝐞𝐫? ↳ It brings discovery and analysis of research into one workspace ↳ It makes ideas branch and evolve naturally, just like your brain ↳ It helps you to easily identify research gaps ↳ It connects knowledge from all sources such as papers and web ↳ It enables you to export knowledge as maps, reports, or data. ↳ Designed for PhD students & researchers, who think deeply. Try Ponder here: Anything you'd like to add?

Faheem Ullah

12,175 次观看 • 1 年前

Finally: An agentic research companion You can now start a notebook by just entering your loose ideas and questions into the chat. NotebookLM will then guide you through building out your repository, even finding and adding (with your permission!) relevant sources from the web. As always your feedback is everything to us. Try it out and let us know what you think 💖

Finally: An agentic research companion You can now start a notebook by just entering your loose ideas and questions into the chat. NotebookLM will then guide you through building out your repository, even finding and adding (with your permission!) relevant sources from the web. As always your feedback is everything to us. Try it out and let us know what you think 💖

NotebookLM

28,469 次观看 • 2 个月前

New short course: Collaborative Writing and Coding with OpenAI Canvas! Explore new ways to write and code with OpenAI Canvas, a user-friendly interface that allows you to brainstorm, draft, and refine text and code in collaboration with ChatGPT. In the short course, created with OpenAI, and taught by , a research lead at OpenAI, you’ll learn to use Canvas to enhance your workflows. Canvas lets you go beyond simple chat interactions. It provides a side-by-side workspace where you and ChatGPT can edit and refine text or code collaboratively. This makes brainstorming, drafting, and iterating as you write feel more natural and effective. As the first major update to ChatGPT’s visual interface since its launch in 2022, Canvas gives a new, innovative approach to collaboration with AI. For instance, after writing the first version of your code, Canvas can review it and give suggestions for improvement. It can also help with debugging by adding logging, identifying problems to fix, and writing comments. In addition, you'll also learn what it takes to train the model for an interface like Canvas. In this video-only short course, you’ll: - Learn how to ask for in-line feedback and control the iteration of your work by directly editing selected areas of your text or code from the model’s output. - Learn how to access quick automation tools in a shortcut menu that allows you to modify your writing tone and length, enhance your code, and restore previous versions of your work. - Learn how to use Canvas as a research assistant tool with an example of asking the model to reason through the screenshot of a plot to write a research report, in which you can ask questions within the created report. - Ask the model to write Python code to replicate the graph seen on a screenshot image. - Go behind the scenes of how you can create a video game, such as Space Battleship, from scratch, edit it, and display it in one self-contained HTML file. - Get a real-world application example of creating a SQL database from the image of its architecture. - Understand the model training and design processes that power Canvas! Please sign up here:

New short course: Collaborative Writing and Coding with OpenAI Canvas! Explore new ways to write and code with OpenAI Canvas, a user-friendly interface that allows you to brainstorm, draft, and refine text and code in collaboration with ChatGPT. In the short course, created with OpenAI, and taught by , a research lead at OpenAI, you’ll learn to use Canvas to enhance your workflows. Canvas lets you go beyond simple chat interactions. It provides a side-by-side workspace where you and ChatGPT can edit and refine text or code collaboratively. This makes brainstorming, drafting, and iterating as you write feel more natural and effective. As the first major update to ChatGPT’s visual interface since its launch in 2022, Canvas gives a new, innovative approach to collaboration with AI. For instance, after writing the first version of your code, Canvas can review it and give suggestions for improvement. It can also help with debugging by adding logging, identifying problems to fix, and writing comments. In addition, you'll also learn what it takes to train the model for an interface like Canvas. In this video-only short course, you’ll: - Learn how to ask for in-line feedback and control the iteration of your work by directly editing selected areas of your text or code from the model’s output. - Learn how to access quick automation tools in a shortcut menu that allows you to modify your writing tone and length, enhance your code, and restore previous versions of your work. - Learn how to use Canvas as a research assistant tool with an example of asking the model to reason through the screenshot of a plot to write a research report, in which you can ask questions within the created report. - Ask the model to write Python code to replicate the graph seen on a screenshot image. - Go behind the scenes of how you can create a video game, such as Space Battleship, from scratch, edit it, and display it in one self-contained HTML file. - Get a real-world application example of creating a SQL database from the image of its architecture. - Understand the model training and design processes that power Canvas! Please sign up here:

Andrew Ng

128,180 次观看 • 1 年前

auto-research is starting to gain traction as a very viable paradigm for creating useful research discovery. now, that paradigm is still in its infancy and the infrastructure to hold all that trail of context as the agents blaze through experiments isn't well defined (to say the least). on that topic, I had the chance to chat with my boys francesco and giulio from paradigma about what underlying infra is needed to make this paradigm work. the paradigma's paradigm, which involves copious amount of DAGs, make this auto-research paradigm a paradigmatic case of essential infrastructure. here's the full video in full: - 0:00 - what is missing from auto-research? - 2:02 - giulio and francesco ai journey - 8:10 - research infra is the bottleneck? - 10:18 - paradigma vision of autonomous research - 13:17 - “important discovery per joules” - 17:15 - why is DAG the unit of research for auto-research? - 20:40 - is paradigma trying to replace the research publication? - 24:50 - how does knowledge is shared between experiments in the DAG? - 27:34 - what is even auto-research lol? - 33:53 - the value of the human mind in this auto-research future. - 37:00 - how do you reconcile hallucination in this auto-research paradigm? - 41:33 - the adoption of auto-research across varied fields? - 47:30 - ✨ introduction to the auto-research infrastructure. ✨ - 56:55 - where is the code? - 59:10 - full IDE next? - 1:03:20 - the place of the human in this DAG / code quality? manual node? token spent? - 1:16:02 - who’s the user for auto-research? - 1:18:13 - how to validate bad DAG? - 1:20:18 - ✨ auto-research agent results ✨ - 1:22:53 - ✨ how a big research DAG looks like? ✨ - 1:25:10 - how to get the canonical DAG for the final result? - 1:27:50 - the auto-research DAG being the new pre-print? - 1:30:05 - what’s next for paradigma and the auto-research infra? - 1:35:00 - what are they excited about research wise? enjoyyyyy my guys 🌹

auto-research is starting to gain traction as a very viable paradigm for creating useful research discovery. now, that paradigm is still in its infancy and the infrastructure to hold all that trail of context as the agents blaze through experiments isn't well defined (to say the least). on that topic, I had the chance to chat with my boys francesco and giulio from paradigma about what underlying infra is needed to make this paradigm work. the paradigma's paradigm, which involves copious amount of DAGs, make this auto-research paradigm a paradigmatic case of essential infrastructure. here's the full video in full: - 0:00 - what is missing from auto-research? - 2:02 - giulio and francesco ai journey - 8:10 - research infra is the bottleneck? - 10:18 - paradigma vision of autonomous research - 13:17 - “important discovery per joules” - 17:15 - why is DAG the unit of research for auto-research? - 20:40 - is paradigma trying to replace the research publication? - 24:50 - how does knowledge is shared between experiments in the DAG? - 27:34 - what is even auto-research lol? - 33:53 - the value of the human mind in this auto-research future. - 37:00 - how do you reconcile hallucination in this auto-research paradigm? - 41:33 - the adoption of auto-research across varied fields? - 47:30 - ✨ introduction to the auto-research infrastructure. ✨ - 56:55 - where is the code? - 59:10 - full IDE next? - 1:03:20 - the place of the human in this DAG / code quality? manual node? token spent? - 1:16:02 - who’s the user for auto-research? - 1:18:13 - how to validate bad DAG? - 1:20:18 - ✨ auto-research agent results ✨ - 1:22:53 - ✨ how a big research DAG looks like? ✨ - 1:25:10 - how to get the canonical DAG for the final result? - 1:27:50 - the auto-research DAG being the new pre-print? - 1:30:05 - what’s next for paradigma and the auto-research infra? - 1:35:00 - what are they excited about research wise? enjoyyyyy my guys 🌹

Yacine Mahdid

12,091 次观看 • 2 个月前

If I learned anything over 5 years as a reporter, it’s this: the best research is firsthand. That’s why we’re doing a review of the latest Solana phone for Bitwise There's a lot of skepticism about Seeker. Some doubt it will work, or that the crypto elements will be helpful. They say it'll be a nice paperweight. Why are we doing this? There's two ways to research things in crypto. You can dig into the onchain data and talk to the experts. Or you can just do it. You can trade on hyperliquid. You can loop for yield. You can travel to Argentina and try to use stablecoins to pay for things. We do a lot of the traditional research at Bitwise, but sometimes, you gotta get your hands dirty. That's what I'm doing with this phone.

If I learned anything over 5 years as a reporter, it’s this: the best research is firsthand. That’s why we’re doing a review of the latest Solana phone for Bitwise There's a lot of skepticism about Seeker. Some doubt it will work, or that the crypto elements will be helpful. They say it'll be a nice paperweight. Why are we doing this? There's two ways to research things in crypto. You can dig into the onchain data and talk to the experts. Or you can just do it. You can trade on hyperliquid. You can loop for yield. You can travel to Argentina and try to use stablecoins to pay for things. We do a lot of the traditional research at Bitwise, but sometimes, you gotta get your hands dirty. That's what I'm doing with this phone.

Danny Nelson

61,480 次观看 • 10 个月前

How to read a research paper 10x faster? PhD Students are often under time pressure. Many research papers but little time to read. Meet Bohrium – a tool that can 10x your paper reading. 𝐇𝐨𝐰 𝐜𝐚𝐧 𝐁𝐨𝐡𝐫𝐢𝐮𝐦 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮 𝐫𝐞𝐚𝐝 𝐬𝐦𝐚𝐫𝐭𝐞𝐫? 1. Go to and log in. 2. Click on 𝑁𝑒𝑤 𝐶ℎ𝑎𝑡 and then on 𝐿𝑖𝑡𝑇𝑎𝑙𝑘 3. Upload the paper you want to read 4. Click on 𝑆𝑢𝑚𝑚𝑎𝑟𝑖𝑧𝑒 from the list. 5. Bohirum will summarize the paper for you. 6. This will help you understand the gist of the paper. 7. Now click on 𝐸𝑥𝑡𝑟𝑎𝑐𝑡 𝐹𝑖𝑛𝑑𝑖𝑛𝑔𝑠 8. Bohrium will extract key findings from the paper. 9. Go through each of the key finding. 10. Bohrium links each finding to respective part 11. This way you can see the links to the paper. 12. In the similar manner, you can also ↳ Extract information about research methods ↳ Academic concepts used in the paper 13. Bohrium can also help you in your writing 14. For example, you can use it to create diagrams 15. You can use Bohrium to create ✓ Graphical abstract ✓ Mechanism diagram ✓ Flowchart ✓ Concept cover 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐬𝐩𝐞𝐜𝐢𝐚𝐥 𝐚𝐛𝐨𝐮𝐭 𝐁𝐨𝐡𝐫𝐢𝐮𝐦? → You can upload and chat with multiple papers together → Instead of only summarizing, it helps you in deep understanding → It links key findings to exact sections of the paper → It works like research-focused but free NotebookLLM Try it today:

How to read a research paper 10x faster? PhD Students are often under time pressure. Many research papers but little time to read. Meet Bohrium – a tool that can 10x your paper reading. 𝐇𝐨𝐰 𝐜𝐚𝐧 𝐁𝐨𝐡𝐫𝐢𝐮𝐦 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮 𝐫𝐞𝐚𝐝 𝐬𝐦𝐚𝐫𝐭𝐞𝐫? 1. Go to and log in. 2. Click on 𝑁𝑒𝑤 𝐶ℎ𝑎𝑡 and then on 𝐿𝑖𝑡𝑇𝑎𝑙𝑘 3. Upload the paper you want to read 4. Click on 𝑆𝑢𝑚𝑚𝑎𝑟𝑖𝑧𝑒 from the list. 5. Bohirum will summarize the paper for you. 6. This will help you understand the gist of the paper. 7. Now click on 𝐸𝑥𝑡𝑟𝑎𝑐𝑡 𝐹𝑖𝑛𝑑𝑖𝑛𝑔𝑠 8. Bohrium will extract key findings from the paper. 9. Go through each of the key finding. 10. Bohrium links each finding to respective part 11. This way you can see the links to the paper. 12. In the similar manner, you can also ↳ Extract information about research methods ↳ Academic concepts used in the paper 13. Bohrium can also help you in your writing 14. For example, you can use it to create diagrams 15. You can use Bohrium to create ✓ Graphical abstract ✓ Mechanism diagram ✓ Flowchart ✓ Concept cover 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐬𝐩𝐞𝐜𝐢𝐚𝐥 𝐚𝐛𝐨𝐮𝐭 𝐁𝐨𝐡𝐫𝐢𝐮𝐦? → You can upload and chat with multiple papers together → Instead of only summarizing, it helps you in deep understanding → It links key findings to exact sections of the paper → It works like research-focused but free NotebookLLM Try it today:

Faheem Ullah

27,133 次观看 • 7 个月前