Загрузка видео...

Не удалось загрузить видео

На главную

Introducing: Consensus Deep Search 🔬 Deep Search is a research agent that conducts literature reviews across 200M academic papers in two minutes.

ConsensusNLP's profile picture

Consensus

12,833 subscribers

1,385,150 просмотров • 1 год назад •via X (Twitter)

Наука и технологииОбразование
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Introducing your arXiv Research Agent A personal research assistant with access to arXiv + bioRxiv + medRxiv + Semantic Scholar. Upload drafts, conduct literature reviews, get insights across millions of papers MCP support coming soon 🚀
0:21

Introducing your arXiv Research Agent A personal research assistant with access to arXiv + bioRxiv + medRxiv + Semantic Scholar. Upload drafts, conduct literature reviews, get insights across millions of papers MCP support coming soon 🚀

alphaXiv

128,305 просмотров • 1 год назад

10 academic papers. Parsed, analyzed, and synthesized. In under 10 seconds. We built a research agent with @Cerebras Inference and Unstructured that processes entire literature reviews so you become a subject expert faster
0:39

10 academic papers. Parsed, analyzed, and synthesized. In under 10 seconds. We built a research agent with @Cerebras Inference and Unstructured that processes entire literature reviews so you become a subject expert faster

Cerebras

14,588 просмотров • 4 месяцев назад

If you need a more detailed answer from Brave Search, try our Deep Research feature! 🔬 Deep Research runs dozens of queries against our independent search index to produce the most comprehensive response. Expand the "Deep Research" panel at the top to see the steps it took.
0:32

If you need a more detailed answer from Brave Search, try our Deep Research feature! 🔬 Deep Research runs dozens of queries against our independent search index to produce the most comprehensive response. Expand the "Deep Research" panel at the top to see the steps it took.

Brave

42,117 просмотров • 2 месяцев назад

Introducing Deep Research for arXiv Ask questions like 'What are the latest breakthroughs in RL fine-tuning?' and get comprehensive lit reviews with trending papers automatically included Turn hours of literature searches into seconds with AI-powered research context ⚡
0:50

Introducing Deep Research for arXiv Ask questions like 'What are the latest breakthroughs in RL fine-tuning?' and get comprehensive lit reviews with trending papers automatically included Turn hours of literature searches into seconds with AI-powered research context ⚡

alphaXiv

372,737 просмотров • 1 год назад

I shipped something cool findmypapers (dot) ai A semantic search engine for 300k+ AI research papers outcompete SoTA Deep Research apps at finding relevant research papers for you more demos👇
0:53

I shipped something cool findmypapers (dot) ai A semantic search engine for 300k+ AI research papers outcompete SoTA Deep Research apps at finding relevant research papers for you more demos👇

bycloud

27,425 просмотров • 1 год назад

We’re bringing deep research capabilities into AI Mode through Deep Search. Deep Search is our most advanced research tool in Google Search and can help save you hours of time by going deeper on your tougher, more complex questions. How, you ask? Let's break it down.
0:59

We’re bringing deep research capabilities into AI Mode through Deep Search. Deep Search is our most advanced research tool in Google Search and can help save you hours of time by going deeper on your tougher, more complex questions. How, you ask? Let's break it down.

Google AI

61,971 просмотров • 1 год назад

Introducing MCP for arXiv Let your research agents stand on the shoulders of giants Fast multi-turn retrieval, keyword search, and embedding search tools across millions of arXiv papers 🚀
0:39

Introducing MCP for arXiv Let your research agents stand on the shoulders of giants Fast multi-turn retrieval, keyword search, and embedding search tools across millions of arXiv papers 🚀

alphaXiv

276,272 просмотров • 4 месяцев назад

Introducing Qwen 3 + Deep Research! We built a deep research agent with Qwen 3 and it performed better than most open source models that we've tried. the code is completely open source and free! built with 's Langgraph Together AI and uses Perplexity Tavily for search here's the code link:
0:57

Introducing Qwen 3 + Deep Research! We built a deep research agent with Qwen 3 and it performed better than most open source models that we've tried. the code is completely open source and free! built with 's Langgraph Together AI and uses Perplexity Tavily for search here's the code link:

Soham

34,566 просмотров • 1 год назад

Consensus in an AI-powered search engine that answers your questions with reference to published papers. No hallucinations. No fake citations to papers that don't exist. Here is a new Consensus feature that will make your literature review faster and easier. Ask a question and Consensus will give you a list of relevant papers. You can filter papers by: • Year • Study Type (Meta Analysis, Literature Review, Systematic Review, Case Report, etc.) • Study Details (Controlled Study, Human Study, Sample Size) Here I am asking a question about how people self manage lower back pain. I am filtering papers so I only see meta analyses and systematic reviews published in 2020.
0:35

Consensus in an AI-powered search engine that answers your questions with reference to published papers. No hallucinations. No fake citations to papers that don't exist. Here is a new Consensus feature that will make your literature review faster and easier. Ask a question and Consensus will give you a list of relevant papers. You can filter papers by: • Year • Study Type (Meta Analysis, Literature Review, Systematic Review, Case Report, etc.) • Study Details (Controlled Study, Human Study, Sample Size) Here I am asking a question about how people self manage lower back pain. I am filtering papers so I only see meta analyses and systematic reviews published in 2020.

Mushtaq Bilal, PhD

115,765 просмотров • 2 лет назад

You can now connect GitHub repos to deep research in ChatGPT. 🐙 Ask a question and the deep research agent will read and search the repo’s source code and PRs, returning a detailed report with citations. Hit deep research → GitHub to get started.
0:46

You can now connect GitHub repos to deep research in ChatGPT. 🐙 Ask a question and the deep research agent will read and search the repo’s source code and PRs, returning a detailed report with citations. Hit deep research → GitHub to get started.

OpenAI Developers

1,506,031 просмотров • 1 год назад

Today we’re releasing Deep Research Tulu (DR Tulu)—the first fully open, end-to-end recipe for long-form deep research, plus an 8B agent you can use right away. Train agents that plan, search, synthesize, & cite across sources, making expert research more accessible. 🧭📚
1:01

Today we’re releasing Deep Research Tulu (DR Tulu)—the first fully open, end-to-end recipe for long-form deep research, plus an 8B agent you can use right away. Train agents that plan, search, synthesize, & cite across sources, making expert research more accessible. 🧭📚

Ai2

123,882 просмотров • 8 месяцев назад

Introducing Open Deep Research! A fully open-source Deep Research tool that: • writes comprehensive reports • does multi-hop search and reasoning • generates cover images & pod-casts! We’re releasing everything: evaluation dataset, code and blog.🔥 Example output report👇
0:34

Introducing Open Deep Research! A fully open-source Deep Research tool that: • writes comprehensive reports • does multi-hop search and reasoning • generates cover images & pod-casts! We’re releasing everything: evaluation dataset, code and blog.🔥 Example output report👇

Together AI

66,541 просмотров • 1 год назад

Introducing the Consensus Meter 2.0 📊 See how science agrees on any research question - now with metrics showing the research quality, methodology, and influence of supporting papers in each position 🔬
0:53

Introducing the Consensus Meter 2.0 📊 See how science agrees on any research question - now with metrics showing the research quality, methodology, and influence of supporting papers in each position 🔬

Consensus

77,791 просмотров • 1 год назад

🛠️ THIS is the new way to run an effective literature search. Use Connected Papers to build a network of papers that are similar, relevant and that provide the most impactful data for your literature review.
0:59

🛠️ THIS is the new way to run an effective literature search. Use Connected Papers to build a network of papers that are similar, relevant and that provide the most impactful data for your literature review.

Amina Yonis, PhD

30,045 просмотров • 2 лет назад

Systematic literature reviews take 12-18 months to complete. Looks like AI is going to fully automate systematic reviews sooner than later. SciSpace ( SciSpace) just launched an autonomous AI agent that conducts a systematic literature review with a single prompt. Go to scispace[.]com and run the following prompt: "Conduct a systematic literature review on [your topic]" SciSpace agent will generate research questions based on the PICO framework. You can review these questions and edit them according to your specific requirements. The agent will also draft screening criteria that you can edit according to your needs. Then the agent asks you to select the databases you want to use and the date range for paper. After this step, everything is fully automated. The agent will search for papers in the relevant databases, it will combine and rerank the papers. Then it will start the title and abstract screening and include the papers that meet the include criteria. In the next step, it will download the full text of included papers and screen them followed by data extraction. Based on the extracted data, it generates a complete systematic literature review and also a PRISMA diagram. It will also give you a table of papers included along with the rational for including them. The only thing that is keeping AI agents to fully automate systematic literature reviews fields is the papers behind paywalls. Check out the agent at scispace[.]com and see if you find its review useful.
0:47

Systematic literature reviews take 12-18 months to complete. Looks like AI is going to fully automate systematic reviews sooner than later. SciSpace ( SciSpace) just launched an autonomous AI agent that conducts a systematic literature review with a single prompt. Go to scispace[.]com and run the following prompt: "Conduct a systematic literature review on [your topic]" SciSpace agent will generate research questions based on the PICO framework. You can review these questions and edit them according to your specific requirements. The agent will also draft screening criteria that you can edit according to your needs. Then the agent asks you to select the databases you want to use and the date range for paper. After this step, everything is fully automated. The agent will search for papers in the relevant databases, it will combine and rerank the papers. Then it will start the title and abstract screening and include the papers that meet the include criteria. In the next step, it will download the full text of included papers and screen them followed by data extraction. Based on the extracted data, it generates a complete systematic literature review and also a PRISMA diagram. It will also give you a table of papers included along with the rational for including them. The only thing that is keeping AI agents to fully automate systematic literature reviews fields is the papers behind paywalls. Check out the agent at scispace[.]com and see if you find its review useful.

Mushtaq Bilal, PhD

41,791 просмотров • 3 месяцев назад

I built a multi-agent Deep Research team using Qwen 3 that can generate consulting style reports as Google docs. It has 3 AI Agents working together as a team: 1. Research Question Agent 2. Web Search Agent 3. Google Docs Compilation Agent 100% Opensource Code.
0:54

I built a multi-agent Deep Research team using Qwen 3 that can generate consulting style reports as Google docs. It has 3 AI Agents working together as a team: 1. Research Question Agent 2. Web Search Agent 3. Google Docs Compilation Agent 100% Opensource Code.

Shubham Saboo

25,071 просмотров • 1 год назад

Today, we're excited to announce Deep Search. It’s like Deep Research, but for your production AI data. Search for anything, and Raindrop automatically trains little models to accurately classify any topic or issue, across millions of events.
1:43

Today, we're excited to announce Deep Search. It’s like Deep Research, but for your production AI data. Search for anything, and Raindrop automatically trains little models to accurately classify any topic or issue, across millions of events.

ben hylak

161,416 просмотров • 1 год назад

Bytedance, opensourced DeerFlow (Deep Exploration and Efficient Research Flow) LLM + Langchain + tools (web search, crawler, code exec). Its a community-driven Deep Research framework.
1:27

Bytedance, opensourced DeerFlow (Deep Exploration and Efficient Research Flow) LLM + Langchain + tools (web search, crawler, code exec). Its a community-driven Deep Research framework.

Rohan Paul

62,422 просмотров • 1 год назад

AI search for papers is here Search anything you want with papers Here are a few examples of what you can do: Semantically search by sentences & phrases. Example: evaluating factuality in LLM outputs Search by concepts. Example: latent diffusion Search by authors names. Example: Ilya Sutskever Hugging Face just crossed 50,000 papers (all the majors ones of the past two years should be covered), with dozens added every day & just enabled semantic search. It's becoming the best place to do collaborative research.
0:20

AI search for papers is here Search anything you want with papers Here are a few examples of what you can do: Semantically search by sentences & phrases. Example: evaluating factuality in LLM outputs Search by concepts. Example: latent diffusion Search by authors names. Example: Ilya Sutskever Hugging Face just crossed 50,000 papers (all the majors ones of the past two years should be covered), with dozens added every day & just enabled semantic search. It's becoming the best place to do collaborative research.

AK

35,896 просмотров • 1 год назад