Загрузка видео...

Не удалось загрузить видео

На главную

AI finally has an unlimited context window. Today, we’re launching Polygres: turn your entire database into an extended context window for AI. Sign up Polygres (it's 100% free for a limited time). Links Below. See it in action ↓

daleverett's profile picture

dale

2,323 subscribers

19,151 просмотров • 8 дней назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Artists, for the time being it is a good idea not to sign any contract regarding usage of your voice in an AI context
1:14

Artists, for the time being it is a good idea not to sign any contract regarding usage of your voice in an AI context

Holly Herndon

65,889 просмотров • 3 лет назад

Web IQ is Microsoft's state-of-the-art grounding service for AI agents and assistants. It returns ranked, citation-ready context across web, news, images, video, and more. Designed for direct injection into an LLM's context window.
1:11

Web IQ is Microsoft's state-of-the-art grounding service for AI agents and assistants. It returns ranked, citation-ready context across web, news, images, video, and more. Designed for direct injection into an LLM's context window.

Microsoft Developer

16,096 просмотров • 1 месяц назад

Today, Frigade is launching Frigade AI - an AI agent that helps users learn your product by actually using it. Unlike basic chatbots, Frigade AI takes action and helps in the context of your actual product UI.
1:30

Today, Frigade is launching Frigade AI - an AI agent that helps users learn your product by actually using it. Unlike basic chatbots, Frigade AI takes action and helps in the context of your actual product UI.

Y Combinator

19,227 просмотров • 1 год назад

Google announces Gemini 1.5 blog: Gemini 1.5 Pro, mid-sized model, will soon come standard with a 128K-token context window, but starting today, developers + customers can sign up for the limited Private Preview to try out 1.5 Pro with a groundbreaking and experimental 1 million token context window
0:20

Google announces Gemini 1.5 blog: Gemini 1.5 Pro, mid-sized model, will soon come standard with a 128K-token context window, but starting today, developers + customers can sign up for the limited Private Preview to try out 1.5 Pro with a groundbreaking and experimental 1 million token context window

AK

13,850 просмотров • 2 лет назад

1/ Introducing MemSync — Portable AI Memory for Personalization MemSync (MemSync) turns your digital footprint into an AI-friendly database, allowing you to port your context over to other AI apps for instant personalization. Built by the OpenGradient (∇, ∇) team
1:55

1/ Introducing MemSync — Portable AI Memory for Personalization MemSync (MemSync) turns your digital footprint into an AI-friendly database, allowing you to port your context over to other AI apps for instant personalization. Built by the OpenGradient (∇, ∇) team

Matthew (∇, ∇)

87,499 просмотров • 1 год назад

Today, we’re launching the Parallel Search API, the most accurate web search for AI agents, built using our proprietary web index and retrieval infrastructure. Traditional search ranks URLs for humans to click. AI search needs something different: the right tokens in their context window. Parallel’s Search API is built from the ground up for AI agents, resulting in higher accuracy, lower costs, and lower latency for end-to-end agentic workflows.
1:20

Today, we’re launching the Parallel Search API, the most accurate web search for AI agents, built using our proprietary web index and retrieval infrastructure. Traditional search ranks URLs for humans to click. AI search needs something different: the right tokens in their context window. Parallel’s Search API is built from the ground up for AI agents, resulting in higher accuracy, lower costs, and lower latency for end-to-end agentic workflows.

Parallel Web Systems

669,725 просмотров • 8 месяцев назад

CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇
0:33

CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇

Md Riyazuddin

31,199 просмотров • 1 месяц назад

Finally, Google has dropped AI for work. It runs your emails, meetings, docs, and even understands your data in context. Here’s everything you need to know:
1:35

Finally, Google has dropped AI for work. It runs your emails, meetings, docs, and even understands your data in context. Here’s everything you need to know:

Pearl AI

20,739 просмотров • 1 год назад

Time for some more Photoshop painting with an AI "amplifier"! I'm using my "hack" that involves placing the Krea ai transformation over my Photoshop window, using a tool called WindowTop. I'll post a small guide for that below. #art #ai
0:31

Time for some more Photoshop painting with an AI "amplifier"! I'm using my "hack" that involves placing the Krea ai transformation over my Photoshop window, using a tool called WindowTop. I'll post a small guide for that below. #art #ai

Martin Nebelong

115,034 просмотров • 2 лет назад

New short course: LLMs as Operating Systems: Agent Memory, created with Letta, and taught by its founders Charles Packer and Sarah Wooders. An LLM's input context window has limited space. Using a longer input context also costs more and results in slower processing. So, managing what's stored in this context window is important. In the innovative paper MemGPT: Towards LLMs as Operating Systems, its authors (which include the instructors) proposed using an LLM agent to manage this context window. Their system uses a large persistent memory that stores everything that could be included in the input context, and an agent decides what is actually included. Take the example of building a chatbot that needs to remember what's been said earlier in a conversation (perhaps over many days of interaction with a user). As the conversation's length grows, the memory management agent will move information from the input context to a persistent searchable database; summarize information to keep relevant facts in the input context; and restore relevant conversation elements from further back in time. This allows a chatbot to keep what's currently most relevant in its input context memory to generate the next response. When I read the original MemGPT paper, I thought it was an innovative technique for handling memory for LLMs. The open-source Letta framework, which we'll use in this course, makes MemGPT easy to implement. It adds memory to your LLM agents and gives them transparent long-term memory. In detail, you’ll learn: - How to build an agent that can edit its own limited input context memory, using tools and multi-step reasoning - What is a memory hierarchy (an idea from computer operating systems, which use a cache to speed up memory access), and how these ideas apply to managing the LLM input context (where the input context window is a "cache" storing the most relevant information; and an agent decides what to move in and out of this to/from a larger persistent storage system) - How to implement multi-agent collaboration by letting different agents share blocks of memory This course will give you a sophisticated understanding of memory management for LLMs, which is important for chatbots having long conversations, and for complex agentic workflows. Please sign up here!
2:57

New short course: LLMs as Operating Systems: Agent Memory, created with Letta, and taught by its founders Charles Packer and Sarah Wooders. An LLM's input context window has limited space. Using a longer input context also costs more and results in slower processing. So, managing what's stored in this context window is important. In the innovative paper MemGPT: Towards LLMs as Operating Systems, its authors (which include the instructors) proposed using an LLM agent to manage this context window. Their system uses a large persistent memory that stores everything that could be included in the input context, and an agent decides what is actually included. Take the example of building a chatbot that needs to remember what's been said earlier in a conversation (perhaps over many days of interaction with a user). As the conversation's length grows, the memory management agent will move information from the input context to a persistent searchable database; summarize information to keep relevant facts in the input context; and restore relevant conversation elements from further back in time. This allows a chatbot to keep what's currently most relevant in its input context memory to generate the next response. When I read the original MemGPT paper, I thought it was an innovative technique for handling memory for LLMs. The open-source Letta framework, which we'll use in this course, makes MemGPT easy to implement. It adds memory to your LLM agents and gives them transparent long-term memory. In detail, you’ll learn: - How to build an agent that can edit its own limited input context memory, using tools and multi-step reasoning - What is a memory hierarchy (an idea from computer operating systems, which use a cache to speed up memory access), and how these ideas apply to managing the LLM input context (where the input context window is a "cache" storing the most relevant information; and an agent decides what to move in and out of this to/from a larger persistent storage system) - How to implement multi-agent collaboration by letting different agents share blocks of memory This course will give you a sophisticated understanding of memory management for LLMs, which is important for chatbots having long conversations, and for complex agentic workflows. Please sign up here!

Andrew Ng

200,788 просмотров • 1 год назад

Think of Model Context Protocol as a USB port for your AI. 🔌 You can plug in documentation, tools, and context directly into Copilot CLI. Scott Hanselman 🌮 shows how to set it all up. 👇
4:07

Think of Model Context Protocol as a USB port for your AI. 🔌 You can plug in documentation, tools, and context directly into Copilot CLI. Scott Hanselman 🌮 shows how to set it all up. 👇

GitHub

44,363 просмотров • 5 месяцев назад

the founder of a $20b ai company breaks down how a swarm of ai agents can replace an entire company. in one minute. for free. doesn't matter if you've never touched an agent or you've been living in claude for a year. you'll follow it. i pulled the key ideas into a practical guide for building with kimi. it's below ↓
1:22

the founder of a $20b ai company breaks down how a swarm of ai agents can replace an entire company. in one minute. for free. doesn't matter if you've never touched an agent or you've been living in claude for a year. you'll follow it. i pulled the key ideas into a practical guide for building with kimi. it's below ↓

Avid

15,597 просмотров • 1 месяц назад

Introducing Toggle for OpenClaw🦞 For the first time ever your Agent can see everything you do on the web. This is real-time context on your work day. Toggle AI analyses all browser actions, clicks, work, meetings and documents -> into AI context of what Projects / Tasks / Tools you are working on. Check it out👇
0:26

Introducing Toggle for OpenClaw🦞 For the first time ever your Agent can see everything you do on the web. This is real-time context on your work day. Toggle AI analyses all browser actions, clicks, work, meetings and documents -> into AI context of what Projects / Tasks / Tools you are working on. Check it out👇

PeLpA

52,323 просмотров • 5 месяцев назад

Introducing PAI 1.0: The First Version of Personal Super Intelligence PAI is the world's first context-aware, widget based AI agent that floats over your screen to read your context in real time and proactively suggest next steps, ensuring safety by executing actions only with your explicit approval. The floating AI interface designed to eliminate the prompt inequality and barrier. Structurally eliminating the "navigate to a chat window, write a prompt, explain your context" workflow that existing AI services have treated as a given for years.
8:24

Introducing PAI 1.0: The First Version of Personal Super Intelligence PAI is the world's first context-aware, widget based AI agent that floats over your screen to read your context in real time and proactively suggest next steps, ensuring safety by executing actions only with your explicit approval. The floating AI interface designed to eliminate the prompt inequality and barrier. Structurally eliminating the "navigate to a chat window, write a prompt, explain your context" workflow that existing AI services have treated as a given for years.

Eon (Yulheon) Seung

130,825 просмотров • 1 месяц назад

🌐No more waitlist!🌐 Today, we’re opening up the Atlas beta for anyone to use. It comes with an upgraded AI - you can now chat with the context-aware solidity assistant. Have it edit contracts, debug errors, or look for security exploits. All without leaving your editor.
0:34

🌐No more waitlist!🌐 Today, we’re opening up the Atlas beta for anyone to use. It comes with an upgraded AI - you can now chat with the context-aware solidity assistant. Have it edit contracts, debug errors, or look for security exploits. All without leaving your editor.

Atlas

34,196 просмотров • 3 лет назад

It’s like having an AI time machine. ⏰📈 ICYMI – we launched Loom AI workflows, so you can turn any Loom video into a share-ready doc or Atlassian Jira issue. ...and now all current and new Loom customers can give AI workflows for a spin, for free! Speed up your workflows today
0:42

It’s like having an AI time machine. ⏰📈 ICYMI – we launched Loom AI workflows, so you can turn any Loom video into a share-ready doc or Atlassian Jira issue. ...and now all current and new Loom customers can give AI workflows for a spin, for free! Speed up your workflows today

Loom

44,601 просмотров • 2 лет назад

In December, we launched Gemini 1.0 Pro. Today, we're introducing Gemini 1.5 Pro! 🚀 This next-gen model uses a Mixture-of-Experts (MoE) approach for more efficient training & higher-quality responses. Gemini 1.5 Pro, our mid-sized model, will soon come standard with a 128K-token context window, but starting today, developers + customers can sign up for the limited Private Preview to try out 1.5 Pro with a groundbreaking and experimental 1 million token context window! The 1M tokens feature unlocks huge possibilities for devs - upload hundreds of pages of text, entire code repos, and long videos and let Gemini reason across them. It's still experimental and early and we’d love your feedback - learn more here.
0:20

In December, we launched Gemini 1.0 Pro. Today, we're introducing Gemini 1.5 Pro! 🚀 This next-gen model uses a Mixture-of-Experts (MoE) approach for more efficient training & higher-quality responses. Gemini 1.5 Pro, our mid-sized model, will soon come standard with a 128K-token context window, but starting today, developers + customers can sign up for the limited Private Preview to try out 1.5 Pro with a groundbreaking and experimental 1 million token context window! The 1M tokens feature unlocks huge possibilities for devs - upload hundreds of pages of text, entire code repos, and long videos and let Gemini reason across them. It's still experimental and early and we’d love your feedback - learn more here.

Sundar Pichai

852,640 просмотров • 2 лет назад

You asked for it, so here it is: a deep-dive on my new /handoff skill. It's an alternative to /compact that gives you WAY more flexibility with your context window. - Think of an idea, handoff to another agent to implement - Grill, handoff to prototype, handoff BACK Enjoy:
12:23

You asked for it, so here it is: a deep-dive on my new /handoff skill. It's an alternative to /compact that gives you WAY more flexibility with your context window. - Think of an idea, handoff to another agent to implement - Grill, handoff to prototype, handoff BACK Enjoy:

Matt Pocock

102,809 просмотров • 2 месяцев назад

Most "AI document tools" are just ChatGPT with a file upload button. Felo LiveDoc gives you an intelligent canvas. It's an actual workspace where your entire project lives, research, drafts, data, slides, all connected on one canvas with AI agents that understand your full context. No more switching between 6 tools or re-explaining context every time. Here's what that actually looks like 👇 1/8
1:00

Most "AI document tools" are just ChatGPT with a file upload button. Felo LiveDoc gives you an intelligent canvas. It's an actual workspace where your entire project lives, research, drafts, data, slides, all connected on one canvas with AI agents that understand your full context. No more switching between 6 tools or re-explaining context every time. Here's what that actually looks like 👇 1/8

AshutoshShrivastava

17,388 просмотров • 7 месяцев назад