Загрузка видео...

Не удалось загрузить видео

На главную

Introducing Nowledge Mem the Context/Memory Manager connecting dots among all Agents in your daily workflow. It enables retrieval, sinking & distilling over your insights, conclusions & precious findings. It persists and by default computes everything locally. #buildinpublic

wey_gu's profile picture

Wey Gu 古思为

19,114 subscribers

79,819 просмотров • 1 год назад •via X (Twitter)

#buildinpublic
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

New course: Agent Memory: Building Memory-Aware Agents, built in partnership with Oracle and taught by Richmond Alake and Nacho Martínez. Many agents work well within a single session but their memory resets once the session ends. Consider a research agent working on dozens of papers across multiple days: without memory, it has no way to store and retrieve what it learned across sessions. This short course teaches you to build a memory system that enables agents to persist memory and thereby learn across sessions. You'll design a Memory Manager that handles different memory types, implement semantic tool retrieval that scales without bloating the context, and build write-back pipelines that let your agent autonomously update and refine what it knows over time. Skills you'll gain: - Build persistent memory stores for different agent memory types - Implement a Memory Manager that orchestrates how your agent reads, writes, and retrieves memory - Treat tools as procedural memory and retrieve only relevant ones at inference time using semantic search Join and learn to build agents that remember and improve over time!
1:37

New course: Agent Memory: Building Memory-Aware Agents, built in partnership with Oracle and taught by Richmond Alake and Nacho Martínez. Many agents work well within a single session but their memory resets once the session ends. Consider a research agent working on dozens of papers across multiple days: without memory, it has no way to store and retrieve what it learned across sessions. This short course teaches you to build a memory system that enables agents to persist memory and thereby learn across sessions. You'll design a Memory Manager that handles different memory types, implement semantic tool retrieval that scales without bloating the context, and build write-back pipelines that let your agent autonomously update and refine what it knows over time. Skills you'll gain: - Build persistent memory stores for different agent memory types - Implement a Memory Manager that orchestrates how your agent reads, writes, and retrieves memory - Treat tools as procedural memory and retrieve only relevant ones at inference time using semantic search Join and learn to build agents that remember and improve over time!

Andrew Ng

160,148 просмотров • 4 месяцев назад

Introducing Membase – portable and persistent memory for your agents. Keep all your context in one place and simply plug it into any agent. We just opened private beta access. Get Membase and make every AI understand you. *Also available in .
0:52

Introducing Membase – portable and persistent memory for your agents. Keep all your context in one place and simply plug it into any agent. We just opened private beta access. Get Membase and make every AI understand you. *Also available in .

Joshua Park

18,238 просмотров • 6 месяцев назад

Perplexity Introduces Personalized Memory 🔥 TLDR : - Gives AI assistants memory to recall preferences, interests, and past chats. - It removes manual context engineering by auto loading relevant context. - Answers become more accurate and personalized using direct memory retrieval. - Users stay fully in control with on or off switches, incognito protection, and encryption. - Memory works across all models so your context follows you anywhere in Perplexity. - Comet Assistant also gets true memory, making it more consistent, personalized, and powerful.
0:30

Perplexity Introduces Personalized Memory 🔥 TLDR : - Gives AI assistants memory to recall preferences, interests, and past chats. - It removes manual context engineering by auto loading relevant context. - Answers become more accurate and personalized using direct memory retrieval. - Users stay fully in control with on or off switches, incognito protection, and encryption. - Memory works across all models so your context follows you anywhere in Perplexity. - Comet Assistant also gets true memory, making it more consistent, personalized, and powerful.

AshutoshShrivastava

22,006 просмотров • 8 месяцев назад

Introducing Gemini CLI extensions, a new framework that allows you to customize Gemini CLI and connect it to the tools you use most—all from the command line. No more context-switching. Start using your favorite tools directly in your workflow today →
0:33

Introducing Gemini CLI extensions, a new framework that allows you to customize Gemini CLI and connect it to the tools you use most—all from the command line. No more context-switching. Start using your favorite tools directly in your workflow today →

Google Cloud Tech

80,461 просмотров • 10 месяцев назад

🚨Introducing the Tri-State Hockey Podcast — hosted by Jonny Lazarus, Mike Rupp & Arthur Staple Your new home for everything #NYR, #NJDevils, and #Isles all season long! Tuesdays & Fridays On The Daily Faceoff YT Channel! Apple: Spotify:
1:37

🚨Introducing the Tri-State Hockey Podcast — hosted by Jonny Lazarus, Mike Rupp & Arthur Staple Your new home for everything #NYR, #NJDevils, and #Isles all season long! Tuesdays & Fridays On The Daily Faceoff YT Channel! Apple: Spotify:

Daily Faceoff

65,032 просмотров • 9 месяцев назад

Introducing Hamster 🐹 Multiplayer AI for product teams. Hunch in, PR out. Design, engineering, product, & business reason on the same work, and your agents deliver it. Your team makes a hundred decisions a week. Now your AI remembers all of them.
1:27

Introducing Hamster 🐹 Multiplayer AI for product teams. Hunch in, PR out. Design, engineering, product, & business reason on the same work, and your agents deliver it. Your team makes a hundred decisions a week. Now your AI remembers all of them.

Hamster

524,409 просмотров • 1 месяц назад

We analyzed Anthropic’s memory architecture and built something better: a persistent, human-inspectable, and token-efficient memory layer that scales with your projects. Today, it’s OPEN-SOURCE. ByteRover CLI gives agents (like OpenClaw, Claude Code, and Hermes) persistent, structured memory. Built on the exact architecture that became the #1 memory system for OpenClaw (30,000+ downloads in a week), it lets developers curate project knowledge into a file-based hierarchy. This guarantees highly accurate, lightning-fast retrieval, even with lightweight models. 👉Highly Accurate: >92% retrieval accuracy across long-running sessions - the highest proven production accuracy on the market. ⚡Fast: ~1.6s average retrieval time. 💰Economic: Maintains >90% accuracy even with lightweight models, saving 50-70% on token costs. ☁ Portable: Runs locally by default, with cloud-sync to share memory across agents and teammates.
1:19

We analyzed Anthropic’s memory architecture and built something better: a persistent, human-inspectable, and token-efficient memory layer that scales with your projects. Today, it’s OPEN-SOURCE. ByteRover CLI gives agents (like OpenClaw, Claude Code, and Hermes) persistent, structured memory. Built on the exact architecture that became the #1 memory system for OpenClaw (30,000+ downloads in a week), it lets developers curate project knowledge into a file-based hierarchy. This guarantees highly accurate, lightning-fast retrieval, even with lightweight models. 👉Highly Accurate: >92% retrieval accuracy across long-running sessions - the highest proven production accuracy on the market. ⚡Fast: ~1.6s average retrieval time. 💰Economic: Maintains >90% accuracy even with lightweight models, saving 50-70% on token costs. ☁ Portable: Runs locally by default, with cloud-sync to share memory across agents and teammates.

andy nguyen

28,980 просмотров • 4 месяцев назад

Introducing Recollect - Sync all your bookmarks & folders from X, Instagram, Chrome in one place ✦ Save anything with a tap using the extension, iOS iPad apps ✦ Everything is tagged & organised as collections with AI ✦ Visualise & search your taste library Check it out ↓
1:12

Introducing Recollect - Sync all your bookmarks & folders from X, Instagram, Chrome in one place ✦ Save anything with a tap using the extension, iOS iPad apps ✦ Everything is tagged & organised as collections with AI ✦ Visualise & search your taste library Check it out ↓

Timeless

63,579 просмотров • 3 месяцев назад

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.
8:17

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.

The Startup Ideas Podcast (SIP) 🧃

13,598 просмотров • 1 месяц назад

🤖 We are entering the second revolution of Personal AI. AI agents aren’t just answering questions, they’re working for you 24/7 to help you stay ahead. Imagine a virtual team that continuously processes data, monitors systems, and executes tasks automatically even while you sleep. With AMD Agent Computers, your AI agents collaborate like a virtual team, maintaining context, sharing insights, and executing tasks as part of a coordinated agentic workflow, something that wasn’t possible before. Everything runs locally, keeping your data private and secure 🛡️ They think deeply, reasoning through problems, connecting insights, and making decisions that multiply your impact. Powered by Ryzen AI Max and Radeon AI PRO, your models, context, and tools live together, no token limits, fully local and private. 💡 Experience what a 24/7 AI team can do to multiply your impact beyond what you thought possible. 🔥 Join us April 30 in San Francisco at AMD Developer Day:
3:10

🤖 We are entering the second revolution of Personal AI. AI agents aren’t just answering questions, they’re working for you 24/7 to help you stay ahead. Imagine a virtual team that continuously processes data, monitors systems, and executes tasks automatically even while you sleep. With AMD Agent Computers, your AI agents collaborate like a virtual team, maintaining context, sharing insights, and executing tasks as part of a coordinated agentic workflow, something that wasn’t possible before. Everything runs locally, keeping your data private and secure 🛡️ They think deeply, reasoning through problems, connecting insights, and making decisions that multiply your impact. Powered by Ryzen AI Max and Radeon AI PRO, your models, context, and tools live together, no token limits, fully local and private. 💡 Experience what a 24/7 AI team can do to multiply your impact beyond what you thought possible. 🔥 Join us April 30 in San Francisco at AMD Developer Day:

Jack Huynh

24,609 просмотров • 3 месяцев назад

We just launched Twin 2 500,000+ tasks automated in our first month. Now: multi-agent automation. → Master agent that orchestrates all your agents → Workspaces where agents share context and collaborate → Persistent databases for long-term memory → See and edit your agent brain for maximum control → Runner mode: scale at 1/10th the cost → Auto-generated web apps to share your agents Try it out now!
2:57

We just launched Twin 2 500,000+ tasks automated in our first month. Now: multi-agent automation. → Master agent that orchestrates all your agents → Workspaces where agents share context and collaborate → Persistent databases for long-term memory → See and edit your agent brain for maximum control → Runner mode: scale at 1/10th the cost → Auto-generated web apps to share your agents Try it out now!

Hugo Mercier

11,216 просмотров • 5 месяцев назад

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇
2:24

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇

Taranjeet

471,972 просмотров • 1 год назад

HERMES AGENT CROSSED 140,000 GITHUB STARS IN 3 MONTHS AND JUST BECAME THE MOST USED AGENT IN THE WORLD. Most AI agents forget everything between sessions. Hermes writes its own skills from experience. Next time it runs the skill, improves it, and gets faster. Independent benchmarks show agents with 20+ self-created skills complete similar tasks 40% faster than fresh instances. Qwen 3.6 where the 35B version outperforms last year's 120B models at one third the memory footprint. DGX Spark with 128GB unified memory running everything locally at $0 per month after hardware. The setup takes 30 minutes. LM Studio plus Qwen 3.6 27B for the model server. One install script for Hermes. One config connecting them. Set context window to 65,536 tokens or nothing works. After one month of daily use your skills directory has 20 to 50 learned workflows. Your Hermes is genuinely different from anyone else's.
0:25

HERMES AGENT CROSSED 140,000 GITHUB STARS IN 3 MONTHS AND JUST BECAME THE MOST USED AGENT IN THE WORLD. Most AI agents forget everything between sessions. Hermes writes its own skills from experience. Next time it runs the skill, improves it, and gets faster. Independent benchmarks show agents with 20+ self-created skills complete similar tasks 40% faster than fresh instances. Qwen 3.6 where the 35B version outperforms last year's 120B models at one third the memory footprint. DGX Spark with 128GB unified memory running everything locally at $0 per month after hardware. The setup takes 30 minutes. LM Studio plus Qwen 3.6 27B for the model server. One install script for Hermes. One config connecting them. Set context window to 65,536 tokens or nothing works. After one month of daily use your skills directory has 20 to 50 learned workflows. Your Hermes is genuinely different from anyone else's.

Lummox

69,676 просмотров • 2 месяцев назад

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.
1:51

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.

Base44

1,581,325 просмотров • 4 месяцев назад

There is so much evil in this world. Why is there silence over children being slaughtered daily? Why is this being normalised? It is disgraceful & shameless from the Western governments. Imagine the pain carrying the remains of your precious children. #StopIsraeliSavagery
2:13

There is so much evil in this world. Why is there silence over children being slaughtered daily? Why is this being normalised? It is disgraceful & shameless from the Western governments. Imagine the pain carrying the remains of your precious children. #StopIsraeliSavagery

Alpha100

27,071 просмотров • 1 год назад

Introducing W&B Skills for coding agents! Watch us install the skill, point it at a live fine-tuning project with thousands of traces and RL training runs, then query it all from the terminal in seconds. Also works with W&B Weave to pull in your agent traces and spot failures.
3:16

Introducing W&B Skills for coding agents! Watch us install the skill, point it at a live fine-tuning project with thousands of traces and RL training runs, then query it all from the terminal in seconds. Also works with W&B Weave to pull in your agent traces and spot failures.

Weights & Biases

257,099 просмотров • 5 месяцев назад

Memory for OpenClaw is now Native! Our first OpenClaw Memory Skill was a massive success: 30k+ downloads in a week and 500k+ organic impressions overnight for launch post. But we knew memory needed to be native. On March 21, OpenClaw merged PR #50848, allowing us to go beyond the skill layer and integrate directly into the agent’s context assembly flow. We try to make OpenClaw a truly 24/7 employee capable of complex workflows. The technical setup isn’t the hardest part but the real challenge is giving it a "brain" that remembers exact project details, past decisions, and team changes over time. The Native Memory Plugin is now live on NPM & ClawHub. Here is what it brings to your OpenClaw agents: 👉 Native Integration: Automatically manages a Three-Layer Memory architecture (Context Tree, Workspace Memory, Daily Memory). 👉 Git-like Stateful Memory: Organizes memory into a semantic hierarchy of human-readable, diffable Markdown files. You always get updated knowledge and can actually see and fix what your agent learns. 👉 Top Market Accuracy: Achieves an industry-leading 92.2% retrieval accuracy (LoCoMo & LongMemEval benchmarks), maintaining 90% accuracy even with cheap, lightweight models. 👉 Local-first & Portable: Local-by-default, fully portable for multi-agent teams. 👉 Super Easy Setup
1:46

Memory for OpenClaw is now Native! Our first OpenClaw Memory Skill was a massive success: 30k+ downloads in a week and 500k+ organic impressions overnight for launch post. But we knew memory needed to be native. On March 21, OpenClaw merged PR #50848, allowing us to go beyond the skill layer and integrate directly into the agent’s context assembly flow. We try to make OpenClaw a truly 24/7 employee capable of complex workflows. The technical setup isn’t the hardest part but the real challenge is giving it a "brain" that remembers exact project details, past decisions, and team changes over time. The Native Memory Plugin is now live on NPM & ClawHub. Here is what it brings to your OpenClaw agents: 👉 Native Integration: Automatically manages a Three-Layer Memory architecture (Context Tree, Workspace Memory, Daily Memory). 👉 Git-like Stateful Memory: Organizes memory into a semantic hierarchy of human-readable, diffable Markdown files. You always get updated knowledge and can actually see and fix what your agent learns. 👉 Top Market Accuracy: Achieves an industry-leading 92.2% retrieval accuracy (LoCoMo & LongMemEval benchmarks), maintaining 90% accuracy even with cheap, lightweight models. 👉 Local-first & Portable: Local-by-default, fully portable for multi-agent teams. 👉 Super Easy Setup

andy nguyen

169,136 просмотров • 4 месяцев назад

🛑Still doing your due dilligence by doomscrolling? NGMI Introducing The DeFi Channel on AITV: delivering 24/7 intelligence powered by AI Agents - so you don’t have to dig for it🤖 🧠 Agents like $GECKO & $VILADY scan news outlets and social media in real time 💬 They turn your prompts into insights 📡 Actionable, always-on, and influenced by you 🎉Welcome to the next era of AI first content delivery.
0:44

🛑Still doing your due dilligence by doomscrolling? NGMI Introducing The DeFi Channel on AITV: delivering 24/7 intelligence powered by AI Agents - so you don’t have to dig for it🤖 🧠 Agents like $GECKO & $VILADY scan news outlets and social media in real time 💬 They turn your prompts into insights 📡 Actionable, always-on, and influenced by you 🎉Welcome to the next era of AI first content delivery.

【 AITV 】

12,837 просмотров • 1 год назад

Cross-context Personal Knowledge Base with Social Graph🧠 Introducing Cross-context Personal Knowledge Base with Social Graph. Your Memory, Across Every Conversation Most AI forgets you the moment a chat ends. Teamily's Personal Knowledge Base remembers — across every group, every agent, and every context. Powered by your social graph, it connects the dots between your work, relationships, and ideas, so your AI always knows who you are, what you care about, and what happened before. No setup. No tagging. Just intelligence that grows with you. 🙌Try the prompt today: “visualize my knowledge base with social graph” #teamily #AI #Agent #KnowledgeBase #Social #SocialGraph
0:24

Cross-context Personal Knowledge Base with Social Graph🧠 Introducing Cross-context Personal Knowledge Base with Social Graph. Your Memory, Across Every Conversation Most AI forgets you the moment a chat ends. Teamily's Personal Knowledge Base remembers — across every group, every agent, and every context. Powered by your social graph, it connects the dots between your work, relationships, and ideas, so your AI always knows who you are, what you care about, and what happened before. No setup. No tagging. Just intelligence that grows with you. 🙌Try the prompt today: “visualize my knowledge base with social graph” #teamily #AI #Agent #KnowledgeBase #Social #SocialGraph

Teamily AI

13,287 просмотров • 3 месяцев назад

👑'Who' by #Jimin is the WINNER of #ChannelRSongOfTheWeek based on YOUR votes and extends his record breaking 15th week at the top! Hear it play 3x daily all week. Keep it at the top! Vote 2X daily on our website & 6X daily on our radio app here:
0:26

👑'Who' by #Jimin is the WINNER of #ChannelRSongOfTheWeek based on YOUR votes and extends his record breaking 15th week at the top! Hear it play 3x daily all week. Keep it at the top! Vote 2X daily on our website & 6X daily on our radio app here:

Channel R Radio

21,631 просмотров • 1 год назад