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Introducing PAl. Your Personal Super-Intelligence 🌀 > The World's 1st Floating AI Agent. Revolutionary User Experience > Always On Accessible, Maintain Your Existing Workflow > No Prompt Needed. Just One Click > Proactive Multi-Agent Tasks > The Evolution of Input. From Typing to Approving > Personal Memory > Mandatory...

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Eon (Yulheon) Seung

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154,394 просмотров • 1 месяц назад •via X (Twitter)

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📣Introducing Personal Time Challenge from Pieverse! Personal Time Challenge is the new home base for all your daily intentions. With customizable goal setting, an AI-powered calendar, and market movement notifications, users are empowered to build personal accountability and maximize productivity. The best part? Every Personal Time Challenge you successfully complete also earns you Pieverse Points—the keys to our entire ecosystem. Lock in, power your time, and join us in living life on-chain. 🗓️Launching this week Stay tuned for more details coming soon.

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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

Introducing Bloome: a human–AI teammate system built around shared context and multi-agent collaboration. → You bring your task, and AI teammates collaborate with you in real time → Work flows through drafting, challenge, and refinement until it reaches the right answer → Claude, ChatGPT, and Deepseek operate together in a shared context with no information loss Everything stays connected from input to final output. This is how work starts changing.
1:15

Introducing Bloome: a human–AI teammate system built around shared context and multi-agent collaboration. → You bring your task, and AI teammates collaborate with you in real time → Work flows through drafting, challenge, and refinement until it reaches the right answer → Claude, ChatGPT, and Deepseek operate together in a shared context with no information loss Everything stays connected from input to final output. This is how work starts changing.

Bloome

343,473 просмотров • 1 месяц назад

clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.
5:50

clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.

Nozz

20,295 просмотров • 7 месяцев назад