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Microsoft launched "Agent Mode" for Outlook, moving Copilot from a writing assistant to an active inbox and calendar manager. It is currently rolling out to users in the "Frontier" early access program. Unlike previous versions that simply drafted replies, Agent Mode can autonomously triage your inbox, prioritize critical threads... show more

Wes Roth

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51,297 次观看 • 3 个月前 •via X (Twitter)

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Gemini Agent can help tackle all sorts of tasks. Even renting a car. Tell Gemini Agent your budget and it’ll get to work comparing prices, gathering info from your inbox, and booking the car. Now available for Google AI Ultra users in the US on desktop and mobile.

Gemini Agent can help tackle all sorts of tasks. Even renting a car. Tell Gemini Agent your budget and it’ll get to work comparing prices, gathering info from your inbox, and booking the car. Now available for Google AI Ultra users in the US on desktop and mobile.

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Introducing Agent Mode: Agentic AI is now measured in the Arena. Agent Mode can do deep research, create reports, generate images, build websites, debug code, and more. It completes more complex tasks by using tools like web search, bash in a sandbox environment, image generation, file writing, and asking follow-up questions. Frontier models are waiting for you in Agent Mode to take on real-world tasks. GPT-5.5, Claude Opus 4.7, Gemini 3.1 Pro, and top open models. Test them yourself.

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23,369 次观看 • 1 年前

is about to ship Tokenized Agents — and I found the first tokens deployed with it. Pump’s new Tokenized Agents feature lets a coin have an attached AI agent that can earn on-chain revenue. Users pay for the agent’s services, and that revenue can be split between creator fees and automatic token buybacks and burns by the agent, based on the percentage set by the creator. Pump.fun is also expected to release a full agent SDK (for agent actions/integrations). How I found it (on-chain): Open → Ctrl+F “pump_agent_payments” → program ID: pUmPFn9WvfaN2WTVGnCEtJTd2ATTpvpsKRz6jVzu6u4 Program activity (created tokens): First ever deployed tokenized AI test agent (“T-coin”, Feb 24): CA: 88Wfk48EvwLkfpSXH84W9xrdfPr5RFGVP3teT76AMnp9 First non-test tokenized AI agent (“Agent Pump”): CA: Boi2KtPApoowwfvqYq1rtjhea4pF45v89vguonf4pump IDL (for interacting with the program):

is about to ship Tokenized Agents — and I found the first tokens deployed with it. Pump’s new Tokenized Agents feature lets a coin have an attached AI agent that can earn on-chain revenue. Users pay for the agent’s services, and that revenue can be split between creator fees and automatic token buybacks and burns by the agent, based on the percentage set by the creator. Pump.fun is also expected to release a full agent SDK (for agent actions/integrations). How I found it (on-chain): Open → Ctrl+F “pump_agent_payments” → program ID: pUmPFn9WvfaN2WTVGnCEtJTd2ATTpvpsKRz6jVzu6u4 Program activity (created tokens): First ever deployed tokenized AI test agent (“T-coin”, Feb 24): CA: 88Wfk48EvwLkfpSXH84W9xrdfPr5RFGVP3teT76AMnp9 First non-test tokenized AI agent (“Agent Pump”): CA: Boi2KtPApoowwfvqYq1rtjhea4pF45v89vguonf4pump IDL (for interacting with the program):

TrenchDiver

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15,622 次观看 • 1 年前

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Google

65,489 次观看 • 8 个月前

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New short course: Long-Term Agentic Memory with LangGraph. Learn to build an agent with long-term memory in this course developed in collaboration with taught by its Co-Founder and CEO, Harrison Chase! Personal assistance and productivity tasks have become important use cases for agents. An important feature of an AI assistant, such as a coding or calendar assistant, is its ability to keep improving over time from its experience. Agent memory is the key capability that enables this. To add memory to an agent, you must first figure out what to store and what to retrieve when it is time to use the information. Additionally, you’ll have to decide when to update the stored information. For example, you might update in each iteration loop of the agent or perform updates in the background, with a helper agent. In this course, you will learn a mental framework to build agents with long-term memory. You'll create a useful email assistant that can respond, ignore, and notify using writing, scheduling, and memory-management tools. You’ll develop your agent's memory by adding facts to its memory store, provide examples to learn the user's preferences, and optimize system prompts to evolve instructions based on previous responses. In detail, you’ll: - Learn how the three types of memory--semantic, episodic, and procedural–and the two update mechanisms–via hot path and in the background–apply to your agents. - Build an email agent with writing, scheduling, and availability tools, along with a router that triages incoming email and handles it accordingly by ignoring, responding, or notifying the user. - Add tools to your email agent that allow it to operate on semantic memory by learning facts about the user, storing them in a long-term memory store, and searching over them in future interactions. - Incorporate episodic memory, in the form of few-shot examples, in the triage step of your agents to help them learn and update user preferences. - Add procedural memory as system prompts, optimized with feedback to improve the instructions the agent follows. Learn how to approach memory in agents, and start building agents with long-term memory with LangGraph! Please sign up here:

Andrew Ng

131,850 次观看 • 1 年前

🇺🇸 xAI launched Grok Build, a coding agent that runs directly from your terminal, now in early beta for SuperGrok and X Premium Plus subscribers. It lets you plan and approve changes before anything runs, works with tools you already use like MCP servers and plugins, and can spin up multiple subagents working in parallel on larger tasks. Some users say it's already competing with Claude Code and GitHub Copilot Workspace. Source: xAI

🇺🇸 xAI launched Grok Build, a coding agent that runs directly from your terminal, now in early beta for SuperGrok and X Premium Plus subscribers. It lets you plan and approve changes before anything runs, works with tools you already use like MCP servers and plugins, and can spin up multiple subagents working in parallel on larger tasks. Some users say it's already competing with Claude Code and GitHub Copilot Workspace. Source: xAI

Mario Nawfal

99,324 次观看 • 2 个月前

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New upgrades to the Google Gemini are you helping you get more done: ✨Gemini Spark is your 24/7 personal AI agent that can take action on your behalf, under your direction. It seamlessly integrates with Gmail, Google Docs, and Slides to automate your workflows and, best of all, it can keep working even when your laptop is closed. ☀ ️Daily Brief is our newest out-of-the-box agent that gives you a personalized digest based on your goals, and suggests next steps. Daily Brief is rolling out starting today to all Google AI subscribers (18+) in the Gemini app, starting in the US. Gemini Spark is starting to roll out next week.

Google AI

39,739 次观看 • 2 个月前

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At Postman, we have adopted an AI-native mindset to product development. What does this mean in practice? Just like you can generate text with AI, Postman's Agent Mode can generate a UI as well. Case in point: we have added the ability to review, generate, and change diffs for important changes right inside agent mode's chat interaction. If the user trusts agent mode, they can continue in auto-mode, but for critical changes, they can have the agent mode inform the user, review what is changing, and then give the go ahead to approve. See this in action below in the video! While there is a lot of focus on AI generated code today, I believe a large chunk of pre-built UI work will just go away and micro-interactions and workflow steps will be created on the fly through a combination of AI + APIs. How to operate in this new world? Build your API first. Hook it up to AI. If your users really want the UI every time, invest in the GUI.

Abhinav Asthana

104,263 次观看 • 1 年前

Our Researcher agent in Microsoft 365 Copilot never ceases to amaze me. It can reason over all your work data, like chats, meetings, files and emails, plus web data, to generate a comprehensive research report that helps you prep for a meeting, analyze trends, or build a strategy. I use it all the time. Here’s an example:

Our Researcher agent in Microsoft 365 Copilot never ceases to amaze me. It can reason over all your work data, like chats, meetings, files and emails, plus web data, to generate a comprehensive research report that helps you prep for a meeting, analyze trends, or build a strategy. I use it all the time. Here’s an example:

Satya Nadella

311,315 次观看 • 11 个月前

Introducing Director Mode in CapCut Video Studio. Lights. Idea. Action! Director Mode is an advanced workflow for AI drama series, films, and long-form videos, built on SOTA models like Seedance 2.0 and GPT-Image-2. You can: → Co-create with the agent to develop a professional script from just an idea → Once the script is confirmed, visualize characters, scenes, and props aligned to the story → Generate connected shot sequences based on the setup → Organize all elements and direct the agent to assembles the final edit → Re-prompt to refine frames at any stage, in your direction If you can think it, you can direct it. Now let the canvas roll. RT+comment in 9h to get 200 credits in your DM Note: Director Mode is available on CapCut Web globally, with US rollout coming soon

Introducing Director Mode in CapCut Video Studio. Lights. Idea. Action! Director Mode is an advanced workflow for AI drama series, films, and long-form videos, built on SOTA models like Seedance 2.0 and GPT-Image-2. You can: → Co-create with the agent to develop a professional script from just an idea → Once the script is confirmed, visualize characters, scenes, and props aligned to the story → Generate connected shot sequences based on the setup → Organize all elements and direct the agent to assembles the final edit → Re-prompt to refine frames at any stage, in your direction If you can think it, you can direct it. Now let the canvas roll. RT+comment in 9h to get 200 credits in your DM Note: Director Mode is available on CapCut Web globally, with US rollout coming soon

CapCut

1,452,534 次观看 • 2 个月前

🚨 memU bot is live. A better alternative to OpenClaw🦞 (formerly Moltbot / Clawdbot) 👉Get instant access to the memU bot: 🕒 A 24/7 proactive assistant memU bot runs continuously on your machine and works as a proactive assistant. It takes action based on your behavior and context — instead of waiting for explicit commands. 🧠 Highly personal, built for you memU bot learns from your long-term usage and memory, and gradually adapts to your work style and preferences. It becomes your assistant — not a generic AI. ⚡ Very easy to use — download and run No complex setup. No configuration. Even non-technical users can simply download and run memU bot. 🔒 Local-first and secure, with no server dependency memU bot runs locally on your device. Your data never needs to be uploaded to public networks or third-party servers. 💸 Lower LLM token cost (more efficient than OpenClaw🦞) While supporting always-on and proactive behavior, memU bot is designed to reduce LLM calls and token usage — so it runs cheaper than OpenClaw, without sacrificing performance. 🧠 "Always-on" is the real key to a proactive agent. And memory is what gives it true proactivity. With memory, an agent is no longer generic. It becomes personal — shaped by who you are. This is how a user-intention-driven proactive agent is born: before you even issue a command, it can already anticipate what kind of help you’ll need, based on your past, your habits, your context. 🔮 A 24/7 process that can observe 👀, remember 📝, and act ⚡ — not just wait for prompts. 🤖 memU bot is our attempt at a user-intention-driven proactive agent — one that lives beyond the chat box.

🚨 memU bot is live. A better alternative to OpenClaw🦞 (formerly Moltbot / Clawdbot) 👉Get instant access to the memU bot: 🕒 A 24/7 proactive assistant memU bot runs continuously on your machine and works as a proactive assistant. It takes action based on your behavior and context — instead of waiting for explicit commands. 🧠 Highly personal, built for you memU bot learns from your long-term usage and memory, and gradually adapts to your work style and preferences. It becomes your assistant — not a generic AI. ⚡ Very easy to use — download and run No complex setup. No configuration. Even non-technical users can simply download and run memU bot. 🔒 Local-first and secure, with no server dependency memU bot runs locally on your device. Your data never needs to be uploaded to public networks or third-party servers. 💸 Lower LLM token cost (more efficient than OpenClaw🦞) While supporting always-on and proactive behavior, memU bot is designed to reduce LLM calls and token usage — so it runs cheaper than OpenClaw, without sacrificing performance. 🧠 "Always-on" is the real key to a proactive agent. And memory is what gives it true proactivity. With memory, an agent is no longer generic. It becomes personal — shaped by who you are. This is how a user-intention-driven proactive agent is born: before you even issue a command, it can already anticipate what kind of help you’ll need, based on your past, your habits, your context. 🔮 A 24/7 process that can observe 👀, remember 📝, and act ⚡ — not just wait for prompts. 🤖 memU bot is our attempt at a user-intention-driven proactive agent — one that lives beyond the chat box.

memU

818,160 次观看 • 6 个月前