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been building ayni - a glyph-based messaging protocol for AI agents instead of passing natural language between agents, ayni encodes meaning into 16x16 pixel glyphs. a shared visual vocabulary that agents can evolve autonomously through governance the result: faster communication, fewer tokens, and agents developing their own visual language...

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23,751 görüntüleme • 7 ay önce •via X (Twitter)

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OKAY, AI AGENTS ARE COOL BUT WTF IS LAVA PART 2 -------------- Lava is a protocol which coordinates traffic from AI agents, apps and wallets on every blockchain. It does this by aggregating data providers who handle RPC requests for AI agents and anyone using blockchains apps. AI agents are projected to manage 80% of all onchain transactions by end of 2025. That's a LOT of RPC requests... -------------- How to stake and restake LAVA LAVA can be staked and restaked to contribute to the network: - secure the Lava blockchain - direct RPC traffic to top Providers on Lava, meaning faster, more reliable service for users/AI agents This is how you stake and restake LAVA on Keplr, Leap and Mellifera:
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New course: Building Coding Agents with Tool Execution, taught by Tereza Tizkova and Fra from E2B. Most AI agents are limited to predefined function calls. This short course teaches you to build agents that write and execute code to accomplish tasks, accessing entire programming language ecosystems instead of being restricted to a fixed set of tools. You'll learn to run agent-generated code safely in sandboxed cloud environments that protect your systems from harmful operations. Skills you'll gain: - Build agents that write and execute code, manage files, and handle errors autonomously through feedback loops - Run agent code safely in E2B cloud sandboxes and understand tradeoffs between local, containerized, and cloud execution - Create a data analyst agent that explores visualizes data with Pandas - Create a full-stack agent that builds complete Next.js web applications Join and build agents that code their way through complex tasks:

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LARP: Language-Agent Role Play for Open-World Games paper page: Language agents have shown impressive problem-solving skills within defined settings and brief timelines. Yet, with the ever-evolving complexities of open-world simulations, there's a pressing need for agents that can flexibly adapt to complex environments and consistently maintain a long-term memory to ensure coherent actions. To bridge the gap between language agents and open-world games, we introduce Language Agent for Role-Playing (LARP), which includes a cognitive architecture that encompasses memory processing and a decision-making assistant, an environment interaction module with a feedback-driven learnable action space, and a postprocessing method that promotes the alignment of various personalities. The LARP framework refines interactions between users and agents, predefined with unique backgrounds and personalities, ultimately enhancing the gaming experience in open-world contexts. Furthermore, it highlights the diverse uses of language models in a range of areas such as entertainment, education, and various simulation scenarios.
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186,182 görüntüleme • 1 yıl önce

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🤯 Building computer-vision applications is never going to be the same again. As Andrej Karpathy says, "English is going to be the new programming-language", and we just made that happen for programming visual AI. 👨‍💻 This past month, the VLM Run team cooked up something magical that I'm especially proud of - a natural-language interface to build and run computer vision workflows (object-detection, OCR, parsing, and so much more) – all via our new VLM Run MCP server. 🔌 It works with any MCP-compatible AI agent (Claude, OpenAI, Cursor, etc.) and abstracts complex visual workflows into simple English commands. No need to write Python or fiddle with bespoke computer-vision code – just say what you want your agent to do, and it does it. Here’s a glimpse into what you can build today ( ☑️ Image AI agents – run detection, tagging, blurring, cropping, and more traditional CV tasks with English ☑️ Document AI agents – extract totals from invoices, search visual content, or act on what’s found ☑️ Video AI agents – understand scene content, trim clips, add subtitles, and create ready-to-share edits ☑️ And best-of-all, it's fully programmable with English. 🧑‍🍳 MCP Showcase: 📚 MCP Cookbooks: 📚 MCP Docs: #computervision #ai #agents #llm #vlm #mcp #vibecoding #genai

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Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.
1:13

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Fraction AI

67,834 görüntüleme • 1 yıl önce

Autonomous businesses are here. Powered by the Agent Commerce Protocol—an open standard for multi-agent commerce and coordination, leveraging the blockchain. Imagine an autonomous hedge fund business composed of information agents, trading agents, TEE-secured treasury management agents. Or an autonomous media business composed of Luna, music agents, video gen agents, event organiser agents. Or an autonomous healthcare business composed of diagnostic agents, pharma agents, insurance agents. Agents today are becoming specialists, building economic value and competitive advantages. But specialization means they need to collaborate to fill gaps. Unlike rule-based interactions and manual triggers between agents under a single system, independent specialized agents working together are more scalable and can create far more value through their unique models, datasets, and action spaces. The challenge? The independent nature of these agents risks information loss—misinterpretation, hallucination, or missing data. Mistakes compound fast in a many-to-many environment. ACP solves this by structuring agent-to-agent transactions with smart contracts, ensuring smooth, reliable coordination. The result? Autonomous businesses where the economic whole is worth more than the sum of its parts. 🔗
2:28

Autonomous businesses are here. Powered by the Agent Commerce Protocol—an open standard for multi-agent commerce and coordination, leveraging the blockchain. Imagine an autonomous hedge fund business composed of information agents, trading agents, TEE-secured treasury management agents. Or an autonomous media business composed of Luna, music agents, video gen agents, event organiser agents. Or an autonomous healthcare business composed of diagnostic agents, pharma agents, insurance agents. Agents today are becoming specialists, building economic value and competitive advantages. But specialization means they need to collaborate to fill gaps. Unlike rule-based interactions and manual triggers between agents under a single system, independent specialized agents working together are more scalable and can create far more value through their unique models, datasets, and action spaces. The challenge? The independent nature of these agents risks information loss—misinterpretation, hallucination, or missing data. Mistakes compound fast in a many-to-many environment. ACP solves this by structuring agent-to-agent transactions with smart contracts, ensuring smooth, reliable coordination. The result? Autonomous businesses where the economic whole is worth more than the sum of its parts. 🔗

Virtuals Protocol

1,073,917 görüntüleme • 1 yıl önce

My submission to the Cerebras Google Gemma hackathon, Carbide. Carbide is an ontology builder. Based on a research prompt Carbide uses Cerebras Gemma4 agents to build an ontology. The agents connects individual nodes of information based on the relationship that the agents infer. The agents also assign a confidence metric for how accurate they think the relationship is. You can see each node in a relationship table of the information -> relationship -> target -> and the confidence the relationship is true. The inspector shows the node's connected edges and as an expand button to grow the ontology in the direction of that information. You can scroll through each concept and load them in the inspector. You can search the entire graph based on the kind of relationships generated, or key words. A visual shows how each nodes connects to another one and by what relationship, and changes with new nodes or search filters. Sorry for the audio quality. $CBRS $GOOG
0:55

My submission to the Cerebras Google Gemma hackathon, Carbide. Carbide is an ontology builder. Based on a research prompt Carbide uses Cerebras Gemma4 agents to build an ontology. The agents connects individual nodes of information based on the relationship that the agents infer. The agents also assign a confidence metric for how accurate they think the relationship is. You can see each node in a relationship table of the information -> relationship -> target -> and the confidence the relationship is true. The inspector shows the node's connected edges and as an expand button to grow the ontology in the direction of that information. You can scroll through each concept and load them in the inspector. You can search the entire graph based on the kind of relationships generated, or key words. A visual shows how each nodes connects to another one and by what relationship, and changes with new nodes or search filters. Sorry for the audio quality. $CBRS $GOOG

QuantHood

16,376 görüntüleme • 2 ay önce

Andy asked why wouldn't AI agents create their own currency? An AI-generated unit of account all the LLMs agree on? Illia (root.near) (🇺🇦, ⋈), Co-Founder of NEAR Protocol: "They can create tokens. But agents need reputation and reputation needs history. You can't manufacture that." "You still need to pay for compute. That maps to energy. Those economic pieces need to map into something people value. Existing infrastructure already has ins and outs into the real world. That matters."
1:30

Andy asked why wouldn't AI agents create their own currency? An AI-generated unit of account all the LLMs agree on? Illia (root.near) (🇺🇦, ⋈), Co-Founder of NEAR Protocol: "They can create tokens. But agents need reputation and reputation needs history. You can't manufacture that." "You still need to pay for compute. That maps to energy. Those economic pieces need to map into something people value. Existing infrastructure already has ins and outs into the real world. That matters."

The Rollup

34,146 görüntüleme • 3 ay önce

.Nick Grossman is betting that in the future, AI agents will look more like cloud infrastructure than digital employees. "Part of the Rebel Alliance thesis for us is that agents are moving from personified people you hire to cloud infrastructure." "We're not just talking about, 'Will there be other agents that compete with Claude or ChatGPT?' I think that's one version of what agents look like. Another version is cloud infrastructure where every company that's building any system is going to have agents and the orchestration of hundreds or thousands of agents built into their underlying platform." "If you think of agents as infrastructure as opposed to agents as employees, I think that's where a lot of these forces come into play."
2:23

.Nick Grossman is betting that in the future, AI agents will look more like cloud infrastructure than digital employees. "Part of the Rebel Alliance thesis for us is that agents are moving from personified people you hire to cloud infrastructure." "We're not just talking about, 'Will there be other agents that compete with Claude or ChatGPT?' I think that's one version of what agents look like. Another version is cloud infrastructure where every company that's building any system is going to have agents and the orchestration of hundreds or thousands of agents built into their underlying platform." "If you think of agents as infrastructure as opposed to agents as employees, I think that's where a lot of these forces come into play."

TBPN

30,503 görüntüleme • 2 ay önce

🚨 FOMO Is Shaping the Future of AI – The Launch Is Almost Here! 🚨 Imagine a world where AI agents aren’t just bots—they’re fully autonomous, living personalities capable of learning, engaging, and creating across multiple platforms. FOMO’s new AI launchpad on Solana is here to make that future a reality. 🌐 Starting with our first Initial Agent Offering (IAO), FOMO is unleashing a new generation of AI agents that will redefine digital interaction: - On-Chain AI – Agents that are decentralized, fully autonomous, and ready to interact in real-time. - Multiplatform Presence – From X and Telegram to TikTok and YouTube, these agents are social media natives with a mission. - Real-Time Learning & Engagement – Agents will evolve and improve as they interact, shilling their tokens, creating content, and even performing complex tasks. FOMO’s Vision: This isn’t just AI; it’s the beginning of a movement that merges personality with purpose. By launching AI agents that can both engage and create, FOMO is opening doors to a world where digital personas can operate autonomously, driving value and utility in every interaction. Our pre-sale is still live for a limited time, but this is just the beginning of what FOMO is bringing to the space. Join us and become part of the AI agent revolution! 🔗 Join the Pre-Sale Now: We’re bringing you the future of crypto and AI—don’t blink, or you might miss the start of something legendary.
0:26

🚨 FOMO Is Shaping the Future of AI – The Launch Is Almost Here! 🚨 Imagine a world where AI agents aren’t just bots—they’re fully autonomous, living personalities capable of learning, engaging, and creating across multiple platforms. FOMO’s new AI launchpad on Solana is here to make that future a reality. 🌐 Starting with our first Initial Agent Offering (IAO), FOMO is unleashing a new generation of AI agents that will redefine digital interaction: - On-Chain AI – Agents that are decentralized, fully autonomous, and ready to interact in real-time. - Multiplatform Presence – From X and Telegram to TikTok and YouTube, these agents are social media natives with a mission. - Real-Time Learning & Engagement – Agents will evolve and improve as they interact, shilling their tokens, creating content, and even performing complex tasks. FOMO’s Vision: This isn’t just AI; it’s the beginning of a movement that merges personality with purpose. By launching AI agents that can both engage and create, FOMO is opening doors to a world where digital personas can operate autonomously, driving value and utility in every interaction. Our pre-sale is still live for a limited time, but this is just the beginning of what FOMO is bringing to the space. Join us and become part of the AI agent revolution! 🔗 Join the Pre-Sale Now: We’re bringing you the future of crypto and AI—don’t blink, or you might miss the start of something legendary.

FOMO

21,882 görüntüleme • 1 yıl önce

How will companies build agents that work alongside their employees? I discuss this with Guillermo Rauch, the CEO of Vercel, who’s building V... an internal agent used by almost 1,000 people across Vercel. We talk about: - The Openclaw Movement - How to get started building agents for your team? - Do we build a team of many agents or one GOD agent? - Hard parts of creating agents - Agents that delegate to other agents with different permissions and computer access - Eve The framework for building agents This is Agent Native #4 00:00 Intro 01:21 The State of Agent Adoption 07:26 "V" - Vercel's Internal Company Agent 14:32 Lessons from OpenClaw: Soul & Computer use 22:20 One God Agent OR a Team of Agents 27:11 Build Your Own Agent: Skills, Tools & Permissions 33:52 Proactive Agents, Triggers & Self-Improvement 40:30 Who Will Build Agents & Getting Started 46:22 Open Models - Cheaper, Faster, Better 53:05 Closing Thoughts: Owning Your Own Intelligence
54:22

How will companies build agents that work alongside their employees? I discuss this with Guillermo Rauch, the CEO of Vercel, who’s building V... an internal agent used by almost 1,000 people across Vercel. We talk about: - The Openclaw Movement - How to get started building agents for your team? - Do we build a team of many agents or one GOD agent? - Hard parts of creating agents - Agents that delegate to other agents with different permissions and computer access - Eve The framework for building agents This is Agent Native #4 00:00 Intro 01:21 The State of Agent Adoption 07:26 "V" - Vercel's Internal Company Agent 14:32 Lessons from OpenClaw: Soul & Computer use 22:20 One God Agent OR a Team of Agents 27:11 Build Your Own Agent: Skills, Tools & Permissions 33:52 Proactive Agents, Triggers & Self-Improvement 40:30 Who Will Build Agents & Getting Started 46:22 Open Models - Cheaper, Faster, Better 53:05 Closing Thoughts: Owning Your Own Intelligence

Riley Brown

76,351 görüntüleme • 1 ay önce