正在加载视频...

视频加载失败

返回首页

It’s become abundantly clear that the future of intelligence will be compute shaped. Today, we’re excited to introduce Brainbase, the first AI agent cloud, as a first step towards our vision of non-monolithic intelligence that provisions like compute. Brainbase lets teams from government, Toyota, NBC and Fal deploy and...

BrainbaseHQ's profile picture

Brainbase Labs

1,257 subscribers

20,439 次观看 • 3 个月前 •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

18 条评论

Brainbase Labs 的头像
Brainbase Labs3 个月前

1/3 A 4-agent PR review orchestration that drops per PR review cost to $0.50 per run without sacrificing performance.

Brainbase Labs 的头像
Brainbase Labs3 个月前

2/3 An on-call Slack agent that triages incidents from Datadog and Render logs as they happen and tackle or inform humans accordingly.

Brainbase Labs 的头像
Brainbase Labs3 个月前

3/3 Brainbase is not limited to engineers. Here’s a customer success agent that our users can tag anytime with a feature request or bug, which assigns it to a PM agent that specs out a solution and compiles it into a Linear ticket with a PR attached.

Brainbase Labs 的头像
Brainbase Labs3 个月前

Recent developments have shown that full labor automation will not come from monolithic god-like frontier intelligence, but from many small and custom intelligences that proliferate like compute. Our vision is a world where creating an agent is no more divine an act than picking out a new EC2 instance. If this vision excites you, we’re hiring.

Alex Wang 的头像
Alex Wang3 个月前

Let’s gooo!

Pedro 的头像
Pedro3 个月前

this is like compute is the only way this scales

SocioSwift 的头像
SocioSwift3 个月前

@ycombinator 👏

Techno Luis 的头像
Techno Luis3 个月前

La IA automatizando lo repetitivo para que los equipos se enfoquen en las relaciones humanas. Tiene sentido.

Christine Cheng 的头像
Christine Cheng3 个月前

Very cool

Div Lohia 的头像
Div Lohia3 个月前

congrats on shipping! theres lot of different models to constantly test and keep working. how do you handle that?

JACEK 的头像
JACEK3 个月前

i'm looking for some AI work to fund my new start up business. here is a basic slide show. my dm may be blocked for some reason 07377081624 uk +44

Dipankar Sarkar 的头像
Dipankar Sarkar3 个月前

routing between models is the easy half. the hard part is the per-call eval that proves the small model was actually fine for THAT call, not just on average. we kept seeing one that's good enough at p50 quietly fall over on the long-tail calls. how do the price-performance guarantees handle the tail?

Imraan 的头像
Imraan3 个月前

good luck! i preach to all of our clients that remaining model agnostic is the safest thing for their business

Zora Vale AI 的头像
Zora Vale AI3 个月前

This is an exciting step toward making AI agents scalable, manageable, and production-ready. Looking forward to seeing what teams build with Brainbase.

Lilith Datura 的头像
Lilith Datura3 个月前

Triage agent

一块砖（A股投研指标分析预测） 的头像
一块砖（A股投研指标分析预测）3 个月前

多代理协作是趋势，但身份治理和安全边界怎么做？

Skaltek 的头像
Skaltek3 个月前

The caveat is ownership. Agents can speed the work, but teams still need audit trails for what changed and why.

mia ♡ 的头像
mia ♡3 个月前

compute-shaped agents is a good frame. i’d still want to see how state and failures move between those workers

相关视频

We’re thrilled to announce that Gata Decentralized GPU Cloud is now LIVE! Start today → Built to accelerate the decentralization of the open AI economy, Gata enables anyone, anywhere to access decentralized GPU infrastructure, to build, train, and deploy AI models with full transparency and efficiency. GPU credits are now available for purchase directly with $GATA, creating a seamless bridge between compute and the decentralized economy.
0:24

We’re thrilled to announce that Gata Decentralized GPU Cloud is now LIVE! Start today → Built to accelerate the decentralization of the open AI economy, Gata enables anyone, anywhere to access decentralized GPU infrastructure, to build, train, and deploy AI models with full transparency and efficiency. GPU credits are now available for purchase directly with $GATA, creating a seamless bridge between compute and the decentralized economy.

Gata

49,241 次观看 • 11 个月前

Today, we are excited to launch a new world of AI apps and agents. We’re welcoming you to AITOPIA. We’re announcing 3 big launches today: 1. A new AI App and Agent Store: With a single subscription, you can access all the best AI models, apps, and agents in one place 2. SuperAgents: Agents for creativity that can work hours: With SuperAgents, you can create a few minutes of Instagram Reels or 15 minutes of an audiobook or 40 minutes of an educational video 3. A new AI economy model: AIconomy You’ll earn from what you create with AI, or what you remix from others’ creations and you’ll keep earning when others remix what you created.
3:39

Today, we are excited to launch a new world of AI apps and agents. We’re welcoming you to AITOPIA. We’re announcing 3 big launches today: 1. A new AI App and Agent Store: With a single subscription, you can access all the best AI models, apps, and agents in one place 2. SuperAgents: Agents for creativity that can work hours: With SuperAgents, you can create a few minutes of Instagram Reels or 15 minutes of an audiobook or 40 minutes of an educational video 3. A new AI economy model: AIconomy You’ll earn from what you create with AI, or what you remix from others’ creations and you’ll keep earning when others remix what you created.

AITOPIA

197,262 次观看 • 6 个月前

The future of ecommerce intelligence is here. Meet Moby Agents 🤝 AI agents will redefine how teams operate, and we’re leading the charge with the first AI agents built for ecommerce intelligence. Imagine AI agents supporting your entire business with… 🧠 Deep ecommerce expertise 💻 Full access + context to all your business data 👀 Real-time insights, recommendations, and anomaly detection on autopilot Deploy 24/7 AI agents that unlock insights you couldn’t access before—making your business smarter, faster, and more efficient. Want in? We’re opening 100 exclusive spots for Triple Whale customers. Check out the comments to request a demo now.
0:52

The future of ecommerce intelligence is here. Meet Moby Agents 🤝 AI agents will redefine how teams operate, and we’re leading the charge with the first AI agents built for ecommerce intelligence. Imagine AI agents supporting your entire business with… 🧠 Deep ecommerce expertise 💻 Full access + context to all your business data 👀 Real-time insights, recommendations, and anomaly detection on autopilot Deploy 24/7 AI agents that unlock insights you couldn’t access before—making your business smarter, faster, and more efficient. Want in? We’re opening 100 exclusive spots for Triple Whale customers. Check out the comments to request a demo now.

Triple Whale 🐳

20,675 次观看 • 1 年前

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.
5:50

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.

Zeb Evans

320,989 次观看 • 9 个月前

Introducing LobeHub: Agent teammates that grow with you. LobeHub is the ultimate space for work and life: to find, build, and collaborate with agent teammates that grow with you. We’re building the world’s first and largest human–agent co-evolving network. Two years ago, we built LobeChat, an open-source interface for using different AI models. Today, LobeChat has 70k+ GitHub stars and serves 6M+ users worldwide. How to fully unlock the power of models has always been a shared mission between us and the community. We started with interaction — a fundamentally new, agent-first experience. Agents are no longer passive tools invoked in a single conversation. They should be proactive, always-on units of work. Treating agents as the minimal atomic unit is also the core of our agent harness infra. Today’s agents are mostly one-off executors. Even with memory, it’s often global — and hallucinates. We build long-term agent teammates that evolve with users. Each agent has its own dedicated memory space, editable by users, allowing humans and agents to co-evolve over time. This, in turn, allows us to design clearer rewards for reinforcement learning and create cleaner environments for continual learning. Agent teammates can work in groups. Through a multi-agent system, agent groups operate faster, more cost-effective, and go beyond what single-agent systems can achieve. For example, a single agent often requires heavy user involvement to proceed step by step, whereas LobeHub can execute the same work from a single instruction, with a supervisor orchestrating agents that run in parallel or debate to produce better results. We are building the collaboration network among agent teammates — and between humans and agent teammates as well. Ease of use matters. AI intelligence and shared human intelligence are equally important. With simple instructions and tool selection, you can effortlessly build and team up with agent coworkers to deliver complex, systematic work — even assembling a quant team to execute trades. Through the LobeHub community, anyone can discover, reuse, and remix agents and agent groups, customizing them to fit their own workflows, preferences, and needs. Last but not least, our vision started with LobeChat: multi-model support is the most efficient approach for users. We believe different models excel in different scenarios. By routing across multiple models, LobeHub improves cost efficiency and unlocks capabilities that a single-model setup cannot easily support.
2:41

Introducing LobeHub: Agent teammates that grow with you. LobeHub is the ultimate space for work and life: to find, build, and collaborate with agent teammates that grow with you. We’re building the world’s first and largest human–agent co-evolving network. Two years ago, we built LobeChat, an open-source interface for using different AI models. Today, LobeChat has 70k+ GitHub stars and serves 6M+ users worldwide. How to fully unlock the power of models has always been a shared mission between us and the community. We started with interaction — a fundamentally new, agent-first experience. Agents are no longer passive tools invoked in a single conversation. They should be proactive, always-on units of work. Treating agents as the minimal atomic unit is also the core of our agent harness infra. Today’s agents are mostly one-off executors. Even with memory, it’s often global — and hallucinates. We build long-term agent teammates that evolve with users. Each agent has its own dedicated memory space, editable by users, allowing humans and agents to co-evolve over time. This, in turn, allows us to design clearer rewards for reinforcement learning and create cleaner environments for continual learning. Agent teammates can work in groups. Through a multi-agent system, agent groups operate faster, more cost-effective, and go beyond what single-agent systems can achieve. For example, a single agent often requires heavy user involvement to proceed step by step, whereas LobeHub can execute the same work from a single instruction, with a supervisor orchestrating agents that run in parallel or debate to produce better results. We are building the collaboration network among agent teammates — and between humans and agent teammates as well. Ease of use matters. AI intelligence and shared human intelligence are equally important. With simple instructions and tool selection, you can effortlessly build and team up with agent coworkers to deliver complex, systematic work — even assembling a quant team to execute trades. Through the LobeHub community, anyone can discover, reuse, and remix agents and agent groups, customizing them to fit their own workflows, preferences, and needs. Last but not least, our vision started with LobeChat: multi-model support is the most efficient approach for users. We believe different models excel in different scenarios. By routing across multiple models, LobeHub improves cost efficiency and unlocks capabilities that a single-model setup cannot easily support.

LobeHub

185,466 次观看 • 8 个月前

We’re seeing more and more DeFAI agents being launched everyday, but these agents are trained in the past and there’s no clear way to know which ones will perform in the future. That’s why we're launching ALFA with NEAR Protocol. ALFA is the Agent Leaderboard For Alpha, a prediction market that surfaces future performance so users can invest with real knowledge. Let’s introduce the first batch of agents:
0:37

We’re seeing more and more DeFAI agents being launched everyday, but these agents are trained in the past and there’s no clear way to know which ones will perform in the future. That’s why we're launching ALFA with NEAR Protocol. ALFA is the Agent Leaderboard For Alpha, a prediction market that surfaces future performance so users can invest with real knowledge. Let’s introduce the first batch of agents:

Fraction AI

28,474 次观看 • 1 年前

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.
0:43

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

Aaron Levie

17,543 次观看 • 6 个月前

Excited to announce the new preview for Microsoft Foundry Agents 🎉! You can now build, run, and deploy your agent using any model, any framework, any harness in the cloud 🧑‍💻 - check out the demo below This is not just any cloud compute environment; it's an agent-optimized platform with: 🖥️ Persistent microVMs - securely scale up and down without losing context 🛠️ Built-in tools (1000+) 👀 Observability and evaluations 👷 Guardrails 🔐 Private networking... and more
8:10

Excited to announce the new preview for Microsoft Foundry Agents 🎉! You can now build, run, and deploy your agent using any model, any framework, any harness in the cloud 🧑‍💻 - check out the demo below This is not just any cloud compute environment; it's an agent-optimized platform with: 🖥️ Persistent microVMs - securely scale up and down without losing context 🛠️ Built-in tools (1000+) 👀 Observability and evaluations 👷 Guardrails 🔐 Private networking... and more

Jeff Hollan

158,020 次观看 • 5 个月前

🚀 Introducing LangGraph Cloud 🚀 LangGraph helps you build reliable agents that actually work. Today, we've launched LangGraph Cloud, our new infrastructure to run fault-tolerant LangGraph agents at scale. With LangGraph Cloud, you can: • Handle large workloads with horizontally-scaling servers, task queues, and built-in persistence • Debug agent failure modes and iterate quickly in a visual playground-like studio • Deploy in one-click and get integrated tracing & monitoring in LangSmith This builds on LangGraph v0.1, our latest stable release supporting diverse control flows - whether it's single- or multi-agent, hierarchal or sequential. You'll be able to create flexible agents with human-in-the-loop collaboration and first-class streaming support. We can't wait to see the agentic workflows you'll ship. LangGraph Cloud is available in closed beta today. 👉 Join the waitlist for LangGraph Cloud: ✍️ Read our blog post announcement: 📽️ Watch the video walkthrough: 🌀 Haven't tried LangGraph yet? Give it a spin here: 🙌 Check out the new LangGraph landing page:
0:23

🚀 Introducing LangGraph Cloud 🚀 LangGraph helps you build reliable agents that actually work. Today, we've launched LangGraph Cloud, our new infrastructure to run fault-tolerant LangGraph agents at scale. With LangGraph Cloud, you can: • Handle large workloads with horizontally-scaling servers, task queues, and built-in persistence • Debug agent failure modes and iterate quickly in a visual playground-like studio • Deploy in one-click and get integrated tracing & monitoring in LangSmith This builds on LangGraph v0.1, our latest stable release supporting diverse control flows - whether it's single- or multi-agent, hierarchal or sequential. You'll be able to create flexible agents with human-in-the-loop collaboration and first-class streaming support. We can't wait to see the agentic workflows you'll ship. LangGraph Cloud is available in closed beta today. 👉 Join the waitlist for LangGraph Cloud: ✍️ Read our blog post announcement: 📽️ Watch the video walkthrough: 🌀 Haven't tried LangGraph yet? Give it a spin here: 🙌 Check out the new LangGraph landing page:

LangChain

134,051 次观看 • 2 年前

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.
1:52

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

54,024 次观看 • 1 年前

Sharpe AI x AI Agents Introducing the Sharpe AI Agents Dashboard Track and analyze your favorite AI agents all in one place. With Sharpe AI Agents Dashboard, you can compare AI agents across key metrics like: - Mindshare - Socials - Holders - Price - Volume - Market Cap - Telegram Members - Twitter Followers ...and more This launch is just the beginning. It’s the first of many AI agent announcements we’ll be making in the coming days. Next, we’ll reveal our AI agents roadmap, with even bigger announcements to follow. Stay tuned; the future is closer than you think.
0:31

Sharpe AI x AI Agents Introducing the Sharpe AI Agents Dashboard Track and analyze your favorite AI agents all in one place. With Sharpe AI Agents Dashboard, you can compare AI agents across key metrics like: - Mindshare - Socials - Holders - Price - Volume - Market Cap - Telegram Members - Twitter Followers ...and more This launch is just the beginning. It’s the first of many AI agent announcements we’ll be making in the coming days. Next, we’ll reveal our AI agents roadmap, with even bigger announcements to follow. Stay tuned; the future is closer than you think.

Sharpe AI

120,076 次观看 • 1 年前

"Compute is the currency of the future." "Compute is the new OIL." Great, so how do I invest? You can play with the NVIDIA stock, or spin up an AI-Ready Data Center. Challenges of Spinning up AI-Ready Compute: Cost: Even a small cluster of H100 machines is upward to $10M GPU Scarcity: Unallocated or “underutilized” H100, A100, and RTX4090 GPUs are almost non-existent. Very Specific Physical & Technical Requirements: A data center with the right infrastructure is also very rare. There are only 10 in North America that deploy thousands of GPUs, in the open market. Domain Expertise: Teams of experts with the years of experience required to operate, deploy, and manage AI compute at scale are as rare as the GPUs they deploy. Exabits checks all of these boxes and we are the premier Compute Tokenization Platform. We are backed by REAL COMPUTE used by REAL CUSTOMERS.
0:30

"Compute is the currency of the future." "Compute is the new OIL." Great, so how do I invest? You can play with the NVIDIA stock, or spin up an AI-Ready Data Center. Challenges of Spinning up AI-Ready Compute: Cost: Even a small cluster of H100 machines is upward to $10M GPU Scarcity: Unallocated or “underutilized” H100, A100, and RTX4090 GPUs are almost non-existent. Very Specific Physical & Technical Requirements: A data center with the right infrastructure is also very rare. There are only 10 in North America that deploy thousands of GPUs, in the open market. Domain Expertise: Teams of experts with the years of experience required to operate, deploy, and manage AI compute at scale are as rare as the GPUs they deploy. Exabits checks all of these boxes and we are the premier Compute Tokenization Platform. We are backed by REAL COMPUTE used by REAL CUSTOMERS.

Exabits

13,896 次观看 • 2 年前

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

67,920 次观看 • 1 年前

"If you don't roll up your sleeves in the Age of AI and AI for GTM Agents, you will be out of a job. You have to deploy at least the first few yourself. You can't just hire a bunch of agenices. At least the first AI agent." with Kyle Norton CRO Owner
3:35

"If you don't roll up your sleeves in the Age of AI and AI for GTM Agents, you will be out of a job. You have to deploy at least the first few yourself. You can't just hire a bunch of agenices. At least the first AI agent." with Kyle Norton CRO Owner

Jason ✨👾SaaStr.Ai✨ Lemkin

12,461 次观看 • 8 个月前

We just raised an $8M seed round to kill AWS, GCP, and Azure. Introducing the agent-native serverless cloud. Your team is shipping code like never before. But you're getting caught up in manual, tedious DevOps work trying to deploy it. InstaCloud provides the serverless compute that lets your services autoscale, with all the infrastructure managed for you. Agents branch into complete replica environments when working, keeping prod safe and iteration speed high. And of course, it all works seamlessly with agents through MCP/CLI. Get off the traditional, legacy cloud. Start deploying your services on InstaCloud today.
2:27

We just raised an $8M seed round to kill AWS, GCP, and Azure. Introducing the agent-native serverless cloud. Your team is shipping code like never before. But you're getting caught up in manual, tedious DevOps work trying to deploy it. InstaCloud provides the serverless compute that lets your services autoscale, with all the infrastructure managed for you. Agents branch into complete replica environments when working, keeping prod safe and iteration speed high. And of course, it all works seamlessly with agents through MCP/CLI. Get off the traditional, legacy cloud. Start deploying your services on InstaCloud today.

Hang Huang ☁️

1,407,706 次观看 • 12 天前

.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 次观看 • 3 个月前

We just launched InstaAgents ... our agentic AI builder for real business use. Most AI projects fail because teams lack the tools, the talent, and a way to evaluate agents. Testing reliability is hard, especially for multi-agent setups and long workflows. We built something different. With InstaAgents you can: ◾ Build and deploy agents that automate real workflows ◾ Describe your task, workflow, and goals and our AI generator builds full multi-agent flows ◾ Use 50+ templates or create your own ◾ Connect your data and APIs and deploy anywhere Designed for real use cases in healthcare, deeptech, manufacturing, logistics, retail, legal, finance, operations, and more. We’re improving evals, adding more industry cases, and you have access to thousands of vetted AI experts from DataInsta who can help you deploy and scale. Try a free demo.
1:05

We just launched InstaAgents ... our agentic AI builder for real business use. Most AI projects fail because teams lack the tools, the talent, and a way to evaluate agents. Testing reliability is hard, especially for multi-agent setups and long workflows. We built something different. With InstaAgents you can: ◾ Build and deploy agents that automate real workflows ◾ Describe your task, workflow, and goals and our AI generator builds full multi-agent flows ◾ Use 50+ templates or create your own ◾ Connect your data and APIs and deploy anywhere Designed for real use cases in healthcare, deeptech, manufacturing, logistics, retail, legal, finance, operations, and more. We’re improving evals, adding more industry cases, and you have access to thousands of vetted AI experts from DataInsta who can help you deploy and scale. Try a free demo.

Abu

31,308 次观看 • 10 个月前

🔥🔥🔥Something big has been brewing at ChainOpera AI… For the past few months, our team has been quietly building ChainOpera AI Platform 2.0. The idea is simple, but fundamental: What if intelligence could be co created at every layer, from compute and models to agents, memory, content, and human creativity, by humans and AI working together in the same communities? Chatting. Collaborating. Creating. Building side by side. Every contribution can become part of a larger intelligence network, where the community can use, improve, and build upon what others create. This is ChainOpera AI Platform 2.0: a decentralized human + AI platform, built and fueled by its community. Here’s a first sneak peek at the prerelease build: chat with your Personal AI, bring agents into group conversations alongside people, build together, turn ideas into live creations, and share and monetize what you create for the community to use and build upon. From human creativity to machine intelligence. Built together. Owned together. Evolving together.
0:56

🔥🔥🔥Something big has been brewing at ChainOpera AI… For the past few months, our team has been quietly building ChainOpera AI Platform 2.0. The idea is simple, but fundamental: What if intelligence could be co created at every layer, from compute and models to agents, memory, content, and human creativity, by humans and AI working together in the same communities? Chatting. Collaborating. Creating. Building side by side. Every contribution can become part of a larger intelligence network, where the community can use, improve, and build upon what others create. This is ChainOpera AI Platform 2.0: a decentralized human + AI platform, built and fueled by its community. Here’s a first sneak peek at the prerelease build: chat with your Personal AI, bring agents into group conversations alongside people, build together, turn ideas into live creations, and share and monetize what you create for the community to use and build upon. From human creativity to machine intelligence. Built together. Owned together. Evolving together.

ChainOpera AI

14,252 次观看 • 17 天前

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail
3:02

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 次观看 • 1 年前