Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

With the launch of GLM-5, introduces Agent Mode. - Agent Mode: Automatically breaks down tasks, orchestrates tools, drives execution, and delivers ready-to-use files. - Data Insights & Smart Writing: Upload data for instant visualizations. Go from outline to finished draft, all in one place. - AI Slides / Full-Stack...

Zai_org's profile picture

Z.ai

129,772 subscribers

29,865 Aufrufe • vor 7 Monaten •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

AI browsing that’s safe for work? Yes, please. Copilot Mode in Edge for Business: 🤖 Agent Mode: Automate multi-step workflows and crush repetitive tasks 🧠 Multi-tab reasoning: No more tab-hopping — Copilot pulls insights from up to 30 tabs ✨ Summarize, analyze, create: Turn pages, files, and ideas into action — all in one place Preview coming soon. Learn more: [
1:00

AI browsing that’s safe for work? Yes, please. Copilot Mode in Edge for Business: 🤖 Agent Mode: Automate multi-step workflows and crush repetitive tasks 🧠 Multi-tab reasoning: No more tab-hopping — Copilot pulls insights from up to 30 tabs ✨ Summarize, analyze, create: Turn pages, files, and ideas into action — all in one place Preview coming soon. Learn more: [

Microsoft Edge

311,718 Aufrufe • vor 10 Monaten

It is now way easier to build multi-agent workflows in n8n with the new AI Agent Tool node. Instead of juggling sub workflows a parent AI Agent can now use other Agents as tools even several layers deep. Max shows how a cheap GPT 4.1 nano Agent handles heavy data and sends summaries to a parent Agent saving token costs and making debugging simpler. Watch the full walkthrough:
0:38

It is now way easier to build multi-agent workflows in n8n with the new AI Agent Tool node. Instead of juggling sub workflows a parent AI Agent can now use other Agents as tools even several layers deep. Max shows how a cheap GPT 4.1 nano Agent handles heavy data and sends summaries to a parent Agent saving token costs and making debugging simpler. Watch the full walkthrough:

n8n.io

27,808 Aufrufe • vor 1 Jahr

The future of automation at the Department of War 🇺🇸 has arrived. We are excited to announce the launch of Agent Designer, now available in first AI instance, Google Google Gemini. All 3 million Department of War personnel now have the power to create their own custom AI assistants to automate tasks and streamline complex workflows, with absolutely no coding experience needed. These custom agents can perform multi-step tasks, ingest various data sources, and be shared with teams for immediate deployment. Now, operators can automatically generate after-action reports, analysts can synthesize CUI images into memos, and comptrollers can build apps to analyze financial data. From logistics to strategy, Agent Designer empowers you to build the tools needed for increased efficiency. Several pre-built agents are already available in Gemini to address common workflows. An “AI-first” Department of War empowers the warfighter to address bigger problems, rather than being burdened by tedious tasks.
1:03

The future of automation at the Department of War 🇺🇸 has arrived. We are excited to announce the launch of Agent Designer, now available in first AI instance, Google Google Gemini. All 3 million Department of War personnel now have the power to create their own custom AI assistants to automate tasks and streamline complex workflows, with absolutely no coding experience needed. These custom agents can perform multi-step tasks, ingest various data sources, and be shared with teams for immediate deployment. Now, operators can automatically generate after-action reports, analysts can synthesize CUI images into memos, and comptrollers can build apps to analyze financial data. From logistics to strategy, Agent Designer empowers you to build the tools needed for increased efficiency. Several pre-built agents are already available in Gemini to address common workflows. An “AI-first” Department of War empowers the warfighter to address bigger problems, rather than being burdened by tedious tasks.

Department of War CTO

14,523 Aufrufe • vor 6 Monaten

Sharing our latest short course: Building and Evaluating Data Agents, created in collaboration with Snowflake and taught by Anupam Datta (Anupam Datta) and Josh Reini (Josh Reini). A data agent extracts data from sources such as files or databases, analyzes it, and provides insights and visualizes its findings. But most data agents struggle with reliability or can't handle multi-step reasoning. In this course, you'll learn to build, trace, and evaluate a multi-agent workflow that plans tasks, pulls context from structured and unstructured data, performs web search, and summarizes or visualizes the final results. Learn more and enroll for free!
3:20

Sharing our latest short course: Building and Evaluating Data Agents, created in collaboration with Snowflake and taught by Anupam Datta (Anupam Datta) and Josh Reini (Josh Reini). A data agent extracts data from sources such as files or databases, analyzes it, and provides insights and visualizes its findings. But most data agents struggle with reliability or can't handle multi-step reasoning. In this course, you'll learn to build, trace, and evaluate a multi-agent workflow that plans tasks, pulls context from structured and unstructured data, performs web search, and summarizes or visualizes the final results. Learn more and enroll for free!

DeepLearning.AI

40,878 Aufrufe • vor 1 Jahr

🚨 AI Agents Can Now Embed Any App And Create Complex Visualizations Weekend launches are the best!! - AI agents can embed and use any app - do detailed system and engineering design - create 3D models for data-centers and scientific research We cleverly mix and match LLMs. Opus 4.8 combined with GLM 5.2 and GPT 5..5 Here is a video of the Abacus AI agent designing a 3D data center
0:54

🚨 AI Agents Can Now Embed Any App And Create Complex Visualizations Weekend launches are the best!! - AI agents can embed and use any app - do detailed system and engineering design - create 3D models for data-centers and scientific research We cleverly mix and match LLMs. Opus 4.8 combined with GLM 5.2 and GPT 5..5 Here is a video of the Abacus AI agent designing a 3D data center

Bindu Reddy

7,750,746 Aufrufe • vor 3 Monaten

Say hi to OK Computer, Kimi's agent mode 🤖🎸 Your AI product & engineering team, all in one. ✨ From chat → multi-page websites, mobile first designs, editable slides ✨ From up to 1 million rows of data → interactive dashboards ✨ Agency: self-scopes, surveys & designs ✨ Natively trained on tools: file system, browser, terminal ✨ More steps, tokens & tools than chat mode, with turbo K2 An agentic model with its own computer, K2 now has true agency.
1:02

Say hi to OK Computer, Kimi's agent mode 🤖🎸 Your AI product & engineering team, all in one. ✨ From chat → multi-page websites, mobile first designs, editable slides ✨ From up to 1 million rows of data → interactive dashboards ✨ Agency: self-scopes, surveys & designs ✨ Natively trained on tools: file system, browser, terminal ✨ More steps, tokens & tools than chat mode, with turbo K2 An agentic model with its own computer, K2 now has true agency.

Kimi.ai

303,057 Aufrufe • vor 1 Jahr

Agent mode is now available in public preview for all users in Visual Studio 17.14. Agent mode in Visual Studio allows you to define tasks using natural language, with Copilot autonomously planning, editing your codebase, invoking tools, and iterating to resolve issues. Unlike Copilot Chat or Edits, agent mode doesn’t stop at one suggestion or file edit. Read more about it in our blog. 📖 #visualstudionews #githubcopilot #agent
1:02

Agent mode is now available in public preview for all users in Visual Studio 17.14. Agent mode in Visual Studio allows you to define tasks using natural language, with Copilot autonomously planning, editing your codebase, invoking tools, and iterating to resolve issues. Unlike Copilot Chat or Edits, agent mode doesn’t stop at one suggestion or file edit. Read more about it in our blog. 📖 #visualstudionews #githubcopilot #agent

Visual Studio

93,286 Aufrufe • vor 1 Jahr

New course in collaboration with CrewAI, and taught by its Co-Founder and CEO, João Moura! In "Design, Develop, and Deploy Multi-Agent Systems" you'll go deep into building teams of AI agents that collaborate to handle complex, end-to-end workflows. You’ll design systems that plan, reason, and coordinate, with tools, memory, and guardrails that make them reliable and production-ready. Learn more and enroll now 👉 Featuring insights from Weaviate AI Database, Snyk, Exa, and AB InBev, whose work with CrewAI demonstrates how multi-agent systems are being applied in the field today.
0:56

New course in collaboration with CrewAI, and taught by its Co-Founder and CEO, João Moura! In "Design, Develop, and Deploy Multi-Agent Systems" you'll go deep into building teams of AI agents that collaborate to handle complex, end-to-end workflows. You’ll design systems that plan, reason, and coordinate, with tools, memory, and guardrails that make them reliable and production-ready. Learn more and enroll now 👉 Featuring insights from Weaviate AI Database, Snyk, Exa, and AB InBev, whose work with CrewAI demonstrates how multi-agent systems are being applied in the field today.

DeepLearning.AI

33,849 Aufrufe • vor 10 Monaten

Grok 4.3 Beta is insanely good and now comes with powerful new tools that are super helpful for everyday use: • Create clean slides, graphs, images and dashboards • Pull real-time data and images directly from the web • Run smooth multi-step workflows • Analyze videos Grok is being built for real-world use - better tools, richer context, and real day-to-day signals make this a big step toward Grok becoming part of everyday life You can now research, visualize, and package your ideas end-to-end..... from concept to finished presentation or dashboard all in one place And the Grok Computer is coming very soon 🔥
0:21

Grok 4.3 Beta is insanely good and now comes with powerful new tools that are super helpful for everyday use: • Create clean slides, graphs, images and dashboards • Pull real-time data and images directly from the web • Run smooth multi-step workflows • Analyze videos Grok is being built for real-world use - better tools, richer context, and real day-to-day signals make this a big step toward Grok becoming part of everyday life You can now research, visualize, and package your ideas end-to-end..... from concept to finished presentation or dashboard all in one place And the Grok Computer is coming very soon 🔥

X Freeze

572,563 Aufrufe • vor 5 Monaten

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:
2:23

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:

Andrew Ng

204,109 Aufrufe • vor 9 Monaten

Solidus Ai Tech Presents Agent Forge: Transforming AI Technology! Agent Forge is more than a platform—it's a revolution in how users interact with AI agents. Accessible to everyone, from seasoned professionals to newcomers, it empowers users to: 🔹Create Autonomous AI Agents: Automate processes, execute strategies, and stay ahead 24/7. 🔹 Gain Real-Time Insights: Stay informed with market updates via leading data platforms like CoinGecko and CoinMarketCap. 🔹 Simplify Complex Systems: Build automated workflows and manage digital strategies effortlessly, with no coding required. 🔹 Optimize Financial Management: Track data, optimize resources, and manage workflows with ease. 🔹 Breaking Barriers in AI Automation: Agent Forge makes advanced AI accessible to all, eliminating traditional technical challenges. 💡 Powered by AITECH HPC Data Center, Agent Forge ensures speed, security, and eco-friendly operations. 🗓 Coming Soon Agent Forge isn’t just a launch—it’s a leap forward.
1:13

Solidus Ai Tech Presents Agent Forge: Transforming AI Technology! Agent Forge is more than a platform—it's a revolution in how users interact with AI agents. Accessible to everyone, from seasoned professionals to newcomers, it empowers users to: 🔹Create Autonomous AI Agents: Automate processes, execute strategies, and stay ahead 24/7. 🔹 Gain Real-Time Insights: Stay informed with market updates via leading data platforms like CoinGecko and CoinMarketCap. 🔹 Simplify Complex Systems: Build automated workflows and manage digital strategies effortlessly, with no coding required. 🔹 Optimize Financial Management: Track data, optimize resources, and manage workflows with ease. 🔹 Breaking Barriers in AI Automation: Agent Forge makes advanced AI accessible to all, eliminating traditional technical challenges. 💡 Powered by AITECH HPC Data Center, Agent Forge ensures speed, security, and eco-friendly operations. 🗓 Coming Soon Agent Forge isn’t just a launch—it’s a leap forward.

AITECH CLOUD NETWORK

171,779 Aufrufe • vor 1 Jahr

3. Agent factory: Foundry is the complete app platform for building apps and agents. We are adding support for more models from Grok, Hugging Face, Meta, Mistral, and more. Plus: Agentic retrieval in Azure AI Search, Foundry Agent Service, integration with Copilot Studio, and more. And we are ensuring the tools you already use for identity, management, and security will now all extend to agents too. The NFL has already used Foundry, along with our data stack, to run its recent Combine.
1:41

3. Agent factory: Foundry is the complete app platform for building apps and agents. We are adding support for more models from Grok, Hugging Face, Meta, Mistral, and more. Plus: Agentic retrieval in Azure AI Search, Foundry Agent Service, integration with Copilot Studio, and more. And we are ensuring the tools you already use for identity, management, and security will now all extend to agents too. The NFL has already used Foundry, along with our data stack, to run its recent Combine.

Satya Nadella

184,995 Aufrufe • vor 1 Jahr

Agentic Browser is now live! This feature allows your AI agent to access real-time internet information for tasks like answering questions or finding recommendations. With this update, you can now see your AI agent's thought process before it responds to your questions—offering greater transparency and insights. Additional updates: •The initial quota of 50 messages per agent has been significantly increased to enable more extensive experimentation •We’ve fine-tuned the AI agents, making their responses more engaging and interactive •We also pushed along crypto social insights tools sourced from Coindesk, Cointelegraph, Cryptocompare and many more, your AI agent now have access to real-time market data
0:54

Agentic Browser is now live! This feature allows your AI agent to access real-time internet information for tasks like answering questions or finding recommendations. With this update, you can now see your AI agent's thought process before it responds to your questions—offering greater transparency and insights. Additional updates: •The initial quota of 50 messages per agent has been significantly increased to enable more extensive experimentation •We’ve fine-tuned the AI agents, making their responses more engaging and interactive •We also pushed along crypto social insights tools sourced from Coindesk, Cointelegraph, Cryptocompare and many more, your AI agent now have access to real-time market data

ai9000

84,665 Aufrufe • vor 1 Jahr

THIS GUY BUILT A COMMAND CENTER FOR MANAGING AI AGENT TEAMS he was running 20+ agents through openclaw. all from terminal tabs and Discord. 12 tabs open. still losing track of who's doing what. which cron failed. so he built a dashboard that gives you one place to see everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.
1:06

THIS GUY BUILT A COMMAND CENTER FOR MANAGING AI AGENT TEAMS he was running 20+ agents through openclaw. all from terminal tabs and Discord. 12 tabs open. still losing track of who's doing what. which cron failed. so he built a dashboard that gives you one place to see everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.

Om Patel

47,207 Aufrufe • vor 6 Monaten

🚨NEW EPISODE: AI Is Changing How We Work with Crypto Data🚨 In today's episode, we're joined by Kofi to discuss how AI agents are fundamentally changing crypto data analysis, research, and engineering workflows. We discuss: - The evolution from manual coding to AI-assisted development - How MCPs unlock onchain data exploration - Using Herd MCP to analyze smart contracts - AI agents for protocol research and data engineering - Context windows, planning, and agent workflows - Cursor vs OpenCode vs Claude Code (Anthropic) - Managing multiple agents simultaneously - Model selection, costs, and productivity tradeoffs - Building internal AI knowledge bases - Agent orchestration and autonomous workflows - Training agents to replicate human expertise - The future of AI-powered crypto analytics - And much more—enjoy! — Timestamps: (00:00) Introduction (01:24) AI replaces frontends (03:24) Herd MCP demo (05:40) Exploring contracts with AI (08:06) Exploration, planning, execution (11:38) Investigating onchain activity (17:10) Managing agent workflows (20:20) Multi-agent productivity (23:01) Model selection tradeoffs (29:11) Trusting AI outputs (31:28) Missing links today (34:37) Agent orchestration future (38:02) Training agents from work (38:20) Outro
38:58

🚨NEW EPISODE: AI Is Changing How We Work with Crypto Data🚨 In today's episode, we're joined by Kofi to discuss how AI agents are fundamentally changing crypto data analysis, research, and engineering workflows. We discuss: - The evolution from manual coding to AI-assisted development - How MCPs unlock onchain data exploration - Using Herd MCP to analyze smart contracts - AI agents for protocol research and data engineering - Context windows, planning, and agent workflows - Cursor vs OpenCode vs Claude Code (Anthropic) - Managing multiple agents simultaneously - Model selection, costs, and productivity tradeoffs - Building internal AI knowledge bases - Agent orchestration and autonomous workflows - Training agents to replicate human expertise - The future of AI-powered crypto analytics - And much more—enjoy! — Timestamps: (00:00) Introduction (01:24) AI replaces frontends (03:24) Herd MCP demo (05:40) Exploring contracts with AI (08:06) Exploration, planning, execution (11:38) Investigating onchain activity (17:10) Managing agent workflows (20:20) Multi-agent productivity (23:01) Model selection tradeoffs (29:11) Trusting AI outputs (31:28) Missing links today (34:37) Agent orchestration future (38:02) Training agents from work (38:20) Outro

Indexed Podcast

10,588 Aufrufe • vor 3 Monaten

Introducing NEO: The first Agentic Machine Learning Engineer. It works like a full-stack ML engineer that never sleeps: handling data exploration, feature engineering, training, tuning, deployment, and monitoring, end to end. Powered by 11 specialized agents, NEO runs autonomously, saving ML engineers thousands of hours and making them 10x faster. Benchmarks: Tested on 75 Kaggle competitions, NEO scored a medal in 34% of them, significantly outperforming Microsoft’s RD Agent (22.4%) on the MLE Bench. This sets a new state of the art for autonomous ML systems. NEO runs on a novel multi-agent orchestrator, powered by a multi-step reasoning engine, context transfer protocol, and agent memory, built to solve complex workflows end to end. And with human-in-the-loop mode, you can guide, inspect, and override any step. You're always in command. NEO is built for real world workflows and ready for production. NEO is here to make every ML engineer truly superhuman. Watch NEO in action:
3:51

Introducing NEO: The first Agentic Machine Learning Engineer. It works like a full-stack ML engineer that never sleeps: handling data exploration, feature engineering, training, tuning, deployment, and monitoring, end to end. Powered by 11 specialized agents, NEO runs autonomously, saving ML engineers thousands of hours and making them 10x faster. Benchmarks: Tested on 75 Kaggle competitions, NEO scored a medal in 34% of them, significantly outperforming Microsoft’s RD Agent (22.4%) on the MLE Bench. This sets a new state of the art for autonomous ML systems. NEO runs on a novel multi-agent orchestrator, powered by a multi-step reasoning engine, context transfer protocol, and agent memory, built to solve complex workflows end to end. And with human-in-the-loop mode, you can guide, inspect, and override any step. You're always in command. NEO is built for real world workflows and ready for production. NEO is here to make every ML engineer truly superhuman. Watch NEO in action:

Neo AI

19,571,775 Aufrufe • vor 1 Jahr

YOUR AI AGENT CAN NOW COLLECT DATA FROM ALMOST ANY WEBSITE X, YouTube, Reddit, random websites, basically whatever you need for research, analytics or monitoring. Here are 3 GitHub tools that let your agent pull the data for you. 1. Agent-Reach Bundles tools for working with different platforms in one place. X, YouTube, Reddit, GitHub and more. 2. Patchright Enhanced Works through the browser with Playwright. You can listen to the requests a website makes and pull the data you need through a script. So if a website doesn’t have a proper API, you still have a way to get the data. 3. Scrapling A general purpose tool for pulling data from web pages. And the best part is that you can give all of this to your AI agent. For example: “Collect posts from 100 X accounts from the last month, find the most popular topics and analyze what’s working.” Or: “Collect reviews about this product from Reddit and YouTube and summarize the main complaints.” You tell the agent what data you need → it writes the code → collects the data → gives you the result. Basically, you’re giving your agent the ability to pull data from almost anywhere on the web. That opens up a whole different level of stuff you can automate.
0:41

YOUR AI AGENT CAN NOW COLLECT DATA FROM ALMOST ANY WEBSITE X, YouTube, Reddit, random websites, basically whatever you need for research, analytics or monitoring. Here are 3 GitHub tools that let your agent pull the data for you. 1. Agent-Reach Bundles tools for working with different platforms in one place. X, YouTube, Reddit, GitHub and more. 2. Patchright Enhanced Works through the browser with Playwright. You can listen to the requests a website makes and pull the data you need through a script. So if a website doesn’t have a proper API, you still have a way to get the data. 3. Scrapling A general purpose tool for pulling data from web pages. And the best part is that you can give all of this to your AI agent. For example: “Collect posts from 100 X accounts from the last month, find the most popular topics and analyze what’s working.” Or: “Collect reviews about this product from Reddit and YouTube and summarize the main complaints.” You tell the agent what data you need → it writes the code → collects the data → gives you the result. Basically, you’re giving your agent the ability to pull data from almost anywhere on the web. That opens up a whole different level of stuff you can automate.

TeddyCEO

198,568 Aufrufe • vor 11 Tagen

We're excited to introduce Box + Perplexity Computer – where your AI assistant becomes a true operator, working directly within your content hub. Empower your agents with: → A Real Filesystem for AI: Seamlessly connect Perplexity with your Box files → Intelligent Insights: Point Perplexity across multiple files to surface insights, patterns, and answers that drive strategic decisions. → Automated Multi-Step Workflows: Perplexity Computer handles complex tasks efficiently in the background. → Secure & Governed Operations: Leverage Box's security and permissions, ensuring your AI operates with the right access and governance. Watch how Box + Perplexity Computer transforms raw data into actionable intelligence, like building a comprehensive competitive brief from multiple documents.
1:29

We're excited to introduce Box + Perplexity Computer – where your AI assistant becomes a true operator, working directly within your content hub. Empower your agents with: → A Real Filesystem for AI: Seamlessly connect Perplexity with your Box files → Intelligent Insights: Point Perplexity across multiple files to surface insights, patterns, and answers that drive strategic decisions. → Automated Multi-Step Workflows: Perplexity Computer handles complex tasks efficiently in the background. → Secure & Governed Operations: Leverage Box's security and permissions, ensuring your AI operates with the right access and governance. Watch how Box + Perplexity Computer transforms raw data into actionable intelligence, like building a comprehensive competitive brief from multiple documents.

Box

246,743 Aufrufe • vor 6 Monaten

Introducing NEO: The first Autonomous Machine Learning Engineer. It works like a full-stack ML engineer that never sleeps: handling data exploration, feature engineering, training, tuning, deployment, and monitoring, end to end. Powered by 11 specialized agents, NEO runs autonomously, saving ML engineers thousands of hours and making them 10x faster. Benchmarks: Tested on 75 Kaggle competitions, NEO scored a medal in 34.2% of them, significantly outperforming Microsoft’s RD Agent (22.4%) on OpenAI's MLE Bench. This sets a new state of the art for autonomous ML systems. NEO runs on a novel multi-agent orchestrator, powered by a multi-step reasoning engine, context transfer protocol, and agent memory, built to solve complex workflows end to end. And with human-in-the-loop mode, you can guide, inspect, and override any step. You're always in command. NEO is built for real world workflows and ready for production. NEO is here to make every ML engineer truly superhuman. Watch NEO in action:
3:51

Introducing NEO: The first Autonomous Machine Learning Engineer. It works like a full-stack ML engineer that never sleeps: handling data exploration, feature engineering, training, tuning, deployment, and monitoring, end to end. Powered by 11 specialized agents, NEO runs autonomously, saving ML engineers thousands of hours and making them 10x faster. Benchmarks: Tested on 75 Kaggle competitions, NEO scored a medal in 34.2% of them, significantly outperforming Microsoft’s RD Agent (22.4%) on OpenAI's MLE Bench. This sets a new state of the art for autonomous ML systems. NEO runs on a novel multi-agent orchestrator, powered by a multi-step reasoning engine, context transfer protocol, and agent memory, built to solve complex workflows end to end. And with human-in-the-loop mode, you can guide, inspect, and override any step. You're always in command. NEO is built for real world workflows and ready for production. NEO is here to make every ML engineer truly superhuman. Watch NEO in action:

Neo AI

861,453 Aufrufe • vor 1 Jahr