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What happens when frontier-level AI no longer requires an internet connection? Gemma 4 brings advanced AI directly to local devices, helping developers build multimodal, agentic experiences anywhere. Learn how communities are already putting it to work, from offline healthcare systems to indigenous language support. Start building ✨ →

Google for Developers

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30,126 просмотров • 2 месяцев назад •via X (Twitter)

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AI is rapidly evolving, and it’s reshaping how and where computing happens. From data center infrastructure to AI systems in the physical world, to the future of personal AI devices, intelligence is being distributed across a new compute landscape. At the edge, more agentic experiences are starting to show up, expanding what devices need to do. Tomorrow in New York, we’ll share what Qualcomm is building across it and how it will drive our next phase of growth. Stay tuned for #QCOMInvestorDay.

AI is rapidly evolving, and it’s reshaping how and where computing happens. From data center infrastructure to AI systems in the physical world, to the future of personal AI devices, intelligence is being distributed across a new compute landscape. At the edge, more agentic experiences are starting to show up, expanding what devices need to do. Tomorrow in New York, we’ll share what Qualcomm is building across it and how it will drive our next phase of growth. Stay tuned for #QCOMInvestorDay.

Cristiano R. Amon

15,783 просмотров • 2 месяцев назад

Today, we’re launching Gemma 4, our most intelligent open models to date. Built with the same breakthrough technology as Gemini 3, Gemma 4 brings advanced reasoning to your personal hardware and devices. Here’s what Gemma 4 unlocks for developers: — Intelligence-per-parameter: Our 31B (Dense) and 26B (MoE) models deliver state-of-the-art performance for their size, outcompeting models 20x their size on Arena.ai — Commercial flexibility: Released under a permissive Apache 2.0 license for complete developer flexibility and digital sovereignty — Agentic workflows: Native support for function-calling and structured JSON output allows you to build reliable, autonomous agents — Multimodal edge AI: The E2B and E4B models bring native vision, audio, and low latency to mobile and IoT devices — Long-context reasoning: Up to 256K context windows allow you to process entire repositories or large documents in a single prompt Whether you're building global applications in 140+ languages or local-first AI code assistants, Gemma 4 is built to be your foundation. Explore in Google AI Studio or download the weights on Hugging Face, Kaggle, and ollama.

Today, we’re launching Gemma 4, our most intelligent open models to date. Built with the same breakthrough technology as Gemini 3, Gemma 4 brings advanced reasoning to your personal hardware and devices. Here’s what Gemma 4 unlocks for developers: — Intelligence-per-parameter: Our 31B (Dense) and 26B (MoE) models deliver state-of-the-art performance for their size, outcompeting models 20x their size on Arena.ai — Commercial flexibility: Released under a permissive Apache 2.0 license for complete developer flexibility and digital sovereignty — Agentic workflows: Native support for function-calling and structured JSON output allows you to build reliable, autonomous agents — Multimodal edge AI: The E2B and E4B models bring native vision, audio, and low latency to mobile and IoT devices — Long-context reasoning: Up to 256K context windows allow you to process entire repositories or large documents in a single prompt Whether you're building global applications in 140+ languages or local-first AI code assistants, Gemma 4 is built to be your foundation. Explore in Google AI Studio or download the weights on Hugging Face, Kaggle, and ollama.

Google AI

1,670,609 просмотров • 5 месяцев назад

Gemma 4 can run on phones without an internet connection! 🤯 It can perform local agentic tasks, such as logging and analyzing trends. When connected, it can also make API calls. Want to try it yourself? Get the Google AI Edge App on iOS or Android. (🔊 Sound on for the demo!)

Gemma 4 can run on phones without an internet connection! 🤯 It can perform local agentic tasks, such as logging and analyzing trends. When connected, it can also make API calls. Want to try it yourself? Get the Google AI Edge App on iOS or Android. (🔊 Sound on for the demo!)

Google Gemma

760,073 просмотров • 5 месяцев назад

We interviewed builders at the Kite AI KITE AI x Moca Network 📍Identity Week 🇺🇸 Identity House – Cannes Edition. From zk credentials to decentralized reputation systems, they’re building the future of onchain identity, and many are already embracing Kite AI’s agent identity ideas. They see the agentic internet as the next frontier. Watch what they had to say. 👇

We interviewed builders at the Kite AI KITE AI x Moca Network 📍Identity Week 🇺🇸 Identity House – Cannes Edition. From zk credentials to decentralized reputation systems, they’re building the future of onchain identity, and many are already embracing Kite AI’s agent identity ideas. They see the agentic internet as the next frontier. Watch what they had to say. 👇

KITE AI

15,826 просмотров • 1 год назад

What if quality healthcare could travel farther than roads ever could? Across India, AI and digital innovation are helping reimagine how healthcare is delivered. By accelerating medicine discovery, enabling connected care and building stronger health systems, technology is helping bring timely, quality healthcare closer to millions. At the Gates Foundation, we work with governments, innovators, and partners to support solutions that can scale, so that geography is no longer a barrier. Next Gen Health - Built for Billions

What if quality healthcare could travel farther than roads ever could? Across India, AI and digital innovation are helping reimagine how healthcare is delivered. By accelerating medicine discovery, enabling connected care and building stronger health systems, technology is helping bring timely, quality healthcare closer to millions. At the Gates Foundation, we work with governments, innovators, and partners to support solutions that can scale, so that geography is no longer a barrier. Next Gen Health - Built for Billions

Gates Foundation India

510,125 просмотров • 3 месяцев назад

The QVAC SDK puts the "brain" directly into your pocket. From real-time on-device translation to multimodal understanding, build apps that work everywhere, even 30,000 feet in the air. Local AI is here: 💡Offline-First: No cloud, no latency, no "Department of Truth". 💻 Universal API: One codebase for iOS, Android, macOS, and Linux. 🔍 Multimodal: Understanding text, audio, and images without a server. If you can dream it, you can build it. The era of Stable Intelligence has begun. Start building:

The QVAC SDK puts the "brain" directly into your pocket. From real-time on-device translation to multimodal understanding, build apps that work everywhere, even 30,000 feet in the air. Local AI is here: 💡Offline-First: No cloud, no latency, no "Department of Truth". 💻 Universal API: One codebase for iOS, Android, macOS, and Linux. 🔍 Multimodal: Understanding text, audio, and images without a server. If you can dream it, you can build it. The era of Stable Intelligence has begun. Start building:

QVAC

36,652 просмотров • 4 месяцев назад

The shift from Copilot to Autopilot is happening now. This is the Agentic Frontier, and while 82% of leaders are investing in it, most are not ready. Why? Because they're stuck in Phase 1 (AI Assistants) while the winners are already building for Phase 3 (Human-Led, Agent-Operated) operations. The gap between pilot and production is where most AI initiatives die. It's not a tech problem. It's a culture, governance, and data problem. But it's possible to cross this chasm. Enjoyed attending Microsoft Ignite with the EY team this past week. I learn about their "Client Zero" journey, 400,000+ people were enabled with operational AI tools. How? They didn't just deploy AI—they became AI-first. Here's the 3-step action plan to cross the frontier: 1️⃣ Mindset Shift: From prompting AI → delegating outcomes to AI. 2️⃣ Laser Focus: Target one painful, high-volume, low-creativity process to prove ROI and build momentum. 3️⃣ Build the Foundation: Create an AI-ready data estate and robust governance. You can't build a skyscraper on a swamp. Start small. Scale fast. I learn one think during my San Francisco visit. It is no longer the question of whether autonomous agents will reshape your industry, but when—and whether you'll lead or follow. Learn how >

The shift from Copilot to Autopilot is happening now. This is the Agentic Frontier, and while 82% of leaders are investing in it, most are not ready. Why? Because they're stuck in Phase 1 (AI Assistants) while the winners are already building for Phase 3 (Human-Led, Agent-Operated) operations. The gap between pilot and production is where most AI initiatives die. It's not a tech problem. It's a culture, governance, and data problem. But it's possible to cross this chasm. Enjoyed attending Microsoft Ignite with the EY team this past week. I learn about their "Client Zero" journey, 400,000+ people were enabled with operational AI tools. How? They didn't just deploy AI—they became AI-first. Here's the 3-step action plan to cross the frontier: 1️⃣ Mindset Shift: From prompting AI → delegating outcomes to AI. 2️⃣ Laser Focus: Target one painful, high-volume, low-creativity process to prove ROI and build momentum. 3️⃣ Build the Foundation: Create an AI-ready data estate and robust governance. You can't build a skyscraper on a swamp. Start small. Scale fast. I learn one think during my San Francisco visit. It is no longer the question of whether autonomous agents will reshape your industry, but when—and whether you'll lead or follow. Learn how >

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236,535 просмотров • 9 месяцев назад

What happens when millions of AI agents start negotiating, transacting, and delegating to one another? Nenad Tomasev joined our podcast with Hannah Fry to explore the rise of agentic economies – and how we can diversify agent decision-making to avoid AI groupthink. Timecodes: 00:00 Intro 1:07 Defining AI agents 4:44 Agentic exploration in science and research 15:46 Delegation between agents 22:46 Agentic security and traps 29:31 Building an agentic economy 33:22 Cognitive monoculture 36:29 Distributed intelligence

What happens when millions of AI agents start negotiating, transacting, and delegating to one another? Nenad Tomasev joined our podcast with Hannah Fry to explore the rise of agentic economies – and how we can diversify agent decision-making to avoid AI groupthink. Timecodes: 00:00 Intro 1:07 Defining AI agents 4:44 Agentic exploration in science and research 15:46 Delegation between agents 22:46 Agentic security and traps 29:31 Building an agentic economy 33:22 Cognitive monoculture 36:29 Distributed intelligence

Google DeepMind

117,010 просмотров • 2 месяцев назад

Dust ( helps companies build AI teammates that work across their organization. Founded by former OpenAI researcher Stanislas Polu (Stanislas Polu) and his team, the company has spent the last three years building AI for work while the capabilities of frontier models have advanced at breakneck speed. At Startup School Paris, YC's Mathilde Collin sat down with Stanislas to talk about what it takes to build alongside frontier AI labs, why staying model agnostic is a competitive advantage, how AI is changing the way we work, and why the best startups are built around a problem founders can't stop thinking about. 01:09 — From Stripe to OpenAI to Founder 01:40 — Why Stan Left OpenAI 02:49 — What Dust Actually Does 03:46 — What Work Looks Like in 3 Years 04:53 — Where the Thesis Was Right (and Wrong) 07:05 — Building Alongside Frontier Labs 09:15 — Model Agnostic as a Moat 10:49 — How Frontier Labs Changed Fundraising 12:19 — Raising Small on Purpose 14:39 — What Mistral Got Right 15:11 — Building in France 16:37 — What Happens When Frontier Labs Enter Your Market? 18:27 — The Margin Problem

Dust ( helps companies build AI teammates that work across their organization. Founded by former OpenAI researcher Stanislas Polu (Stanislas Polu) and his team, the company has spent the last three years building AI for work while the capabilities of frontier models have advanced at breakneck speed. At Startup School Paris, YC's Mathilde Collin sat down with Stanislas to talk about what it takes to build alongside frontier AI labs, why staying model agnostic is a competitive advantage, how AI is changing the way we work, and why the best startups are built around a problem founders can't stop thinking about. 01:09 — From Stripe to OpenAI to Founder 01:40 — Why Stan Left OpenAI 02:49 — What Dust Actually Does 03:46 — What Work Looks Like in 3 Years 04:53 — Where the Thesis Was Right (and Wrong) 07:05 — Building Alongside Frontier Labs 09:15 — Model Agnostic as a Moat 10:49 — How Frontier Labs Changed Fundraising 12:19 — Raising Small on Purpose 14:39 — What Mistral Got Right 15:11 — Building in France 16:37 — What Happens When Frontier Labs Enter Your Market? 18:27 — The Margin Problem

Y Combinator

54,342 просмотров • 1 месяц назад

What happens when PayPal and Kite AI come together to discuss the future of AI commerce? Our founders Chi Zhang and Scott Shi - e/acc recently hosted a very special episode of AI on AIR, with Jonathan Cordeau (VP, Enterprise Product Growth, PayPal) and Alan (Partner, M12 - Microsoft's Venture Fund; ex-Partner, PayPal Ventures), to explore how AI and payments are converging to shape the foundations of the agentic internet. Together, they unpacked: ☑️ How stablecoins are shaping agentic commerce ☑️ Why verifiable agent identities are key to building programmable trust ☑️ What the next era of machine-to-machine payments could look like ☑️ How Kite AI and PayPal are co-building the rails for an autonomous financial future Watch the full recording! 👇

What happens when PayPal and Kite AI come together to discuss the future of AI commerce? Our founders Chi Zhang and Scott Shi - e/acc recently hosted a very special episode of AI on AIR, with Jonathan Cordeau (VP, Enterprise Product Growth, PayPal) and Alan (Partner, M12 - Microsoft's Venture Fund; ex-Partner, PayPal Ventures), to explore how AI and payments are converging to shape the foundations of the agentic internet. Together, they unpacked: ☑️ How stablecoins are shaping agentic commerce ☑️ Why verifiable agent identities are key to building programmable trust ☑️ What the next era of machine-to-machine payments could look like ☑️ How Kite AI and PayPal are co-building the rails for an autonomous financial future Watch the full recording! 👇

KITE AI

28,810 просмотров • 10 месяцев назад

Most AI is built to replace humans. We're building AI to understand them. Introducing Atypica's Subjective World Model. A foundation for understanding how people express themselves, tell their stories, make decisions, and behave under real-world constraints. Not just what users say — but why they choose, hesitate, and act. It powers AI Research, AI Personas, AI Panels, and AI Interviews, helping teams turn user research from a quarterly project into a permanent capability. Watch the video to see how it works and what teams are already building with Atypica. Start to explore this AI-native consumer research platform from here:

Most AI is built to replace humans. We're building AI to understand them. Introducing Atypica's Subjective World Model. A foundation for understanding how people express themselves, tell their stories, make decisions, and behave under real-world constraints. Not just what users say — but why they choose, hesitate, and act. It powers AI Research, AI Personas, AI Panels, and AI Interviews, helping teams turn user research from a quarterly project into a permanent capability. Watch the video to see how it works and what teams are already building with Atypica. Start to explore this AI-native consumer research platform from here:

atypica.AI

28,221 просмотров • 1 месяц назад

Andrew Ng: “Agents are the most important trend in AI right now - 100% of my tasks already done by agents. in 3-6 months, we’ll all be building Graphs to orchestrate self-improving agents. No more prompting.” in a 20-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch. Worth more than a $500 agentic course. Watch this talk, then read how to become an agent orchestrator with graph engineering below.

Andrew Ng: “Agents are the most important trend in AI right now - 100% of my tasks already done by agents. in 3-6 months, we’ll all be building Graphs to orchestrate self-improving agents. No more prompting.” in a 20-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch. Worth more than a $500 agentic course. Watch this talk, then read how to become an agent orchestrator with graph engineering below.

Movez

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🚨Elon Musk:“In 6-12 months GrokBot will be the #1 tool for building agentic systems. In a year, 100% of code will be written by LLMs.” At SpaceXAI, more than 70% of engineers are already using GrokBot to build self-learning agentic systems. In a 40-minute talk, Elon sits down with SpaceXAI engineers and discusses what the future of AI engineering is really going to look like.This conversation is honestly worth more than 2 hours of any Stanford lecture on AI engineering. Watch it today, then go read the article below on how to build a full Grok bot agents team from scratch. Who’s ready to see the future of AI engineering from the people actually building it?

🚨Elon Musk:“In 6-12 months GrokBot will be the #1 tool for building agentic systems. In a year, 100% of code will be written by LLMs.” At SpaceXAI, more than 70% of engineers are already using GrokBot to build self-learning agentic systems. In a 40-minute talk, Elon sits down with SpaceXAI engineers and discusses what the future of AI engineering is really going to look like.This conversation is honestly worth more than 2 hours of any Stanford lecture on AI engineering. Watch it today, then go read the article below on how to build a full Grok bot agents team from scratch. Who’s ready to see the future of AI engineering from the people actually building it?

Hosna ⚖️ בניטה

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The QVAC SDK is the "LEGO block" of the next era of computing. It’s a modular, local-first framework designed to turn anything—from a simple robot to an industrial server—into a sovereign, autonomous mind. Why build with QVAC? Atomic Intelligence: AI as a raw material embedded directly into your hardware. No Cloud Dependency: 0 latency and total privacy. If the internet breaks, your world keeps thinking. Infinite Scale: A single API for local AI that runs on any device, anywhere. From a child’s toy to the fabric of the universe, if you can dream it, you can build it. Start building the future: 🚀

The QVAC SDK is the "LEGO block" of the next era of computing. It’s a modular, local-first framework designed to turn anything—from a simple robot to an industrial server—into a sovereign, autonomous mind. Why build with QVAC? Atomic Intelligence: AI as a raw material embedded directly into your hardware. No Cloud Dependency: 0 latency and total privacy. If the internet breaks, your world keeps thinking. Infinite Scale: A single API for local AI that runs on any device, anywhere. From a child’s toy to the fabric of the universe, if you can dream it, you can build it. Start building the future: 🚀

QVAC

4,707,376 просмотров • 4 месяцев назад

As agentic automation helps developers get more done, the role is evolving toward higher-level decisions about what to build, how systems should work, and where taste and creativity matter most. Databricks Co-founder Patrick Wendell, OpenClaw creator Peter Steinberger 🦞, and Codex engineering lead Tibo discuss what that shift means for enterprises building, governing, and scaling fleets of AI agents in production. Watch the full conversation:

As agentic automation helps developers get more done, the role is evolving toward higher-level decisions about what to build, how systems should work, and where taste and creativity matter most. Databricks Co-founder Patrick Wendell, OpenClaw creator Peter Steinberger 🦞, and Codex engineering lead Tibo discuss what that shift means for enterprises building, governing, and scaling fleets of AI agents in production. Watch the full conversation:

Databricks

13,419 просмотров • 24 дней назад

Andrew Ng: “AI agents are doing almost 100% of my tasks now - the hype has exceeded my expectations. in 4-6 months, we’ll all be building graphs to orchestrate self-improving agents. No more prompting.” In a 20-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch. Worth more than a $500 agentic course. Watch this video, then read the article below on how to become a graph architect.

Andrew Ng: “AI agents are doing almost 100% of my tasks now - the hype has exceeded my expectations. in 4-6 months, we’ll all be building graphs to orchestrate self-improving agents. No more prompting.” In a 20-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch. Worth more than a $500 agentic course. Watch this video, then read the article below on how to become a graph architect.

Movez

278,459 просмотров • 1 месяц назад

What happens when AI connects an entire global organization? 🌏 Padma Chukka, SVP of Strategic Partnerships at Arrive, explains how they used the Gemini Enterprise Agent Platform to build "Aria," shrinking RFP times from a week to just 4–6 hours. Watch how they made it happen →

What happens when AI connects an entire global organization? 🌏 Padma Chukka, SVP of Strategic Partnerships at Arrive, explains how they used the Gemini Enterprise Agent Platform to build "Aria," shrinking RFP times from a week to just 4–6 hours. Watch how they made it happen →

Google Workspace

13,060 просмотров • 1 месяц назад

Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth

Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth

Marktechpost AI Dev News ⚡

31,551 просмотров • 8 месяцев назад

Amazon AI engineer just explained how to build agentic loops from scratch in under 10-minutes. this is one of the clearest explanations of AI agentic loops you’ll find anywhere. Loop + model + agent + hooks + MCP = an autonomous, self-improving system. People are paying $500 for courses that teach less than this. Watch it, then read the step-by-step guide below on building loops for your own agents.

Amazon AI engineer just explained how to build agentic loops from scratch in under 10-minutes. this is one of the clearest explanations of AI agentic loops you’ll find anywhere. Loop + model + agent + hooks + MCP = an autonomous, self-improving system. People are paying $500 for courses that teach less than this. Watch it, then read the step-by-step guide below on building loops for your own agents.

Codez

26,868 просмотров • 2 месяцев назад

New short course: Practical Multi AI Agents and Advanced Use Cases with crewAI. Learn to build and deploy advanced agent-based systems in real applications in this course, created with CrewAI and taught by its founder, João Moura! (Disclosure: I've made a small seed investment in CrewAI.) In this course, you’ll learn how to create advanced agent-based apps that use external tools, do performance testing, can be trained with human feedback, and perform multiple tasks with different large language models. You will build several practical agentic apps that provide real business value, such as an automated project planning system, lead scoring and engagement pipeline, customer support data analysis, and a robust content creation system. In detail, you will learn how to: - Create these multi-agent systems with the building blocks of tasks, agents, and crews, along with the different things that make them work, such as caching, memory, and guardrails. - Integrate your multi-agent application with internal and external systems. - Connect multiple agents in complex setups, including parallel, sequential, and hybrid configurations, and create flows involving multiple agentic applications working together. - Test your agentic workflow and train it using human feedback to optimize its performance for better and more consistent results. - Work with multiple LLMs in your multi-agent system, using the appropriate model sizes and providers to fit each agent’s specific task. - Start a project from scratch in your environment and prepare it for deployment. You’ll also learn from an interview between João and Jacob Wilson, the Commercial GenAI Principal at PwC , in which they discuss deploying agentic workflows in real industry use cases. By the end of this course, you will be equipped to start building custom multi-agentic systems for your work. Please sign up here!

New short course: Practical Multi AI Agents and Advanced Use Cases with crewAI. Learn to build and deploy advanced agent-based systems in real applications in this course, created with CrewAI and taught by its founder, João Moura! (Disclosure: I've made a small seed investment in CrewAI.) In this course, you’ll learn how to create advanced agent-based apps that use external tools, do performance testing, can be trained with human feedback, and perform multiple tasks with different large language models. You will build several practical agentic apps that provide real business value, such as an automated project planning system, lead scoring and engagement pipeline, customer support data analysis, and a robust content creation system. In detail, you will learn how to: - Create these multi-agent systems with the building blocks of tasks, agents, and crews, along with the different things that make them work, such as caching, memory, and guardrails. - Integrate your multi-agent application with internal and external systems. - Connect multiple agents in complex setups, including parallel, sequential, and hybrid configurations, and create flows involving multiple agentic applications working together. - Test your agentic workflow and train it using human feedback to optimize its performance for better and more consistent results. - Work with multiple LLMs in your multi-agent system, using the appropriate model sizes and providers to fit each agent’s specific task. - Start a project from scratch in your environment and prepare it for deployment. You’ll also learn from an interview between João and Jacob Wilson, the Commercial GenAI Principal at PwC , in which they discuss deploying agentic workflows in real industry use cases. By the end of this course, you will be equipped to start building custom multi-agentic systems for your work. Please sign up here!

Andrew Ng

341,204 просмотров • 1 год назад