Загрузка видео...

Не удалось загрузить видео

На главную

Advice for AI engineers 💡 Browser control is possible with a Small Model, like LFM2-350M by Liquid AI . Here's a 60-minute deep dive on how to fine-tune with RL and OpenEnv by Hugging Face Enjoy ↓

paulabartabajo_'s profile picture

Pau Labarta Bajo

70,161 subscribers

16,169 просмотров • 3 месяцев назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Advice for AI engineers 💡 A local AI assistant is just a while loop, an LLM and a set of tools. Here's a step-by-step lesson on how to build one from scratch with Liquid AI LFM2-24B-A2B running on llama.cpp. No cloud APIs. Enjoy ↓
57:09

Advice for AI engineers 💡 A local AI assistant is just a while loop, an LLM and a set of tools. Here's a step-by-step lesson on how to build one from scratch with Liquid AI LFM2-24B-A2B running on llama.cpp. No cloud APIs. Enjoy ↓

Pau Labarta Bajo

15,463 просмотров • 3 месяцев назад

Advice for AI engineers 💡 A small Visual Language Model fine-tuned on your custom dataset is as accurate as GPT-5... ... and costs 50 times less. For example, LFM2.5-VL-1.6B by Liquid AI running locally at full speed with llama.cpp ↓
0:24

Advice for AI engineers 💡 A small Visual Language Model fine-tuned on your custom dataset is as accurate as GPT-5... ... and costs 50 times less. For example, LFM2.5-VL-1.6B by Liquid AI running locally at full speed with llama.cpp ↓

Pau Labarta Bajo

80,258 просмотров • 6 месяцев назад

Advice for AI engineers 💡 Small Audio LMs + Tool-calling LMs running locally are as fast as cloud speech APIs... ... but cost $0 per request and keep your data private. For example, LFM2.5-Audio-1.5B + LFM2-1.2B-Tool by Liquid AI ↓
0:37

Advice for AI engineers 💡 Small Audio LMs + Tool-calling LMs running locally are as fast as cloud speech APIs... ... but cost $0 per request and keep your data private. For example, LFM2.5-Audio-1.5B + LFM2-1.2B-Tool by Liquid AI ↓

Pau Labarta Bajo

38,504 просмотров • 6 месяцев назад

If you want to learn AI from the experts, keep reading. 💡 Together with UCL, we made a free AI Research Foundations curriculum – available now on Google Skills. With lessons from a Gemini Lead like Oriol Vinyals, you'll explore how to code better, fine-tune an AI model and more. →
0:35

If you want to learn AI from the experts, keep reading. 💡 Together with UCL, we made a free AI Research Foundations curriculum – available now on Google Skills. With lessons from a Gemini Lead like Oriol Vinyals, you'll explore how to code better, fine-tune an AI model and more. →

Google DeepMind

287,147 просмотров • 9 месяцев назад

I found an AI browser that is actually awesome FlowithOS is a web browser COMPLETELY powered by AI You give it tasks, the agents work for you in the background It's like an army of AI agents working for you 24/7 Here's a guide on how it works and how you can get started today
12:09

I found an AI browser that is actually awesome FlowithOS is a web browser COMPLETELY powered by AI You give it tasks, the agents work for you in the background It's like an army of AI agents working for you 24/7 Here's a guide on how it works and how you can get started today

Alex Finn

25,490 просмотров • 7 месяцев назад

How did a tiny, scrappy team build one of the most powerful AI voice models? In a deep dive with Sesame CTO Ankit Kumar and a16z's Anjney Midha, we explore how Sesame is pushing the boundaries of AI conversation, why it open-sourced its speech generation model, and the power of small teams to outdo much larger AI labs on product focus. A part of their secret: a relentless focus on real-time, natural conversations over raw intelligence, and a deep commitment to voice, personality, and user experience. By opening up its speech generation model, Sesame is paving the way for even more breakthroughs in AI-native conversation 👇
1:04

How did a tiny, scrappy team build one of the most powerful AI voice models? In a deep dive with Sesame CTO Ankit Kumar and a16z's Anjney Midha, we explore how Sesame is pushing the boundaries of AI conversation, why it open-sourced its speech generation model, and the power of small teams to outdo much larger AI labs on product focus. A part of their secret: a relentless focus on real-time, natural conversations over raw intelligence, and a deep commitment to voice, personality, and user experience. By opening up its speech generation model, Sesame is paving the way for even more breakthroughs in AI-native conversation 👇

a16z

29,930 просмотров • 1 год назад

With Harvard University, we built a ‘virtual rodent’ powered by AI to help us better understand how the brain controls movement. 🧠 With deep RL, it learned to operate a biomechanically accurate rat model - allowing us to compare real & virtual neural activity. →
0:38

With Harvard University, we built a ‘virtual rodent’ powered by AI to help us better understand how the brain controls movement. 🧠 With deep RL, it learned to operate a biomechanically accurate rat model - allowing us to compare real & virtual neural activity. →

Google DeepMind

229,082 просмотров • 2 лет назад

oh my.. this shouldn't be possible a 1B model that runs inside your browser, beats every model its size, and comes with its own desktop pet. MiniCPM-5 1B just changed the game for on-device AI. here's everything you need to know 🧵
0:32

oh my.. this shouldn't be possible a 1B model that runs inside your browser, beats every model its size, and comes with its own desktop pet. MiniCPM-5 1B just changed the game for on-device AI. here's everything you need to know 🧵

Muhammad Ayan

62,050 просмотров • 2 месяцев назад

Hands-on edge AI with robotics 🤖 Dominic Pajak prototyped an on-device AI app for Hugging Face Pollen Robotics Reachy Mini. Running locally on Arm-based Raspberry Pi 5, it shows how low-latency AI enables responsive interaction. Sometimes the best way to understand what's possible with AI is to build it! Code linked in comments 💻
0:41

Hands-on edge AI with robotics 🤖 Dominic Pajak prototyped an on-device AI app for Hugging Face Pollen Robotics Reachy Mini. Running locally on Arm-based Raspberry Pi 5, it shows how low-latency AI enables responsive interaction. Sometimes the best way to understand what's possible with AI is to build it! Code linked in comments 💻

Arm Software Developers

18,051 просмотров • 7 месяцев назад

Hugging Face has acquired a French robotics startup, Pollen Robotics, for an undisclosed amount. The Reachy 2 robot, developed by Pollen, is an open-source and VR-compatible bimanual robot for advancing embodied AI, available to order at $70K. Hugging Face, the leading platform for sharing and fine-tuning LLMs, is also building LeRobot - a platform for providing models, tools, and datasets for robotics AI. Hugging Face was valued at $4.5B in the last round.
2:22

Hugging Face has acquired a French robotics startup, Pollen Robotics, for an undisclosed amount. The Reachy 2 robot, developed by Pollen, is an open-source and VR-compatible bimanual robot for advancing embodied AI, available to order at $70K. Hugging Face, the leading platform for sharing and fine-tuning LLMs, is also building LeRobot - a platform for providing models, tools, and datasets for robotics AI. Hugging Face was valued at $4.5B in the last round.

The Humanoid Hub

108,683 просмотров • 1 год назад

Excited to introduce DeepSeek R1 fine-tuning with Firecrawl 🔥 Learn how to fine-tune DeepSeek's R1 model on custom instruction datasets generated by Firecrawl's web data extraction. Train your own AI expert to answer domain-specific questions about your website!
0:36

Excited to introduce DeepSeek R1 fine-tuning with Firecrawl 🔥 Learn how to fine-tune DeepSeek's R1 model on custom instruction datasets generated by Firecrawl's web data extraction. Train your own AI expert to answer domain-specific questions about your website!

Eric Ciarla (hiring)

40,189 просмотров • 1 год назад

We developed an RL method for fine-tuning our models for precise tasks in just a few hours or even minutes. Instead of training the whole model, we add an “RL token” output to π-0.6, our latest model, which is used by a tiny actor and critic to learn quickly with RL.
2:15

We developed an RL method for fine-tuning our models for precise tasks in just a few hours or even minutes. Instead of training the whole model, we add an “RL token” output to π-0.6, our latest model, which is used by a tiny actor and critic to learn quickly with RL.

Physical Intelligence

438,768 просмотров • 4 месяцев назад

Exciting update for AI developers! The Hugging Face Hub is now more natively integrated into Google Cloud Vertex AI Model Garden. Search through thousands of open Generative AI models from Hugging Face models & deploy them with one click to Vertex AI or GKE. 🤯 What's new: 🔎 Browse and search thousands of Hugging Face models directly within the Vertex AI Model Garden and filter based on what is currently trending in the community. 🚀 Accelerate your AI projects by leveraging readily available one-click deploy your model to Vertex AI or Google Kubernetes Engine (GKE). ⭐️ Featuring popular open models from BlackForestLabsAI - Unofficial FLUX.1, AI at Meta Llama 3.1, Mistral AI, Google DeepMind Gemma, and countless others. Get Started:
0:38

Exciting update for AI developers! The Hugging Face Hub is now more natively integrated into Google Cloud Vertex AI Model Garden. Search through thousands of open Generative AI models from Hugging Face models & deploy them with one click to Vertex AI or GKE. 🤯 What's new: 🔎 Browse and search thousands of Hugging Face models directly within the Vertex AI Model Garden and filter based on what is currently trending in the community. 🚀 Accelerate your AI projects by leveraging readily available one-click deploy your model to Vertex AI or Google Kubernetes Engine (GKE). ⭐️ Featuring popular open models from BlackForestLabsAI - Unofficial FLUX.1, AI at Meta Llama 3.1, Mistral AI, Google DeepMind Gemma, and countless others. Get Started:

Philipp Schmid

34,754 просмотров • 1 год назад

Announcing the Open Model Series: a new series on open source AI models, with merve of Hugging Face. Hugging Face is the open model hub: it hosts model weights, datasets, evals, & demo apps, and maintains the open-source libraries (like transformers) used to run and train them. I think of it like GitHub, but for AI models. You can download open models and run them on your own machines. In this series we'll cover what open source and open weight models are, how they work, how to run them yourself, and why they're important. By the way - this video is edited entirely with Claude! I can make a tutorial on how I did it. If there's a question you want answered about open models, leave it in the comments. We will read them all. Episode 1 is out soon.
0:26

Announcing the Open Model Series: a new series on open source AI models, with merve of Hugging Face. Hugging Face is the open model hub: it hosts model weights, datasets, evals, & demo apps, and maintains the open-source libraries (like transformers) used to run and train them. I think of it like GitHub, but for AI models. You can download open models and run them on your own machines. In this series we'll cover what open source and open weight models are, how they work, how to run them yourself, and why they're important. By the way - this video is edited entirely with Claude! I can make a tutorial on how I did it. If there's a question you want answered about open models, leave it in the comments. We will read them all. Episode 1 is out soon.

Harper Carroll

30,392 просмотров • 7 дней назад

here's a 39-second tutorial on how to generate meshes with AI (for free!)
0:39

here's a 39-second tutorial on how to generate meshes with AI (for free!)

dylan

26,727 просмотров • 1 год назад