正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

A 35B language model running on an iPhone using only 1–2.5 GB of peak memory. No cloud. No remote server. No desktop GPU. Today, we’re open-sourcing Edge0 — a framework for running large AI models fully on-device.

Samuel Zeng

3,330 subscribers

550,682 次观看 • 1 天前 •via X (Twitter)

科学技术教育新闻政治

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

What happens when you combine voice, vision, and reasoning on-device? 🤔 Gemma 4 + a vision-language agent (VLA) running on NVIDIA Jetson Orin Nano shows how compact hardware can now handle real-world AI tasks using today’s open models—no cloud required. Get started:

What happens when you combine voice, vision, and reasoning on-device? 🤔 Gemma 4 + a vision-language agent (VLA) running on NVIDIA Jetson Orin Nano shows how compact hardware can now handle real-world AI tasks using today’s open models—no cloud required. Get started:

NVIDIA Robotics

25,655 次观看 • 4 个月前

Sheepy-T: A fully open-source instruction-tuned language model based on GPT-J running locally on iPhone 14. Reply for beta access via TestFlight.

Sheepy-T: A fully open-source instruction-tuned language model based on GPT-J running locally on iPhone 14. Reply for beta access via TestFlight.

Kevin Kwok

102,369 次观看 • 3 年前

just generated an ai video on my mac no cloud, no server bill last year this needed a gpu cluster

just generated an ai video on my mac no cloud, no server bill last year this needed a gpu cluster

Igor Tarasenko

427,139 次观看 • 1 年前

🚨 Claude Code just got REPLACED overnight… for $0 An open-source project is now running a 122B model locally on your MacBook 🤯 No API fees. No cloud. No limits. Just raw power on your own machine. 1 command install. Double-click to launch. If this works at scale… it’s game over for paid AI tools. GitHub ↓

🚨 Claude Code just got REPLACED overnight… for $0 An open-source project is now running a 122B model locally on your MacBook 🤯 No API fees. No cloud. No limits. Just raw power on your own machine. 1 command install. Double-click to launch. If this works at scale… it’s game over for paid AI tools. GitHub ↓

Shruti Codes

40,749 次观看 • 5 个月前

Qwen 3.6 35B running at over 100 tokens per second on my $5,399 MacBook Pro M5 Max. This is the best local AI model I have ever run. 128GB of unified memory. No cloud. No API costs. No rate limits. Just raw local inference at speeds I didn't think were possible on a laptop. This model is more intelligent than GPT 5 on benchmarks. Running locally. On a MacBook. For free after the hardware cost. I said local AI would never compete with frontier. I'm starting to rethink that. The gap is closing faster than anyone expected.

Qwen 3.6 35B running at over 100 tokens per second on my $5,399 MacBook Pro M5 Max. This is the best local AI model I have ever run. 128GB of unified memory. No cloud. No API costs. No rate limits. Just raw local inference at speeds I didn't think were possible on a laptop. This model is more intelligent than GPT 5 on benchmarks. Running locally. On a MacBook. For free after the hardware cost. I said local AI would never compete with frontier. I'm starting to rethink that. The gap is closing faster than anyone expected.

BridgeMind

62,800 次观看 • 3 个月前

China just open sourced an embodied AI model series. and the demo is wild. They ripped the network cable out of a robot dog mid run. it kept tracking like nothing happened. No cloud. no wifi. a 0.9B model running entirely on the dog. This is MiniCPM-Robot 🧵

China just open sourced an embodied AI model series. and the demo is wild. They ripped the network cable out of a robot dog mid run. it kept tracking like nothing happened. No cloud. no wifi. a 0.9B model running entirely on the dog. This is MiniCPM-Robot 🧵

Clara Bennett

13,013 次观看 • 1 个月前

This guy fit a barista AI inside an $8 ESP32. Ask it an espresso question over USB. It answers on a tiny OLED. Fully local. No cloud. No GPU. Tiny specialized AI is getting interesting. Repo below.

This guy fit a barista AI inside an $8 ESP32. Ask it an espresso question over USB. It answers on a tiny OLED. Fully local. No cloud. No GPU. Tiny specialized AI is getting interesting. Repo below.

Min Choi

51,718 次观看 • 1 个月前

Run KiloCode on open models powered by Atomic Chat Kilo is trusted by 3M+ developers. Code, debug, and build entirely on your device — no cloud, fully private, free and open-source with atomic.chat local AI provider

Run KiloCode on open models powered by Atomic Chat Kilo is trusted by 3M+ developers. Code, debug, and build entirely on your device — no cloud, fully private, free and open-source with atomic.chat local AI provider

atomic.chat

11,990 次观看 • 2 个月前

I taught this robot duck to backflip trained entirely on my MacBook. Today I'm open-sourcing the lab behind it. In this video I teach it a brand-new trick, a headstand, from scratch live in the browser, just by asking for it. No GPU. No cloud. Repo below 👇

jonathanhawkins

13,456 次观看 • 9 天前

“BRIAN, IT CANT BE DONE” Done: A low resolution holographic of the entire corpus of online information. A fully local AI with no Internet Connection running on 4 models back, iPhones. Next up YOUR AI trained on YOUR local data, to become an active part of your life.

“BRIAN, IT CANT BE DONE” Done: A low resolution holographic of the entire corpus of online information. A fully local AI with no Internet Connection running on 4 models back, iPhones. Next up YOUR AI trained on YOUR local data, to become an active part of your life.

Brian Roemmele

269,226 次观看 • 11 个月前

we're turning University of Waterloo into a supercomputer! arceus is a cross-device distributed compute network for training large models, using model/tensor/pipeline parallelism. you can train anything, from deep neural networks to language models on the network. oss & deployment soon!

we're turning University of Waterloo into a supercomputer! arceus is a cross-device distributed compute network for training large models, using model/tensor/pipeline parallelism. you can train anything, from deep neural networks to language models on the network. oss & deployment soon!

rajan agarwal

35,720 次观看 • 1 年前

Watch Marco Chiappetta, Head of QVAC, cloning his voice with nothing but local AI, and then generating speech in any language he wants. No cloud, no upload, the model runs on the device. Watch it below.

Watch Marco Chiappetta, Head of QVAC, cloning his voice with nothing but local AI, and then generating speech in any language he wants. No cloud, no upload, the model runs on the device. Watch it below.

QVAC

8,882,357 次观看 • 1 个月前

What Lisa Su actually held on stage: A mini PC the size of a lunchbox running Qwen3-235B locally, with no cloud and no discrete GPU Inside: the Ryzen AI Max+ 395, 128GB unified memory, 110GB usable as VRAM on Linux The first x86 chip that handles 200+ billion parameters on a single die AMD claims it beats the RTX 5080 by several times on memory-bound models — because the 5080 simply cannot fit them $1,400 to $2,500 once. cloud bills run $200 to $400 a month It pays for itself in a few months, then costs nothing per request This is not a faster GPU. it is the first real argument that your AI does not belong in someone else's data center

What Lisa Su actually held on stage: A mini PC the size of a lunchbox running Qwen3-235B locally, with no cloud and no discrete GPU Inside: the Ryzen AI Max+ 395, 128GB unified memory, 110GB usable as VRAM on Linux The first x86 chip that handles 200+ billion parameters on a single die AMD claims it beats the RTX 5080 by several times on memory-bound models — because the 5080 simply cannot fit them $1,400 to $2,500 once. cloud bills run $200 to $400 a month It pays for itself in a few months, then costs nothing per request This is not a faster GPU. it is the first real argument that your AI does not belong in someone else's data center

plutos

1,237,742 次观看 • 2 个月前

AMD on local AI: "this is the smallest AI development system in the world, capable of running models up to 200 billion parameters locally, not connected to anything" 128GB of unified memory shared by CPU, GPU, and NPU fits in your hand. Runs a model larger than GPT-3 with no internet $3,999 once. roughly $16 a month in power Cloud equivalent: up to $750 a month The question was never whether local AI could compete on power It was whether it could compete on price. Now it does

AMD on local AI: "this is the smallest AI development system in the world, capable of running models up to 200 billion parameters locally, not connected to anything" 128GB of unified memory shared by CPU, GPU, and NPU fits in your hand. Runs a model larger than GPT-3 with no internet $3,999 once. roughly $16 a month in power Cloud equivalent: up to $750 a month The question was never whether local AI could compete on power It was whether it could compete on price. Now it does

plutos

152,392 次观看 • 2 个月前

You imagine it. We create it. 🎨 Introducing #PixelStudio, a first-of-its-kind image generator on #Pixel9 powered by an on-device diffusion model¹ running on Tensor G4 and our Imagen 3 text-to-image model in the cloud.

You imagine it. We create it. 🎨 Introducing #PixelStudio, a first-of-its-kind image generator on #Pixel9 powered by an on-device diffusion model¹ running on Tensor G4 and our Imagen 3 text-to-image model in the cloud.

Made by Google

28,283 次观看 • 2 年前

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 ↓

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 次观看 • 4 个月前

I thought I needed a powerful GPU to run serious AI locally. I was completely wrong. Late 2025, Ollama quietly launched something that changed everything. They built a cloud inference layer running on NVIDIA's Blackwell architecture, the most powerful GPU hardware available today. No GPU on your desk required. No expensive API subscription. No complex setup. Just one command and you're running Kimi K2.5, a 1 trillion parameter open-source model, completely free. I connected it to OpenClaw, which links my phone's messaging apps to the AI agent running at home. I sent a message from WhatsApp. My machine picked it up, ran the task, and sent me back the result. It felt like magic. It's just good engineering. Save this post, you'll want this when you're building your first workflow. Want the SOP? DM me.

I thought I needed a powerful GPU to run serious AI locally. I was completely wrong. Late 2025, Ollama quietly launched something that changed everything. They built a cloud inference layer running on NVIDIA's Blackwell architecture, the most powerful GPU hardware available today. No GPU on your desk required. No expensive API subscription. No complex setup. Just one command and you're running Kimi K2.5, a 1 trillion parameter open-source model, completely free. I connected it to OpenClaw, which links my phone's messaging apps to the AI agent running at home. I sent a message from WhatsApp. My machine picked it up, ran the task, and sent me back the result. It felt like magic. It's just good engineering. Save this post, you'll want this when you're building your first workflow. Want the SOP? DM me.

Julian Goldie SEO

11,967 次观看 • 5 个月前

We deployed a fully private AI agent on NuNet in under 5 minutes 🚀 OpenClaw🦞 running Qwen through ollama , one of the hottest open source model families right now, entirely on decentralized compute. No cloud. No API keys. No data leaving the machine. This is what private AI looks like when you actually build it instead of just talking about it. Your model. Your hardware. Your rules. Full walkthrough showing exactly how it works: What should we deploy next?

We deployed a fully private AI agent on NuNet in under 5 minutes 🚀 OpenClaw🦞 running Qwen through ollama , one of the hottest open source model families right now, entirely on decentralized compute. No cloud. No API keys. No data leaving the machine. This is what private AI looks like when you actually build it instead of just talking about it. Your model. Your hardware. Your rules. Full walkthrough showing exactly how it works: What should we deploy next?

NuNet 🌐

87,626 次观看 • 5 个月前

Here's a quick demo of an agentic loop running offline entirely on-device on Apple Watch Series 9. --- We have been spearheading small models and one of the biggest unlock it provides for consumer is having intelligence right at their fingertips, no cloud-round trip = faster, cheaper, private, more control. This also unlocks a whole suite of new use-cases with product specific models - or models built specifically for and shipped alongside an app. We now have full expertise on the entire on-device Apple Intelligence stack. We have pioneered training and running models with Apple native APIs on iPhones, Macs and Watches. Already working with Apple DR team and some of the biggest wearable brands exploring running AI on different form factors. If you're a team exploring this domain, we are here to help. Reach out -> follow Conscious Engines • Studio for consumer AI

Here's a quick demo of an agentic loop running offline entirely on-device on Apple Watch Series 9. --- We have been spearheading small models and one of the biggest unlock it provides for consumer is having intelligence right at their fingertips, no cloud-round trip = faster, cheaper, private, more control. This also unlocks a whole suite of new use-cases with product specific models - or models built specifically for and shipped alongside an app. We now have full expertise on the entire on-device Apple Intelligence stack. We have pioneered training and running models with Apple native APIs on iPhones, Macs and Watches. Already working with Apple DR team and some of the biggest wearable brands exploring running AI on different form factors. If you're a team exploring this domain, we are here to help. Reach out -> follow Conscious Engines • Studio for consumer AI

Kautuk | Conscious Engines

16,692 次观看 • 15 天前