Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

Finally found a meaningful scenario for running LLM in the browser, peering into the internals of LLM to see what's really happening inside

Broooooklyn

7,257 subscribers

46,339 просмотров • 2 месяцев назад •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

INTRODUCING Notte Building the agentic internet with the strongest web browser for LLM agents. We transform ANY webpage into structured text, enabling better web understanding and navigation. Plug any LLM to to build your own AI agent

INTRODUCING Notte Building the agentic internet with the strongest web browser for LLM agents. We transform ANY webpage into structured text, enabling better web understanding and navigation. Plug any LLM to to build your own AI agent

Notte

225,219 просмотров • 1 год назад

Incredible things happening in the LLM psychosis community

Incredible things happening in the LLM psychosis community

Justine Moore

573,468 просмотров • 8 месяцев назад

JSX Tool (@jsxtool) is an in-browser IDE for building React UIs. Click on any element in the browser to jump straight to the relevant line of code and edit it yourself or provide precise context to an LLM to make updates.

JSX Tool (@jsxtool) is an in-browser IDE for building React UIs. Click on any element in the browser to jump straight to the relevant line of code and edit it yourself or provide precise context to an LLM to make updates.

Y Combinator

49,755 просмотров • 9 месяцев назад

The harness can make a difference in AI for CAD. Below: same LLM (Opus 4.8) with different harnesses. Looking forward to see more progress without waiting for a new LLM version :) (Good job Paul Fremantle)

The harness can make a difference in AI for CAD. Below: same LLM (Opus 4.8) with different harnesses. Looking forward to see more progress without waiting for a new LLM version :) (Good job Paul Fremantle)

Michael Rabinovich

22,413 просмотров • 2 месяцев назад

Free Mode is live in Higgsfield Supercomputer. The LLM inside is now free to use for brainstorming, prompt writing, scripting, research, and project planning. Credits kick in only when you generate. A Supercomputer-level LLM, yours to use.

Free Mode is live in Higgsfield Supercomputer. The LLM inside is now free to use for brainstorming, prompt writing, scripting, research, and project planning. Credits kick in only when you generate. A Supercomputer-level LLM, yours to use.

Higgsfield AI 🧩

264,206 просмотров • 1 месяц назад

stress_test.mp4 c++ rewrite finished. 1.5 months. ~6 billion LLM tokens spent through codex runs at 60 fps in the browser (~120-180 uncapped). every tree and sprite and texture is LLM authored.

stress_test.mp4 c++ rewrite finished. 1.5 months. ~6 billion LLM tokens spent through codex runs at 60 fps in the browser (~120-180 uncapped). every tree and sprite and texture is LLM authored.

scaredofboobs🪲

53,733 просмотров • 2 месяцев назад

Today we're launching 2.0, the in-browser Postgres sandbox with AI assistance - now with bring-your-own-LLM 🚀

Today we're launching 2.0, the in-browser Postgres sandbox with AI assistance - now with bring-your-own-LLM 🚀

Greg Richardson

17,982 просмотров • 1 год назад

My friend applied to 250 tech jobs in two years. No MIT. No Stanford. No PhD. Last month Anthropic offered him $750,000. I asked him how he broke in from zero. He sent me the exact video that got him in. Andrej Karpathy's 4-hour course on "How to build a full LLM from scratch." Anthropic's own researcher gives up the exact playbook behind building LLMs like ChatGPT & Claude. I watched it last night. Halfway through, I realized I could break into an AI lab in months, not years. Bookmark this and read the article below. • 00:00 - LLMs as new OS • 40:58 - LLM tokenization architecture • 53:22 - LLM neural network internals • 1:04:20 - LLM pretraining • 3:21:37 - LLM RLHF & DeepSeek R1

My friend applied to 250 tech jobs in two years. No MIT. No Stanford. No PhD. Last month Anthropic offered him $750,000. I asked him how he broke in from zero. He sent me the exact video that got him in. Andrej Karpathy's 4-hour course on "How to build a full LLM from scratch." Anthropic's own researcher gives up the exact playbook behind building LLMs like ChatGPT & Claude. I watched it last night. Halfway through, I realized I could break into an AI lab in months, not years. Bookmark this and read the article below. • 00:00 - LLMs as new OS • 40:58 - LLM tokenization architecture • 53:22 - LLM neural network internals • 1:04:20 - LLM pretraining • 3:21:37 - LLM RLHF & DeepSeek R1

Roan

123,977 просмотров • 29 дней назад

Project #2: LLM Visualization So I created a web-page to visualize a small LLM, of the sort that's behind ChatGPT. Rendered in 3D, it shows all the steps to run a single token inference. (link in bio)

Project #2: LLM Visualization So I created a web-page to visualize a small LLM, of the sort that's behind ChatGPT. Rendered in 3D, it shows all the steps to run a single token inference. (link in bio)

Brendan Bycroft

1,202,301 просмотров • 2 лет назад

See how the Box MCP server turns Box into a LLM-ready toolbox. In this demo, we showcase @Cursor_ai to fast track AI-powered content workflows.

See how the Box MCP server turns Box into a LLM-ready toolbox. In this demo, we showcase @Cursor_ai to fast track AI-powered content workflows.

Box

292,769 просмотров • 1 год назад

Stories have shapes: a comedy rises toward joy; a tragedy falls into loss. Inside an LLM, that’s visible more literally: as an LLM reads a story, its internal activations trace a wandering path that reflects the model’s sense of what kind of story it is reading. (1/5)

Stories have shapes: a comedy rises toward joy; a tragedy falls into loss. Inside an LLM, that’s visible more literally: as an LLM reads a story, its internal activations trace a wandering path that reflects the model’s sense of what kind of story it is reading. (1/5)

Goodfire

104,799 просмотров • 2 месяцев назад

We've built the best in house observability for Stagehand 🔭 Get inference time, token usage, LLM output, and more on the new dashboard. No more black box, see everything behind the scenes. See for yourself, get started with npx create-browser-app 🤘

We've built the best in house observability for Stagehand 🔭 Get inference time, token usage, LLM output, and more on the new dashboard. No more black box, see everything behind the scenes. See for yourself, get started with npx create-browser-app 🤘

Stagehand

10,887 просмотров • 1 год назад

Second place: Ambien by give me a sec A daydreaming agent running inside Hermes Agent that samples a curated Obsidian corpus for resonant idea collisions and synthesizes them into published essays, leveraging the harness for iterative voice calibration that keeps the prose from reading like an LLM.

Second place: Ambien by give me a sec A daydreaming agent running inside Hermes Agent that samples a curated Obsidian corpus for resonant idea collisions and synthesizes them into published essays, leveraging the harness for iterative voice calibration that keeps the prose from reading like an LLM.

Nous Research

26,904 просмотров • 3 месяцев назад

i'm a little sick of chatgpt giving me obviously broken code i've found a "micro agent" approach to LLM code generation can work much better the LLM first generates a *test*, and then enters a loop where it generates and iterates on the code until the tests pass source below

i'm a little sick of chatgpt giving me obviously broken code i've found a "micro agent" approach to LLM code generation can work much better the LLM first generates a test, and then enters a loop where it generates and iterates on the code until the tests pass source below

Steve (Builder.io)

544,212 просмотров • 2 лет назад

Jupyter Agents - LLMs running data analysis directly in a notebook! The agent can load data, execute code, plot results and following your guidance and ideas! A very natural way to collaborate with an LLM over data and it's just scratching the surface of what's possible soon!

Jupyter Agents - LLMs running data analysis directly in a notebook! The agent can load data, execute code, plot results and following your guidance and ideas! A very natural way to collaborate with an LLM over data and it's just scratching the surface of what's possible soon!

Leandro von Werra

200,291 просмотров • 1 год назад

Another example of the multiple TTS parallel pipelines pattern. Here's a voice AI agent that speaks both English and Arabic, using a specific model/voice for each language. These are PlayAI voices. The STT, TTS, and LLM inference is all running on Groq Inc. (The LLM is LLama 4 Maverick.)

Another example of the multiple TTS parallel pipelines pattern. Here's a voice AI agent that speaks both English and Arabic, using a specific model/voice for each language. These are PlayAI voices. The STT, TTS, and LLM inference is all running on Groq Inc. (The LLM is LLama 4 Maverick.)

kwindla

13,401 просмотров • 1 год назад

Met a guy making $1.6 million/year as an LLM engineer. I asked him how he learned LLMs from scratch. He sent me the exact video that got him in. A 1 hour course on how LLMs actually work. He shows how transformers inside LLMs like ChatGPT & Claude are actually built. I watched it last night. Halfway through, I realized LLM architecture is way simpler than they make it look. Bookmark this and read the article below. • 00:00 - LLM foundations • 04:21 - LLM tokenization • 05:43 - LLMs vector embeddings • 22:16 - attention mechanism of LLM • 43:42 - LLM multi head attention

Met a guy making $1.6 million/year as an LLM engineer. I asked him how he learned LLMs from scratch. He sent me the exact video that got him in. A 1 hour course on how LLMs actually work. He shows how transformers inside LLMs like ChatGPT & Claude are actually built. I watched it last night. Halfway through, I realized LLM architecture is way simpler than they make it look. Bookmark this and read the article below. • 00:00 - LLM foundations • 04:21 - LLM tokenization • 05:43 - LLMs vector embeddings • 22:16 - attention mechanism of LLM • 43:42 - LLM multi head attention

Roan

80,961 просмотров • 1 месяц назад