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Introducing Argmax Local Server Run our state-of-the-art real-time transcription server directly on Mac! 0:31 Feature complete for AI Meeting Notes apps 0:49 Migrate from cloud APIs with 1 line of code 1:05 Fastest speech models with top accuracy 1:31 Other apps do not slow down Available starting today with...

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argmax

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13,003 Aufrufe • vor 11 Monaten •via X (Twitter)

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Introducing Real-time Transcription with Speakers! - Step change in accuracy, surpassing top cloud APIs - Faster than real-time on Mac and iPhone - Still under 3 watts when all features are enabled Available in Argmax SDK 2.0 for early access! Benchmarks and details in comments.
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Real-time Transcription with Speakers is now generally available on iOS and macOS! Details for installing or simply testing Argmax SDK 2 are in the comments.
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TTSKit now achieves sub-100ms time-to-first-byte for Qwen3-TTS 1.7b on Apple Silicon! Link to the code repo and details in comments.
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One of the biggest headaches in mobile AI is deciding between a cloud model (reliable but costly) and an on-device model (fast but fragmented) 😵‍💫 With hybrid inference, you don't have to choose! Learn the details in this deep dive. Chapters: 0:00 - Introducing hybrid SDKs for Firebase AI Logic 0:41 - Use Case: AI-Powered star ratings & reviews 1:00 - Why local? Reliability, offline support, & cost 1:30 - Coding step 1: SDKs and AICore setup 2:10 - Fallback strategies & JsonSchema 2:52 - Demo: Real-time hybrid inference in action
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Here's my conversation with the founding team of Cursor, a popular code editor (based on VSCode) that specializes in AI-assisted programming. This is a super technical conversation that is bigger than just about one code editor. It's about the future of programming and, in general, the future of human-AI collaboration. It's here on X in full, and is up on everywhere else. Timestamps: 0:00 - Introduction 0:59 - Code editor basics 3:09 - GitHub Copilot 10:27 - Cursor 16:54 - Cursor Tab 23:08 - Code diff 31:20 - ML details 36:54 - GPT vs Claude 43:28 - Prompt engineering 50:54 - AI agents 1:04:51 - Running code in background 1:09:31 - Debugging 1:14:58 - Dangerous code 1:26:09 - Branching file systems 1:29:20 - Scaling challenges 1:43:32 - Context 1:48:39 - OpenAI o1 2:00:01 - Synthetic data 2:03:48 - RLHF vs RLAIF 2:05:34 - Fields Medal for AI 2:08:17 - Scaling laws 2:17:06 - The future of programming
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15,201 Aufrufe • vor 25 Tagen

The goose team from Spiral joined us last night to introduce the Goose Development Kit (GDK) They walk through what goose is, why it's evolving into a toolkit for building open-source agentic apps, and what’s coming next Full talk ↓ Timestamps: 0:00 - Introducing Presidio Bitcoin and the Open Source AI Summit 1:40 - Why Spiral (Spiral) is expanding into AI with goose (Steve Lee) 4:59 - Introducing the Goose Development Kit (GDK) 10:34 - Goose's path from app to platform (Alex Hancock) 14:40 - Making agents easier to build (Douwe Osinga) 21:10 - Shipping goose as Rust APIs (Jack Amadeo) 25:15 - Building apps on top of goose (Lifei Z) 32:08 - Local models and open weights in goose (Jasper Hugo) 41:12 - Cutting token costs with routing (mic) 43:30 - Mesh-LLM: sharing local AI compute 47:53 - Q&A: Sharing compute across devices 50:20 - Finding hidden token costs (Filip Kujawa) 54:58 - Q&A: What makes goose different 59:17 - Q&A: Why GDK can stay neutral 1:06:52 - Q&A: Benchmarking harnesses without overfitting 1:10:48 - Q&A: Should goose train its own models? 1:15:20 - Q&A: Building specialized apps on goose
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Presidio Bitcoin

119,755 Aufrufe • vor 6 Tagen

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Starting today, open source is leading the way. Introducing Llama 3.1: Our most capable models yet. Today we’re releasing a collection of new Llama 3.1 models including our long awaited 405B. These models deliver improved reasoning capabilities, a larger 128K token context window and improved support for 8 languages among other improvements. Llama 3.1 405B rivals leading closed source models on state-of-the-art capabilities across a range of tasks in general knowledge, steerability, math, tool use and multilingual translation. The models are available to download now directly from Meta or Hugging Face. With today’s release the ecosystem is also ready to go with 25+ partners rolling out our latest models — including Amazon Web Services, NVIDIA, Databricks, Groq Inc, Dell Technologies, Microsoft Azure and Google Cloud ready on day one. More details in the full announcement ➡️ Download Llama 3.1 models ➡️ With these releases we’re setting the stage for unprecedented new opportunities and we can’t wait to see the innovation our newest models will unlock across all levels of the AI community.

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Ryan Ferris

138,272 Aufrufe • vor 7 Monaten

DiffusionKit now supports Stable Diffusion 3 Medium MLX Python and Core ML Swift Inference work great for on-device inference on Mac! MLX: Core ML: Mac App: Hugging Face Diffusers App (Pending App Store review)
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DiffusionKit now supports Stable Diffusion 3 Medium MLX Python and Core ML Swift Inference work great for on-device inference on Mac! MLX: Core ML: Mac App: Hugging Face Diffusers App (Pending App Store review)

argmax

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Here's my conversation with ThePrimeagen, a programmer who has educated, entertained, and inspired millions of people to build software and have fun doing it. It's here on X in full, and is up everywhere else too (see comment). Timestamps: 0:00 - Introduction 0:42 - Love for programming 10:15 - Hardest part of programming 12:31 - Types of programming 20:08 - Life story 30:12 - Hardship 31:44 - High school 37:30 - Porn addiction 47:16 - God 1:02:59 - Perseverance 1:12:55 - Netflix 1:25:23 - Groovy 1:30:27 - Printf() debugging 1:36:49 - Falcor 1:46:19 - Breaking production 1:49:04 - Pieter Levels 1:53:34 - Netflix, Twitch, and YouTube infrastructure 2:05:36 - ThePrimeagen origin story 2:20:52 - Learning programming languages 2:29:55 - Best programming languages in 2025 2:34:50 - Python 2:35:30 - HTML & CSS 2:36:20 - Bash 2:37:00 - FFmpeg 2:43:42 - Performance 2:46:15 - Rust 2:51:03 - Epic projects 3:04:27 - Asserts 3:13:41 - ADHD 3:21:49 - Productivity 3:26:13 - Programming setup 4:01:43 - Coffee 4:08:47 - Programming with AI 4:51:31 - Advice for young programmers 5:03:03 - Reddit questions 5:10:35 - God
5:20:10

Here's my conversation with ThePrimeagen, a programmer who has educated, entertained, and inspired millions of people to build software and have fun doing it. It's here on X in full, and is up everywhere else too (see comment). Timestamps: 0:00 - Introduction 0:42 - Love for programming 10:15 - Hardest part of programming 12:31 - Types of programming 20:08 - Life story 30:12 - Hardship 31:44 - High school 37:30 - Porn addiction 47:16 - God 1:02:59 - Perseverance 1:12:55 - Netflix 1:25:23 - Groovy 1:30:27 - Printf() debugging 1:36:49 - Falcor 1:46:19 - Breaking production 1:49:04 - Pieter Levels 1:53:34 - Netflix, Twitch, and YouTube infrastructure 2:05:36 - ThePrimeagen origin story 2:20:52 - Learning programming languages 2:29:55 - Best programming languages in 2025 2:34:50 - Python 2:35:30 - HTML & CSS 2:36:20 - Bash 2:37:00 - FFmpeg 2:43:42 - Performance 2:46:15 - Rust 2:51:03 - Epic projects 3:04:27 - Asserts 3:13:41 - ADHD 3:21:49 - Productivity 3:26:13 - Programming setup 4:01:43 - Coffee 4:08:47 - Programming with AI 4:51:31 - Advice for young programmers 5:03:03 - Reddit questions 5:10:35 - God

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1,135,502 Aufrufe • vor 1 Jahr

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i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

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16,289 Aufrufe • vor 1 Monat

first video from the All-In Summit 2025 - in conversation with Elon Musk available exclusively on X (0:00) Besties welcome Elon via Starlink (05:31) Ukraine and Starlink (19:10) green shoots of X (22:24) the creator economy and optimizing the X experience (26:43) the ADL, free speech, and advocating for peace (32:41) China (37:20) AI (44:30) where are we with self-driving? and MUCH more
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first video from the All-In Summit 2025 - in conversation with Elon Musk available exclusively on X (0:00) Besties welcome Elon via Starlink (05:31) Ukraine and Starlink (19:10) green shoots of X (22:24) the creator economy and optimizing the X experience (26:43) the ADL, free speech, and advocating for peace (32:41) China (37:20) AI (44:30) where are we with self-driving? and MUCH more

The All-In Podcast

80,974,084 Aufrufe • vor 2 Jahren