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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... show more

argmax

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13,003 views • 1 year ago •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.

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.

argmax

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Introducing Real-time Transcription with Nvidia Parakeet - Same top accuracy as file transcription - Best-in-market 160 ms lips-to-screen latency - 744x more cost-efficient compared to cloud APIs - Available in Argmax Pro SDK starting today! Link in comments

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argmax

58,986 views • 1 year ago

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.

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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29,142 views • 5 months ago

🤖 Introducing our Model Context Protocol (MCP) Server The MCP protocol standardizes how apps provide context to LLMs. No more training LLMs — just connect them directly to our blockchain APIs for live token prices, transfers, NFT data, and more 💪 Build smarter AI agents today! Let’s gooooooo 🔗 -------------- TIMESTAMPS 0:00 Setting up the configuration file 0:30 Add configuration to Cursor 1:06 Executing prompts for the price of ETH 2:25 Getting data on Vitalik’s transfers 3:45 Contributing or accessing our MCP server

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Alchemy

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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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argmax

30,154 views • 5 months ago

Introducing Modern Claudefare Built fully with Opus 5 on High Mode over a few days using principles from Matt Shumer’s Gauntlet Loop - 84,100 lines of code Includes remakes of 4 beloved maps: 0:00 - Rust 0:40 - Highrise 0:57 - Nuketown 1:26 - Terminal Solo & multiplayer (w/ voice chat), bots included Tools used: - Three.js as core Javascript 3D library (all 20 guns and 4 maps generated by the model in code) - MeshyAI for 3D models + rigging + animations of 8 soldiers, 1 helicopter (highrise) and 1 bus (nuketown) - ElevenLabs for 430+ SFX, Music & TTS generations Play it now at (More details in thread)

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Rishi

276,255 views • 8 days ago

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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Firebase

12,038 views • 3 months ago

The next generation of mobile apps will run multimodal AI locally by default. Today, we’re making it practical for developers to ship. We just launched NexaSDK for Mobile on Product Hunt. Developers can run the latest multimodal AI models fully on-device in iOS & Android apps with Apple Neural Engine and Qualcomm Hexagon NPU acceleration. In just 3 lines of code, build chat, multimodal, search, and audio features with no cloud cost, complete privacy, 2x faster speed and 9× better energy efficiency. Try out NexaSDK for Mobile and we’d love your feedback (Product Hunt link in thread).

The next generation of mobile apps will run multimodal AI locally by default. Today, we’re making it practical for developers to ship. We just launched NexaSDK for Mobile on Product Hunt. Developers can run the latest multimodal AI models fully on-device in iOS & Android apps with Apple Neural Engine and Qualcomm Hexagon NPU acceleration. In just 3 lines of code, build chat, multimodal, search, and audio features with no cloud cost, complete privacy, 2x faster speed and 9× better energy efficiency. Try out NexaSDK for Mobile and we’d love your feedback (Product Hunt link in thread).

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319,337 views • 7 months ago

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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Lex Fridman

1,261,340 views • 1 year ago

We recently sat down with Brett Adcock at Figure to discuss Helix 02, the future of Humanoids, and Brett's vision for Figure. It's a full blown Humanoid takeover. (w/ @DavidBlundin ) (0:00:00) - Neural Nets, Data Moats & The Age of Abundance (0:04:06) - Going All‑In on Neural Nets (0:12:22) - LLMs vs Physics: Why Language Models Can’t Run Robots (0:16:31) - Global Competition & Industry Consolidation (0:24:27) - Helix in Production: Logistics & Long‑Horizon Autonomy (0:30:00) - Scaling Figure 3: Robots Building Robots (0:52:44) - Jarvis‑Style Digital AI (1:02:25) - Healthcare, Surgery & Robots in the Home (1:15:20) - Safety, Privacy & Trusting Robots with Your Family (1:29:37) - Billions of Humanoids & The Global Robot Economy

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Peter H. Diamandis, MD

174,220 views • 6 months ago

Today we’re introducing the Apps for Advertising collection. A growing library of easy-to-use apps inside of Runway that allow you to get from idea to deliverable with less time, money and effort. From generating endless product shots for social and e-commerce to mocking up designs in real world placements, the Apps for Advertising collection is designed to help your teams get the most out of Runway without the need for complicated prompting or advanced workflows. Learn more below and get started today. 1/5

Today we’re introducing the Apps for Advertising collection. A growing library of easy-to-use apps inside of Runway that allow you to get from idea to deliverable with less time, money and effort. From generating endless product shots for social and e-commerce to mocking up designs in real world placements, the Apps for Advertising collection is designed to help your teams get the most out of Runway without the need for complicated prompting or advanced workflows. Learn more below and get started today. 1/5

Runway

35,664 views • 9 months ago

"Projects like the New Deal, the Apollo program pale in comparison to what we're doing right now." 🆕 Greg Brockman (Greg Brockman) joins us to talk GPT-5, GPT-OSS, and what's next on OpenAI's road to crystallizing all of human intelligence! “Energy turns into compute, turns into intelligence… crystallizing compute into potential energy you can release again and again.” 0:00:04 - Introductions 0:01:04 - The Evolution of Reasoning at OpenAI 0:04:01 - Online vs Offline Learning in Language Models 0:06:44 - Sample Efficiency and Human Curation in Reinforcement Learning 0:08:16 - Scaling Compute and Supercritical Learning 0:13:21 - Wall clock time limitations in RL and real-world interactions 0:16:34 - Experience with ARC Institute and DNA neural networks 0:19:33 - Defining the GPT-5 Era 0:22:46 - Evaluating Model Intelligence and Task Difficulty 0:25:06 - Practical Advice for Developers Using GPT-5 0:31:48 - Model Specs 0:37:21 - Challenges in RL Preferences (e.g., try/catch) 0:39:13 - Model Routing and Hybrid Architectures in GPT-5 0:43:58 - GPT-5 pricing and compute efficiency improvements 0:46:04 - Self-Improving Coding Agents and Tool Usage 0:49:11 - On-Device Models and Local vs Remote Agent Systems 0:51:34 - Engineering at OpenAI and Leveraging LLMs 0:54:16 - Structuring Codebases and Teams for AI Optimization 0:55:27 - The Value of Engineers in the Age of AGI 0:58:42 - Current state of AI research and lab diversity 1:01:11 - OpenAI’s Prioritization and Focus Areas 1:03:05 - Advice for Founders - It's Not Too Late 1:04:20 - Future outlook and closing thoughts 1:04:33 - Time Capsule to 2045 - Future of Compute and Abundance 1:07:07 - Time Capsule to 2005 - More Problems Will Emerge

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Latent.Space

305,090 views • 1 year ago

NVIDIA CEO JENSEN HUANG: THE AI APOCALYPSE NARRATIVE IS COMPLETE NONSENSE "it's computer and software. we make it better every year because we know exactly how it works" the real disruption is developers deploying local setups to out-produce entire teams: > hardware scale - from a $249 Jetson Orin Nano Super to a $2,999 DGX Spark with 128GB of unified memory > local inference - DGX Spark runs 70B-200B models on 1 PFLOP of throughput with zero cloud GPU rental costs > database privacy - redirecting Python API clients to Ollama takes one line of code to bypass subscription bills the people who configure local AI today are going to look very far ahead of the curve by 2027 read the setup guide below 👇

NVIDIA CEO JENSEN HUANG: THE AI APOCALYPSE NARRATIVE IS COMPLETE NONSENSE "it's computer and software. we make it better every year because we know exactly how it works" the real disruption is developers deploying local setups to out-produce entire teams: > hardware scale - from a $249 Jetson Orin Nano Super to a $2,999 DGX Spark with 128GB of unified memory > local inference - DGX Spark runs 70B-200B models on 1 PFLOP of throughput with zero cloud GPU rental costs > database privacy - redirecting Python API clients to Ollama takes one line of code to bypass subscription bills the people who configure local AI today are going to look very far ahead of the curve by 2027 read the setup guide below 👇

Mr. Buzzoni

15,201 views • 1 month ago

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

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

Presidio Bitcoin

126,900 views • 1 month ago

New Epoch podcast episode: How far can current AI trends continue? Jaime Sevilla and Yafah Edelman on where current AI trends carry us —and where they break. They disagree on mechanisms and outcomes, but agree on this: fast diffusion now, broad cognitive automation by ~2035, and extreme uncertainty after. (0:00:00) - Preview (0:00:41) - Intro: Does 5× compute scaling continue? (0:08:15) - Largest training run in 2030 & what does it imply? (0:12:44) - Impact on Software Engineering & other cognitive tasks (0:23:27) - Economic impacts near the end of the decade (0:31:34) - 2030 bifurcation: Slow down or take off? (0:35:49) - Physical vs cognitive automation (0:44:37) - Timelines and impact of full cognitive automation (1:02:37) - Returns to intelligence (1:08:51) - Three cruxes after 2035 (Robots, technology & intelligence) (1:16:28) - What happens in 2040? (1:23:16) - Recap: Three eras of forecasting (1:37:42) - Closing remarks

New Epoch podcast episode: How far can current AI trends continue? Jaime Sevilla and Yafah Edelman on where current AI trends carry us —and where they break. They disagree on mechanisms and outcomes, but agree on this: fast diffusion now, broad cognitive automation by ~2035, and extreme uncertainty after. (0:00:00) - Preview (0:00:41) - Intro: Does 5× compute scaling continue? (0:08:15) - Largest training run in 2030 & what does it imply? (0:12:44) - Impact on Software Engineering & other cognitive tasks (0:23:27) - Economic impacts near the end of the decade (0:31:34) - 2030 bifurcation: Slow down or take off? (0:35:49) - Physical vs cognitive automation (0:44:37) - Timelines and impact of full cognitive automation (1:02:37) - Returns to intelligence (1:08:51) - Three cruxes after 2035 (Robots, technology & intelligence) (1:16:28) - What happens in 2040? (1:23:16) - Recap: Three eras of forecasting (1:37:42) - Closing remarks

Epoch AI

34,979 views • 11 months ago

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.

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.

AI at Meta

1,269,168 views • 2 years ago

J⧉nus (j⧉nus) is mapping the psychology of synthetic minds. They offer a different path to AI alignment, arguing that models exhibit forms of agency and emotional states. 0:00:00 - LLM vs human cognition & what it is like to be J⧉nus 0:06:30 - Cyborgism, The Dreaming, reality melting into narrative 0:12:08 - The role of love in alignment and co-ordination 0:17:30 - What J⧉nus would do differently at Anthropic 0:23:05 - The "AI assistant" problem 0:29:02 - Phenomenology and “cosmic love” of Claude 3 Opus 0:33:36 - Altered states and drugs use in LLMs 0:42:59 - The "Batman" and multimodal consciousness 0:45:06 - Embodiment in Claude models 0:54:49 - “Truesight”: models seeing more than they should 0:59:38 - The origin story of J⧉nus 1:02:00 - Bing Sydney and Hyperstition 1:07:57 - Morpheus, Mu, Loom and the Multiverse Optimizer 1:14:37 - The Good Timeline and the danger of complacency Recorded live with Ryan Ferris and j⧉nus at State of the Art[ist] 001. Video production and avatar by Goodbye Monkey. Thank you to the hosts at The Garden.

Ryan Ferris

138,584 views • 8 months ago

Hunter Biden. 0:00 Why Did Hunter Sit Down With Candace Owens? 12:34 The Dark Side of Social Media 18:06 War, Insider Trading, and the Washington Elites 32:36 Thomas Massie and Marjorie Taylor Greene 35:21 The Importance of Self-Reflection 39:49 Addiction and Sobriety 48:31 The Unanswered Questions of the Hunter Biden Laptop Story 58:21 How Hunter Found Out About the Laptop Story 1:05:44 What Was Israel's Role in the Laptop Story? 1:12:12 Hunter Meeting His Wife and Overcoming Addiction 1:23:28 The Thing Far More Important Than Politics 1:31:51 The Dangers of AI 1:35:27 The Evils of Benjamin Netanyahu 1:36:57 How Alcohol Affects You and How to Get Sober 1:57:13 What Does Hunter's Wife Think About All This? 1:58:22 What's Hunter's Plan for the Future? 2:01:04 Hunter's Journey to Financial Freedom 2:04:34 Hunter's Relationship With God

Hunter Biden. 0:00 Why Did Hunter Sit Down With Candace Owens? 12:34 The Dark Side of Social Media 18:06 War, Insider Trading, and the Washington Elites 32:36 Thomas Massie and Marjorie Taylor Greene 35:21 The Importance of Self-Reflection 39:49 Addiction and Sobriety 48:31 The Unanswered Questions of the Hunter Biden Laptop Story 58:21 How Hunter Found Out About the Laptop Story 1:05:44 What Was Israel's Role in the Laptop Story? 1:12:12 Hunter Meeting His Wife and Overcoming Addiction 1:23:28 The Thing Far More Important Than Politics 1:31:51 The Dangers of AI 1:35:27 The Evils of Benjamin Netanyahu 1:36:57 How Alcohol Affects You and How to Get Sober 1:57:13 What Does Hunter's Wife Think About All This? 1:58:22 What's Hunter's Plan for the Future? 2:01:04 Hunter's Journey to Financial Freedom 2:04:34 Hunter's Relationship With God

Tucker Carlson

2,037,494 views • 1 day ago

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)

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

74,009 views • 2 years ago

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

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

Lex Fridman

1,139,667 views • 1 year ago