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i'm speechless! i got MiniMax-H3 running fully offline on a mac studio! 15 seconds, three shots, 32kHz stereo denoised jointly with the picture. took 39 minutes! Weights MiniMax Design (H3), Mac engine David Dalcu 🤗 I have ZERO knowledge of making any movies! Sound on and enjoy!

30,078 Aufrufe • vor 23 Tagen •via X (Twitter)

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“Bruce Lee had me up to three miles a day, really at a good pace. We'd run the three miles in twenty-one or twenty-two minutes. Just under eight minutes a mile [Note: when running on his own in 1968, Lee would get his time down to six-and-a-half minutes per mile]. So this morning he said to me ‘We're going to go five.’ I said, ‘Bruce, I can't go five. l'm a helluva lot older than you are, and I can't do five.’ He said, ‘When we get to three, we'll shift gears and it's only two more and you'll do it.’ I said ‘Okay, hell, I'll go for it.’ So we get to three, we go into the fourth mile and I'm okay for three or four minutes, and then I really begin to give out. I'm tired, my heart's pounding, I can't go any more and so I say to him, ‘Bruce, if I run any more, — and we're still running — ‘if I run any more I'm liable to have a heart attack and die.’ He said, ‘Then die’ It made me so mad that I went the full five miles. Afterward I went to the shower and then I wanted to talk to him about it. I said, you know, ‘Why did you say that?’ He said, ‘Because you might as well be dead. Seriously, if you always put limits on what you can do, physical or anything else, it'll spread over into the rest of your life. It'll spread into your work, into your morality, into your entire being. There are no limits. There are plateaus, but you must not stay there, you must go beyond them.’” - John Little, “The Art of Expressing the Human Body” (1998)

Historic Vids

6,923,976 Aufrufe • vor 2 Jahren

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B MoE refresh, Terminal-Bench 2.1 jumps 61.8→82.7 over the preview, DeepSWE 7.3→54.4. Closes in on Opus-4.8 on Agents' Last Exam (25.2 vs 25.7). MIT. → Muse-Glimmer-30B, from Meta (they are back!!): their first open agentic model. ~29.6B dense + perception encoder, 131k+ context, built to run fully local, no cloud. Apache 2.0. → Liquid AI LFM2.5-2.6B: 2.69B params, 131k context, 220 tok/s on an M5 Max in under 2.5GB RAM. Competitive with models 4x larger on agentic tasks. → inclusionAI Ling-3.0-flash: 124B total, only 5.1B active, ~12% the size of their old 1T flagship Ring-2.6, matches it on key benchmarks. MIT. → inclusionAI Ling-3.0-tiny: 7.9B total, 1.3B active, 86-90 tok/s on an M4 Pro MacBook at ~8GB peak memory. MIT. → NVIDIA Nemotron-3.5-Lightning-30B-A3B: hybrid Mamba-2+MoE+Attention, up to 1M context, runs on a single H100 or DGX Spark, SWE-bench Verified 52.8. → deepgrove maple-preview: 20B-A1B ternary-weight reasoner, 218 tok/s on a Mac mini M4, 5.3GB checkpoint. MIT. → BigBang-v1 (endless-frontier): fine-tuned from Qwen3.6-35B-A3B via a self-evolving generator/critic synthetic-data loop. Lands aggregate performance between DeepSeek V4 Flash (284B) and V4 Pro (1.6T), at 35B. Apache 2.0. 🎬 Video → MiniMax-H3: 33B dense omni model, native stereo audio, up to 2K/15s. 3.6k+ likes already. → Minimax-H3-Turbo (lightx2v): Apache-2.0 turbo distillation of H3 for fast inference. → Lightricks LTX-2.5: image-to-video update, custom Gemma-4-12B text encoder, a markedly stronger distilled model. 🔊 Voice → NVIDIA NemotronLabs VoiceChat-11B: full-duplex speech-to-speech, ~450ms turn-taking, #2 on open VoiceBench, and the first open full-duplex model with live tool-calling mid-conversation. 🛡️ Safety → Mistral Shieldstral-1.0-3B: 3B multimodal guardrail that takes your safety policy as plain text instead of fixed categories. Beats LlamaGuard-4-12B and ShieldGemma-9B on HarmBench (99.4) and ToxicChat (84.1) at a fraction of the size. Apache 2.0.

Victor M

54,264 Aufrufe • vor 17 Tagen

You don't need a GPU for fast studio grade voice cloning anymore. Qwen3 TTS (1.7B Q4_K_M) + mainline llama.cpp is officially the fastest way to generate zero shot voice clones using 100% pure CPU execution. Following up on my last post where we ran the Q8 model on a GPU, we just took local C++ voice synthesis a massive step further. The open source community quantized Alibaba's SOTA Qwen3 TTS model down to Q4_K_M GGUF, completely freeing local audio pipelines from dedicated graphics hardware. Here is the real world benchmark and hardware breakdown of running SOTA voice cloning on CPU: # Architecture & Model Setup Using Qwen3-TTS-12Hz-1.7B-Base-Q4_K_M.gguf paired with the 8 bit multimodal projector (mmproj-Q8_0.gguf), llama.cpp executes the entire pipeline in pure C++. No PyTorch, no CUDA dependencies, and no VRAM bottlenecks. # Real-World Memory Footprint - Baseline RAM: 1.6 GB system idle. - Peak Generation RAM: 8 GB RAM during active voice synthesis. - Requirement: Any basic machine with at least 8 GB of system RAM can run this easily. # Real World CPU Benchmarks - Google Colab Free Tier (Throttled 2 Core CPU): Synthesizes a 5 sec studio quality audio clip (~8 words) in 45 seconds. - Modern Consumer CPU (Intel i5/i7 13th/14th Gen or AMD Ryzen 7000/9000): generation should drop to 5 to 20 seconds (nearly 1:1 real-time generation speed!). # Zero Shot Voice Cloning Quality Pass any 5 to 20 second .wav audio sample to the C++ engine using the --tts-speaker-file flag. It yields clean, natural sounding cloned speech with virtually zero quality loss compared to unquantized FP16 weights. To make testing seamless, I built an updated zero config Google Colab notebook. It pulls the official pre built llama.cpp CPU binaries (zero compilation time!) launches a live Gradio web app right in your browser. Record a 5 second clip from your mic (or drop a .mp3, .wav file), type text, and generate cloned audio on CPU. Native C++ audio models are making edge based, offline AI voice agents a reality. Links to the free Q4 CPU Colab notebook and the Q4_K_M GGUF HuggingFace repository are in the replies below! Which models have you been running on your CPUs? What CPU hardware are you using for local inference?

Alok

60,514 Aufrufe • vor 21 Tagen

First off, thank you for such great support so far. The book was #1 in Poverty Studies (Amazon) and even got to the low thousands in Fiction and Literature 😊👍 which I got a kick out of...nice to have a book that isn't in the trillion ranking... I'll be continuing to promote this book as it's still new but it's fun to get back to work on the Quitturz. I hope to have that out in maybe three months. As usual, I'll be working on more than one book so I'll also be assembling Book 2 of the Al and Ivy series. That one will have more insight into the mental health issue, larger camps, and have much more Ivy as she became especially important as the series progresses. On The Road With Al & Ivy: Book One: Becoming A Face is now live on Kindle Unlimited and will be .99 until July 30th. Link: Note: The book is a realistic depiction of the scene, so it's 18+ Also the Anthology is priced at .99 for now. Book 1 Overview On The Road With Al & Ivy is a planned trilogy of novels that are loosely based on the author's life in the San Francisco Bay homeless scene in 2016. His travels took him and Ivy to Northern California, Marin County, San Francisco, East Bay, Silicon Valley, Gilroy, Monterrey Peninsula, and Fresno. The On The Road With Al & Ivy novels are about a group of people in 2016, with all of their virtues and flaws, dealing with a catastrophic situation with resilience and making both good and bad choices to survive. The novel depicts various subcultures and situations that are rarely covered in the media and gives the reader a realistic picture of the homeless population. That means everything, from the violence and drug use that's often sensationalized in the media, back stories that humanize the stereotypes, the sense of community as strong as any in the mainstream, and even the rough sense of humor that many have about their situation. The author's main intent is to put a human face on the homeless population. It's always been there and Book 1 begins that process. #BookTwitter #kindleunlimited #homeless #shitzu #books #siliconvalley #fiction #Blogs

Boogie Underground

22,754 Aufrufe • vor 1 Jahr

Hello legends! I'm Cryptobrax , the guy who's been on quite the roller coaster ride. From being broke to hitting six figures, then back to zero, and back up to six figures again – all in just three years! Let me break it down for you: In 2021, I started with $2,000 (all my life savings!), and with a stroke of luck, it soared past six figures by simply following advice from friends and folks on Twitter. I thought I was on the path to millionaire status, but it all came crashing down to $0 as quickly as it rose. In 2023, I started again with just $200, but this time, I dug deeper. Instead of blindly following trends, I investigated the projects deeper, did my homework, and invested wisely. As a result, despite the recent market turbulence losing 6 figures sum in my portfolio, my overall portfolio has maintained well above the six-figure mark. Sure, it stings to see losses, but it is what it is. As we gear up for the bullish phase, get ready for better content and more projects that I believe have the potential to at least 100x! I want to take a moment to express my sincere gratitude to the amazing community that has supported me on this crypto journey. Building a following from scratch has been both challenging and rewarding. I've spent countless hours researching projects, absorbing every piece of information I could find, and sharing insights with you. I'm proud of the progress we've made together. While I strive to provide valuable insights, I'm not right all the time. Mistakes happen, and not every project pans out as expected. That's why I'm committed to thorough due diligence, and I urge you to do the same before making any investment decisions. Transparency, honesty, and trust are the cornerstones of my approach. I'm not just tweeting about projects; my own investments are on the line. We're embarking on an exciting journey together, aiming for positive change and enjoying the ride along the way. I wanted to share this message to give you a glimpse into who I am and what value I can share with you. If you value my content and the person behind it, I'd appreciate your continued support. Feel free to share this post if it resonates with you. Thank you from the bottom of my heart for your incredible support thus far! Remember: I'm not a financial advisor. Always do your own research before making investment decisions. #degen #blockchain #smartmoney

Cryptobrax

373,038 Aufrufe • vor 2 Jahren

Yesterday at 3 AM Claude Code called me I woke up, picked up the phone, and on the screen was a message: "Wallet entered BTC Up at 11 cents. Open Polymarket?" I said yes and went back to sleep Claude Code unlocked my 2nd phone on its own, opened Polymarket, found the right market, entered the amount, and hit Buy. I could see all of it in real time through the web interface on my laptop. Screenshots from the phone updating every second. By morning the position closed in profit Let me tell you how I got here A week ago I asked Claude Code to write a script that pulls on-chain data from Polymarket and ranks wallets by win rate on 15-minute BTC markets In 20 minutes I had a table with hundreds of addresses, and 1 of them stood apart from the rest. More than 200 trades per day, surgical entry precision, and a profit curve going straight up I fed that address back into Claude Code and asked it to break down the strategy. Turns out the wallet monitors BTC volatility on Binance and Bybit every 100 milliseconds, and when it drops below 0.08% it enters Up and Down simultaneously at 25 to 35 cents A pure straddle: 1 side burns and the other flies to a dollar, giving 3 to 4x per position. Dozens of times a day I wanted to follow it but signals came at any hour, and waking up every 15 minutes for a notification was simply impossible. So I built something else Took an old Android phone and installed an agent running on the Qwen3-VL visual model. It sees what is happening on the screen and mimics human actions through ADB: taps, swipes, text input. Then I connected it to Claude Code as the executor Now the chain works like this: Claude Code monitors the wallet, sees a new position, calls me. And if I say "yes" or just do not pick up within 30 seconds, the agent on the phone opens Polymarket on its own and copies the entry Essentially I built myself an autopilot out of 2 AI systems: 1 thinks and the other presses buttons. I just sleep and occasionally pick up the phone → Here is the wallet the whole thing is tracking: For those who do not want to build a setup like this there is a Telegram bot that handles the 1st part: tracks this wallet and sends a signal on every new entry: AI calls me at 3 AM to ask permission to spend my money A year ago this would have sounded like schizophrenia. Now it is just Tuesday

Blaze

56,501 Aufrufe • vor 5 Monaten