JayTee427

@hau9000 Your creations are so beautiful and intricate! 😍 I think we would all love to see some of the process behind your creative works too!

世界の皆さん、こんにちは！ 私は、金属でメカニカルな動物を作るアーティストです🛠️ 作品は銀やブロンズでできていて、翼が開閉したり色々なパーツが動くもの、トランスフォームして形が変わるものなど、どれも面白い仕掛けを持っています！ 是非皆さんに知っていただけたら嬉しいです😄

The tech is here, now! On long trips, I’ve never waited to charge for longer than 25 mins (by choice) for a full charge when almost fully depleted, but typically it’s 15-20 mins.. With kids on road trips, you’re stopping for them more than you are for gas/charging! Typically it’s 20mins breaks for us, as thats about as long as it takes for a bathroom visit and to get your kids a snack/treat etc. You can do more/less per stop, as she was showing in the video, the map will auto route based on your charge/time/destination. As a guy with a truck as well, to fill 36 gallons takes almost 10 mins, and I have to stand at the pump and wait. Not the case with charging. I’m hoping you get that Model X soon enough!! Happy travels!!

@elonmusk Charging fatigue for long trips, we are 650 miles away and when we drive 15 minute breaks. I don't want to sit for 2 hours waiting on my car to charge. Maybe one day the tech will get there, or Elon can send me a model X to try out ..lol. 2 kids of course.

It does this right now! Jump in, tell it where you want to go, it drives you from your driveway, to the store and parks itself. When you get out of the store, head to the curb and press the summon button on your phone, watch the car come to you. Load your stuff. Jump in car and have it drive you home!

@elonmusk Tesla needs to make it so I can get out of my car and it finds itself a parking space and then when I get back out of a store or wherever, I hit a button and it comes and finds me using the GPS on my phone and picks me up!

Thank you @nikitabier. Watching the heartwarming cultural exchange, in real time on X, between Japanese and Americans on all things of common goodness... food, drink, music, cars, cute stuff and random craziness. It’s the thing I don’t think most of us knew we all needed in our feeds!

@UnslothAI @grok can this be run on an Nvidia Spark DGX, or only on Mac/Windows with an RTX GPU?

Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool calling and code execution • Compare models side by side + export to GGUF GitHub: github.com/unslothai/unsl… Blog and Guide: unsloth.ai/docs/new/studio Available now on Hugging Face, NVIDIA, Docker and Colab.

@NVIDIAAIDev @openclaw @grok will this run on an nvidia dgx spark?

🦞These innovations come together to create a model that is well suited for long-running autonomous agents. On PinchBench—a benchmark for evaluating LLMs as @OpenClaw coding agents—Nemotron 3 Super scores 85.6% across the full test suite, making it the best open model in its class.

Introducing NVIDIA Nemotron 3 Super 🎉 Open 120B-parameter (12B active) hybrid Mamba-Transformer MoE model Native 1M-token context Built for compute-efficient, high-accuracy multi-agent applications Plus, fully open weights, datasets and recipes for easy customization and deployment. 🧵

Made with Grok Imagine

@icreatelife Happy Birthday Kris!! I’m hoping you are celebrating it with close friends or distant family, but also all your virtual X friends here as well!! Best wishes! Keep up the amazing work and importation for us all! ❤️

Hi everyone from Seoul, South Korea 🥹🫶 Today is my birthday and I am super happy and grateful for you

@karpathy Thanks so much for doing Dwarkesh’s podcast @karpathy. It was such a fascinating discussion, and some really thought provoking discussions on where we are headed with AI and the future! I greatly appreciated you sharing your views and insights with us all.

My pleasure to come on Dwarkesh last week, I thought the questions and conversation were really good. I re-watched the pod just now too. First of all, yes I know, and I'm sorry that I speak so fast :). It's to my detriment because sometimes my speaking thread out-executes my thinking thread, so I think I botched a few explanations due to that, and sometimes I was also nervous that I'm going too much on a tangent or too deep into something relatively spurious. Anyway, a few notes/pointers: AGI timelines. My comments on AGI timelines looks to be the most trending part of the early response. This is the "decade of agents" is a reference to this earlier tweet x.com/karpathy/statu… Basically my AI timelines are about 5-10X pessimistic w.r.t. what you'll find in your neighborhood SF AI house party or on your twitter timeline, but still quite optimistic w.r.t. a rising tide of AI deniers and skeptics. The apparent conflict is not: imo we simultaneously 1) saw a huge amount of progress in recent years with LLMs while 2) there is still a lot of work remaining (grunt work, integration work, sensors and actuators to the physical world, societal work, safety and security work (jailbreaks, poisoning, etc.)) and also research to get done before we have an entity that you'd prefer to hire over a person for an arbitrary job in the world. I think that overall, 10 years should otherwise be a very bullish timeline for AGI, it's only in contrast to present hype that it doesn't feel that way. Animals vs Ghosts. My earlier writeup on Sutton's podcast x.com/karpathy/statu… . I am suspicious that there is a single simple algorithm you can let loose on the world and it learns everything from scratch. If someone builds such a thing, I will be wrong and it will be the most incredible breakthrough in AI. In my mind, animals are not an example of this at all - they are prepackaged with a ton of intelligence by evolution and the learning they do is quite minimal overall (example: Zebra at birth). Putting our engineering hats on, we're not going to redo evolution. But with LLMs we have stumbled by an alternative approach to "prepackage" a ton of intelligence in a neural network - not by evolution, but by predicting the next token over the internet. This approach leads to a different kind of entity in the intelligence space. Distinct from animals, more like ghosts or spirits. But we can (and should) make them more animal like over time and in some ways that's what a lot of frontier work is about. On RL. I've critiqued RL a few times already, e.g. x.com/karpathy/statu… . First, you're "sucking supervision through a straw", so I think the signal/flop is very bad. RL is also very noisy because a completion might have lots of errors that might get encourages (if you happen to stumble to the right answer), and conversely brilliant insight tokens that might get discouraged (if you happen to screw up later). Process supervision and LLM judges have issues too. I think we'll see alternative learning paradigms. I am long "agentic interaction" but short "reinforcement learning" x.com/karpathy/statu…. I've seen a number of papers pop up recently that are imo barking up the right tree along the lines of what I called "system prompt learning" x.com/karpathy/statu… , but I think there is also a gap between ideas on arxiv and actual, at scale implementation at an LLM frontier lab that works in a general way. I am overall quite optimistic that we'll see good progress on this dimension of remaining work quite soon, and e.g. I'd even say ChatGPT memory and so on are primordial deployed examples of new learning paradigms. Cognitive core. My earlier post on "cognitive core": x.com/karpathy/statu… , the idea of stripping down LLMs, of making it harder for them to memorize, or actively stripping away their memory, to make them better at generalization. Otherwise they lean too hard on what they've memorized. Humans can't memorize so easily, which now looks more like a feature than a bug by contrast. Maybe the inability to memorize is a kind of regularization. Also my post from a while back on how the trend in model size is "backwards" and why "the models have to first get larger before they can get smaller" x.com/karpathy/statu… Time travel to Yann LeCun 1989. This is the post that I did a very hasty/bad job of describing on the pod: x.com/karpathy/statu… . Basically - how much could you improve Yann LeCun's results with the knowledge of 33 years of algorithmic progress? How constrained were the results by each of algorithms, data, and compute? Case study there of. nanochat. My end-to-end implementation of the ChatGPT training/inference pipeline (the bare essentials) x.com/karpathy/statu… On LLM agents. My critique of the industry is more in overshooting the tooling w.r.t. present capability. I live in what I view as an intermediate world where I want to collaborate with LLMs and where our pros/cons are matched up. The industry lives in a future where fully autonomous entities collaborate in parallel to write all the code and humans are useless. For example, I don't want an Agent that goes off for 20 minutes and comes back with 1,000 lines of code. I certainly don't feel ready to supervise a team of 10 of them. I'd like to go in chunks that I can keep in my head, where an LLM explains the code that it is writing. I'd like it to prove to me that what it did is correct, I want it to pull the API docs and show me that it used things correctly. I want it to make fewer assumptions and ask/collaborate with me when not sure about something. I want to learn along the way and become better as a programmer, not just get served mountains of code that I'm told works. I just think the tools should be more realistic w.r.t. their capability and how they fit into the industry today, and I fear that if this isn't done well we might end up with mountains of slop accumulating across software, and an increase in vulnerabilities, security breaches and etc. x.com/karpathy/statu… Job automation. How the radiologists are doing great x.com/karpathy/statu… and what jobs are more susceptible to automation and why. Physics. Children should learn physics in early education not because they go on to do physics, but because it is the subject that best boots up a brain. Physicists are the intellectual embryonic stem cell x.com/karpathy/statu… I have a longer post that has been half-written in my drafts for ~year, which I hope to finish soon. Thanks again Dwarkesh for having me over!

@thatsKAIZEN Kaizen, thanks for being and amazing human, a voice of reason, a source of perspective.. Happy Birthday!

Today is my 35th bday. It’s been my best year of life yet. Thank you to all of you who supported my mission. Many of you have asked where you can get the Clear Thinker clothing I wear. I’m making it available starting today. For the next 72 hours, 100% of the profits will go to the Tim Tebow Foundation to fight child trafficking. Link in replies.

We're All We Need youtu.be/oeFUVunx8Ag?si… Thanks to Zoe Johnston and A&B for such an incredible piece of music…🫶❤️

@icreatelife I’m so very sorry! I can’t imagine. Take time for your self to process it all and feel all the feelings. Even if that means you step away from here for a bit, (unless we’re all a good distraction!) We’ll all be here sending positive thoughts and prayers your way! 🤗

@jephtanner Thank you, it’s related to health, family and profound loss 🥺 one day I will share more when I find a way and process it all. But now just breathing and appreciating all of your support and love and kindness ❤️

Got another difficult personal news. Past few days have been really challenging and all love and support mean more than you can imagine. Currently, need a hug and some good thoughts.

@nikitabier 408 BBS’s at 300 baud!

What was your earliest memory of the Internet?

@icreatelife Kris, thank you for all that you’ve done for us to get there!! Keep on keeping on!!

Thank you 𝕏 team and this platform for supporting my AI work and welcoming my AI community of over 108,000 people now. AI community and innovation wouldn’t be the same without this platform and being able to share and reach millions. Thank you for this absolute cool merch.

@icreatelife Kris, we're all grateful for you too!

Grateful for you

@NVIDIAGeForce GeForce Day

🟢 GEFORCE DAY IS BACK 🟢 To celebrate, we're giving away TWO GeForce RTX 5080 Founders Edition GPUs, signed by NVIDIA CEO Jensen Huang. Want one? Comment "GeForce Day" for a chance to WIN & stay tuned for more!