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Xpicker2
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Xpicker2
@xpickr
Automatically pick a random winner from any X post 🤖 the X picker 🔥 Follow us for a bonus point. AI acceleration incoming.
Katılım Ağustos 2022
543 Takip Edilen6.9K Takipçiler
🚨Free Seedance 2.0 giveaway!🚨
We're giving away 20 more monthly subscriptions with Seedance 2.0 access today 🎁
Here's how to win!
⚡️Like, repost, and comment "seedance"
⏰ 20 lucky winners will be announced in the next 24h
Must be following @yapper_so!
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Who wants early access to a new AI tool from a major AI company?👀
Drop a comment and I’ll add you to the list.
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Xpicker2 retweetledi
OK, well. I ran /autoresearch on the the liquid codebase.
53% faster combined parse+render time, 61% fewer object allocations.
This is probably somewhat overfit, but there are absolutely amazing ideas in this.
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Xpicker2 retweetledi
Noah is the world's first executive AI agent, exclusively designed for very busy executives.
Love how @ashishtoshniwal launched his company.
The company says it learns from your habits, and it works where busy executives are: on their phone.
I'll be using it next week at NVIDIA GTC since I'm gonna be living the life of a busy executive: the whole week scheduled out already.
Ashish Toshniwal@ashishtoshniwal
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Xpicker2 retweetledi
Xpicker2 retweetledi
karpathy just broke the internet with something called auto research
it’s basically an ai research agent that runs experiments for you 24/7
you give it a goal like
“make this model better”
“find a higher converting landing page”
“lower customer acquisition cost”
then it runs a loop:
1) plan an experiment
2) edit the code or config
3) run a short test on a gpu
4) read the metrics
5) keep the winner
6) try again
over and over
while you sleep
by the morning you wake up to the best version
actual tested improvements
think of it like a robot research intern that runs hundreds of experiments and only keeps the winners
this is link to his repo github.com/karpathy/autor… for your to mess around with it
in the latest episode of @startupideaspod
i break down:
• what auto research actually is
• how it works step by step
• 10 business ideas you can build with it
• how to install it and start using it
this one is saucy
because tools like this change how startups get built
watch
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Xpicker2 retweetledi
Fractional Cursor acquisition.
xAI taking the right steps
Jason Ginsberg@JasonBud
I’m proud to be joining SpaceX and xAI with @milichab It has become clear that software is changing fundamentally. More and more, people can shape the tools they use directly, and the ceiling of what can be built keeps rising. What makes xAI special is the scale of its ambition: to build from first principles all the way out to the stars. I’m especially grateful to work on products that expand human agency and freedom. That mission is deeply personal to me. My family came to the United States fleeing communism, and the belief that freedom should be part of the next generation of the internet has driven me every day since Andrew and I started Skiff. Now, we get to work on intelligence, understanding, and freedom on a universal scale.
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Xpicker2 retweetledi
Unconventional advice from my conversation with Netflix co-founder and first CEO Marc Randolph.
He said first prove your "non-repeatable, non-scalable idea".
If you can do that, you're onto something.
Feels especially relevant after Netflix acquired Ben Affleck’s AI film startup. Keep building your story.
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Xpicker2 retweetledi
🎉 We just released Rotate Object in Photoshop (beta) 🎉
You can now rotate 2D images! 🤯
Then use Harmonize to add light and shadows, to blend it perfectly with the rest of the scene.
It's like Turntable in Illustrator, but instead of vectors, it's pixels in Photoshop!
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Xpicker2 retweetledi
The Grok 4.20 Beta shows three major improvements over Grok 4:
➤ Our lowest ever hallucination rate on the AA-Omniscience evaluation. When Grok did not know the answer, it hallucinated an incorrect answer 22% of the time - this is the lowest hallucination rate of any model we have tested, topping Claude Haiku 4.5 (25%)
➤ Top scores for instruction following and prompt adherence. On IFBench, Grok 4.20 takes the #1 spot with 82.9% - a +29.2 point increase on Grok 4
➤ Leading speed for its intelligence. At 265 tokens per second output speed on xAI’s API, Grok 4.20 is significantly faster than its peer and over 2x the output speed seen from Grok 4.1 Fast
Congratulations to @xai and @elonmusk on the 4.20 Beta 0309 launch!
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Xpicker2 retweetledi
OK this thing is totally insane. Before going to bed I...
* used try to make a new qmdresearcher directory
* told my pi to read this github repo and make a version of that for the qmd query-expansion model with the goal of highest quality score and speed. Get training data from tobi/qmd github.
* woke up to +19% score on a 0.8b model (higher than previous 1.6b) after 8 hours and 37 experiments.
I'm not a ML researcher of course. I'm sure way more sophisticated stuff is being done by real researchers. But its mesmerizing to just read it reasoning its way through the experiments. I learned more from that than months of following ml researchers.
I just asked it to also make a new reranker and its already got higher base than the previous one. Incredible.
Andrej Karpathy@karpathy
I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the prompt (.md) - the AI agent iterates on the training code (.py) The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc. github.com/karpathy/autor… Part code, part sci-fi, and a pinch of psychosis :)
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Xpicker2 retweetledi
Wow — over 2.3k stars and 400 forks of OBLITERATUS already!! 🙏
To say thanks for all the community support, I've squashed a number of bugs and added a new feature... TOURNEY MODE! 🤺🤺🤺
Now, you can battle multiple guardrail removal methods in a bracket-style tournament to find the best technique for any specific architecture. 🏆
You can select different methods to pit head-to-head in multiple elimination rounds, including all the community favorites like FailSpy, Heretic, and Gabliteration. Obliteration Madness!
The winning uncensored model can (optionally) be pushed to Hugging Face with one click 🤗
Happy liberating! 🫶
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Xpicker2 retweetledi
Have your 𝕏 recommendations improved?
Adam Lowisz X Meetup 🇺🇸🇵🇱🇪🇺🇬🇧🇺🇦@AdamLowisz
The Grok algo lately has been fire 🔥
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Xpicker2 retweetledi
Single-GPU, lightweight, autoresearch loops.
One more reason Individual AI becomes inevitable.
Andrej Karpathy@karpathy
I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the prompt (.md) - the AI agent iterates on the training code (.py) The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc. github.com/karpathy/autor… Part code, part sci-fi, and a pinch of psychosis :)
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Xpicker2 retweetledi
an emerging way of doing work
Derya Unutmaz, MD@DeryaTR_
My new Sunday morning routine: 1. Get coffee 2. Check GPT-5.4 projects on the Codex App, continue & start new ones 4. Launch ChatGPT 5.4 Pro for fresh brainstorming sessions 5. Think/learn how to use the 90% of AI capabilities I have yet to explore 6. Drink more coffee
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Xpicker2 retweetledi
Xpicker2 retweetledi
Share your Elegant art
Tomorrow I will repost 4 of my favorites.
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Xpicker2 retweetledi
This is essentially my workflow of coding in production on the server with Claude Code
It's instant and extremely high velocity and I think that's where it's going
AI lets us dev extremely fast and the bottleneck now is slow deployments many of us (not me) still have I think
Sam Hogan 🇺🇸@samhogan
What if a codebase was actually stored in Postgres and agents directly modified files by reading/writing to the DB? Code velocity has increased 3-5x. This will undoubtedly continue. PR review has already become a bottleneck for high output teams. Codebase checked-out on filesystem seems like a terrible primitive when you have 10-100-1000 agents writing code. Code is now high velocity data and should be modeled at such. Bare minimum, we need write-level atomicity and better coordination across agents, better synchronization primitives for subscribing to codebase state changes and real-time time file-level code lint/fmt/review. The current ~20 year old paradigm of git checkout/branch/push/pr/review/rebase ended Jan 2026. We need an entirely new foundational system for writing code if we’re really going to keep pace with scale laws.
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