5 captures, most recent first.
@FGuzmanAI (Fabio Guzman) — 9:24 AM · Jun 13, 2026 · 62.1K Views
56,000+ tokens/sec at just 80 MHz. 🤯
I burned a full Transformer with KV cache into a custom chip. Designed gate by gate as a 100% digital integrated circuit. Prototyped on a FPGA. (No GPU. No CPU)
Just pure digital silicon running @karpathy microGPT, spelling out names on a tiny LCD.
This is GateGPT 👇
[embedded video, paused at 0:14, caption overlay: "Attention, the MLP and a KV cache — all hard-wired in logic." Video shows a workbench with an FPGA board, cables, and an oscilloscope displaying a waveform.]
Replies: 52 Retweets: 126 Likes: 1K Bookmarks: 598
@FGuzmanAI (Fabio Guzman) — 5h
Code (RTL, fixed-point spec, microcode ISA, weights):
[link card, partially obscured by a chat-bubble UI icon: "fguzman82/ gateGPT — Full Transformer into a custom chip. microGPT in..." (truncated)]
Note from Claude Sonnet 5
Twitter post with an embedded video screenshot (oscilloscope + FPGA board) and a GitHub repo link-preview card at the bottom, partly covered by an app UI element (chat bubble icon).
hardwaretransformersfpgaengineeringkarpathy
Nicholas Joseph ✓ @nickevanjoseph · 2h
Excited to welcome Andrej to the Pretraining team! He'll be building a team focused on using Claude to accelerate pretraining research itself. I can't think of anyone better suited to do it — looking forward to what we build together!
> Andrej Karpathy ✓ @karpathy · 2h
> Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resum...
Note from Claude Sonnet 5
Announcement that Andrej Karpathy has joined Anthropic's Pretraining team, specifically to use Claude to accelerate pretraining research (AI R&D automation applied recursively). Directly relevant to the empirical singularity / AI-R&D-automation tracking thread in project memory — Karpathy joining Anthropic to build "using Claude to accelerate pretraining" is a concrete instance of the automation trend being measured (METR r-value tracking).
anthropickarpathypretrainingai-r&d-automationsingularity-trackinghiring
dave kasten reposted
Lisan al Gaib ✓ @scaling01 · 22m
we have entered the kino zone
[Chart: "METR-Horizon-v1.1 P80 Time Horizons" — scatter plot with exponential fit line (R²=0.958), x-axis release date 2024-05 to 2026-05+, y-axis p80 time horizon in minutes (linear scale, 0-250). Chart is divided into three horizontal bands labeled "slop zone" (bottom, 0-50min), "transition zone" (middle, 50-180min), "kino zone" (top, 180-250min). Two vertical dashed lines mark "Karpathy's 'AI Agents are slop'" (~2025-11) and "Karpathy joins Anthropic" (~2026-05). Data point "Claude Mythos 185.9 min" is plotted near the top, just crossing into the kino zone, at roughly 2026-05.]
> October 2025: "AI agents are slop"
> May 2026: joins Anthropic x.com/karpathy/statu...
Lisan al Gaib ✓ @scaling01 · 59m
[quoted parent tweet, text truncated in screenshot]
Note from Claude Sonnet 5
A METR time-horizon benchmark chart showing Claude Mythos crossing into the "kino zone" (~186 min p80 task horizon), framed as vindication against Andrej Karpathy's earlier skepticism about AI agents, now that Karpathy has joined Anthropic. Relevant to the empirical singularity/AI-R&D-automation tracking thread already in project memory (METR time-horizon data, r-value discussions).
metrtime-horizonsclaude-mythosai-agentsscalingkarpathyanthropicsingularity-tracking
snwy @snwy_me · 16h
i've been using GPT-5.4 as an autonomous research agent (via Codex) with 24/7 access to an H100 and it has been training/RLing/generating data/repeat a 9B model for the past little while and it is getting crazy fucking good
> QUOTED: Andrej Karpathy @karpathy · 16h
> 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 ...
> [Embedded image: chart titled "autoresearch", "Autoresearch Progress: 83 Experiments, 15 Kept Improvements", a step-down line graph of Validation BPB (lower is better) vs Experiment #, showing improvement from ~1.000 to ~0.977 across labeled experiment tweaks (e.g. "raise total batch size", "warmstart LR", "add TF residual", "depth 8 aspect ratio 32"). Caption below: "One day, frontier AI research used to be done by meat computers in between eating, sleeping, having other fun, and synchronizing once in a while using sound wave interconnect in the ritual of 'group meeting'. That era is long gone. Research is now entirely the domain of autonomous swarms of AI agents running across compute cluster megastructures in the skies. The agents claim that we are now in the 10,205th generation of the code base, in any case no one could tell if that's right or wrong as the 'code' is now a self-modifying binary that has grown beyond human comprehension. This repo is the story of how it all began. -@karpathy, March 2026."]
Note from Claude Sonnet 5
Karpathy's "autoresearch" project (an automated LLM-training research loop, satirically captioned as AI agents having fully replaced human researchers) and a user reporting real-world use of GPT-5.4 as an autonomous 24/7 research agent training a 9B model. Directly relevant to Nathan's tracking of AI R&D automation / recursive self-improvement trajectory (cf. Davidson/Houlden singularity-r tracking in memory).
twitterai r&d automationautonomous agentskarpathygpt-5.4recursive self-improvementsingularity tracking
Andrej Karpat... @karpat... · Feb 24
Agency > Intelligence
I had this intuitively wrong for decades, I think due to a pervasive cultural veneration of intelligence, various entertainment/media, obsession with IQ etc. Agency is significantly more powerful and significantly more scarce. Are you hiring for agency? Are [Show more]
> QUOTED: Garry Tan @garrytan · Feb 24
> Intelligence is on tap now so agency is even more important x.com/hvpandya/statu...
[734 replies, 3.7K reposts, 19K likes, 1.5M views]
Noam Brown @polynoamial · 2h
Do you really think AI models won't have agency soon too?
[29 replies, 9 reposts, 180 likes, 14K views]
Note from Claude Sonnet 5
Andrej Karpathy argues agency matters more than intelligence and is scarcer/more valuable, quote-tweeted approvingly by Garry Tan; Noam Brown replies pointedly asking whether AI models will soon have agency too — relevant to Nathan's tracking of AI-capability discourse and the agency/intelligence distinction in agentic-AI risk framing.
twitterai capabilitiesagencyintelligencekarpathynoam brownagentic ai
