CAIO | PhD | Adj. Asst. Prof. @utcompsci | Former AI Resident @OpenAI | CS @StanfordEng | ❤️ Dogs & Lifting Weights
Austin, TX
Joined November 2009
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Fatma Tarlaci retweeted
Just watched the @netflix Instadocs about the @OpenAI cyberattack on @huggingface. Super disappointing, as they went for maximum anthropomorphism of the technology and full doomer mode.
I spent more than two hours with them trying to correct all their mistakes and ground this in reality, explaining that agents are technological systems, not aliens. But it looks like the drive to scare people for maximum views was too strong.
Also, they didn’t mention the lack of containment and monitoring of the agents, how closed-model safeguards blocked our defensive work, or how we defended ourselves with AI using an open model. And that we still lack a lot of information and transparency, including full agent traces and that companies need to remain accountable for what their agents do.
It ends up being a fun sci-fi movie though!
Fatma Tarlaci retweeted
Now I see why some people talk about AGI. This is so clever!
Fatma Tarlaci retweeted
We’re partnering with Accenture on independent evaluation of frontier AI—part of our recent commitment to embed evaluators at Anthropic. Both we and Accenture expect to invest at least $1 billion to build capacity in this area over the next five years. anthropic.com/news/accenture…
Readers added context they thought people might want to know
Anthropic presents this as an "independent evaluation" but will directly fund Accenture's work and has a prior commercial partnership deploying its models, including training ~30,000 Accenture professionals on Claude.
anthropic.com/news/accenture…
anthropic.com/news/anthropic…
Fatma Tarlaci retweeted
we are officially out of stealth! join the frontier and get access to Jev on our website (link on profile)
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
Fatma Tarlaci retweeted
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
Fatma Tarlaci retweeted
We ride
One of NASA's partners in lunar surface construction, Carlos García-Galán, just spent an hour on Houston We Have a Podcast describing humanity's first Moon Base. Phase one alone: more than 20 lunar landings.
Listen for what he says about the surface itself. 3D printing structures from regolith. Lasing regolith to pave a road or smooth a pad so habitats sit on level ground. Printed berms to shield landing sites and shelter a nuclear reactor.
That is not a wish list. That is the work. It is why we cannot ship buildings to the Moon. We have to ship the builder.
At ICON Prime, this is what our team wakes up to do as NASA's industry lead on lunar surface construction. Landing pads, habitats, and roadways built from the material already there.
Apollo got us there. Artemis is how we stay. Worth your commute:
megaphone.link/NATIONALAERON…
Fatma Tarlaci retweeted
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: darioamodei.com/post/we-must…
Fatma Tarlaci retweeted
Dario is right
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: darioamodei.com/post/we-must…
Fatma Tarlaci retweeted
Reasoning from scratch round 2: In this video, I cover the text generation process in LLMs and KV caching (to prepare the base model before adding reasoning techniques in the upcoming ones).
00:00 Introduction and reasoning model demo
01:55 How to work through the book
05:00 Chapter 2 overview
08:25 Checking PyTorch and hardware support
10:26 Apple silicon and MPS caveats
15:00 Cloud GPU options
16:08 Tokens and tokenization
18:20 Qwen3 and the Reasoning From Scratch package
23:05 Encoding and decoding text
26:24 Downloading weights and selecting a device
31:01 Loading the pretrained Qwen3 model
34:32 How LLMs generate text
36:47 Input tensors and batch dimensions
41:48 Running the model in inference mode
44:11 Logits and next-token predictions
49:21 Greedy decoding with argmax
52:28 Building a streaming text generator
01:01:28 Generating text and handling end-of-sequence tokens
01:06:00 Benchmarking text generation
01:14:34 How KV caching works
01:17:22 Adding KV caching and measuring the speedup
01:24:31 Model compilation with torch.compile
01:30:33 Combining compilation with KV caching
01:32:53 Comparing CPU and GPU performance
01:35:32 Recap and next steps
Fatma Tarlaci retweeted
Built a slopmeter into our team server.
You clearly see where we started pushing for more tests.
Fatma Tarlaci retweeted
Banger paper from Google.
If you maintain a skill library for your agents, you might want to check this out.
(bookmark it)
This work separates three things that skill-evolution systems usually collapse into one. Raw execution traces, a persistent wiki of accumulated knowledge, and the executable skills themselves.
Experience gets consolidated into the wiki, and every later skill update builds on that wiki instead of on a scattered optimization history.
Ablations confirm the wiki is what carries a lot of the gain. Two results stand out in particular. Smaller models with evolved skills beat substantially larger models without them. And skills evolved by one model transfer across families, where skills evolved elsewhere sometimes beat self-evolved ones.
Paper: arxiv.org/abs/2608.27454
Chat with Paper: academy.dair.ai/papers/wikis…
Fatma Tarlaci retweeted
Human judgement in engineering is ironically even more crucial now. Deciding what to build. Deciding on the right architectures. Deciding whether you regenerate from scratch $$$ or reuse existing legos. Managing tech debt. You can do anything now, but you can't do everything.
Fatma Tarlaci retweeted
Google Brain founder, Andrew Ng:
"100% of my tasks are done by ai agents, self-improving loops are next.
Give it 3-6 months and prompting is gone."
31 minutes of clear explanation on building self-improving agents from scratch.
Worth more than any $500 agentic course.
Watch it, then read the full guide on loops below.
Fatma Tarlaci retweeted
We’ve designed and built our first AI chip: Jalapeño.
Designed from the ground up by OpenAI and brought to production with @Broadcom, Jalapeño is purpose-built for the LLM workloads powering ChatGPT, Codex, the API, and future agentic products.
Chips are foundational to the AI economy. Building our own expands our full-stack platform from products to models to infrastructure, and will help us scale intelligence, serve more people, and expand access to AI.
