Simplifying the world of semiconductor investing in the age of AI. Part of the @semianalysis_ gang. all views are personal
Joined September 2021
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Fabricated Knowledge retweeted
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
Fabricated Knowledge retweeted
"Stocks don't seem to care about higher bond yields over the past month"
The stocks:
Fabricated Knowledge retweeted
DAMN
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
Fabricated Knowledge retweeted
A quick check shows that this list claims to fully solve 90 of the top 500 open problems in math (proofatlas.ai/open-problems/).
The highest ranked would be:
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
Fabricated Knowledge retweeted
ML4 was trained on 3,800 NVIDIA Grace Blackwell GPUs in our European datacenters -- our cluster in Bruyères-le-Châtel built using our Series B fundraise.
We are investing heavily in infrastructure, with our Series C and D clusters coming online soon. This additional compute will let us train longer, pursue more ambitious post-training, and iterate faster.
We expect large and rapid improvements in the weeks and months ahead.
2/n
Fabricated Knowledge retweeted
Mistral is back:
-pushing the frontier on dollar per intelligence (1.13$ per task for a 38. mimo v2.6 pro gets 46 for 0.13$)
-best open model out of us or europe (competition: nemotron 3 ultra 23, gemma 4 17, gpt-oss 12)
-same score as gpt 6 luna. luna costs 0.07$ per task. 16x
-#64 of 225 on artificial analysis. frontier
-1 trillion parameters to land 3 points under GLM 5.3 flash (320B, 0.25$)
-open weights (AA lists it as proprietary. weights oct 27)
-most open license yet (large 3 apache 2.0, medium 3.5 modified mit, this one "custom mistral license")
-only 8 points behind the best chinese open model and 20 behind opus 5.5
-beat glm 5.3 on deepswe, 62 to 61 (on mistrals chart. the live leaderboard has glm 5.3 at ~69)
-state of the art in legal (15%)
-highest cyber score of any model, 82% (opus 5.5 and astra refuse the task and score near zero)
-same blog post brags it refuses more cyber prompts than any other open model
-200M output tokens to run the index, median is 81M. le chonk talks
-+29 points over large 3 (large 3 had 9)
-sovereign ai (they resell glm 5.3 since august. until today the smartest model on mistrals own platform was chinese)
-3 billion euro raised, 21 billion valuation, first model out of it: 38
-"no signs of saturation" (the rl run isnt finished, they shipped anyway)
-the meme promised 30 trillion parameters. we got 1 (49B active)
-europe can compete, said mensch. in abu dhabi
-2nd of 5 in their own blind eval. behind opus 5. not 5.5
Fabricated Knowledge retweeted
Mistral has released Mistral Large 4, scoring 38 on the Artificial Analysis Intelligence Index; France is back to having the most intelligent model from outside the US and China
@MistralAI has released Mistral Large 4 in Research Public Preview, with plans to release the weights of the 1T parameter (49B active) model at the end of October. It achieves 38 on the Artificial Analysis Intelligence Index, comparable to GPT-6 Luna (max, 38) and DeepSeek V4.1 Flash (max, 39). It also achieves 50% on the Artificial Analysis Cyber Index, level with GLM-5.3-Flash and ahead of models such as Kimi K3 and DeepSeek V4.1 Flash (max).
Key benchmarking results for Mistral Large 4 Preview:
➤ Most intelligent model from outside the US and China: Mistral Large 4 Preview scores 38 on the Intelligence Index, comparable to DeepSeek V4.1 Flash (max, 39) and GPT-6 Luna (max, 38). This makes it the most intelligent model from outside the US and China, ahead of countries such as South Korea and the United Arab Emirates
➤ Level with GLM-5.3-Flash on cyber defense capability: Mistral Large 4 Preview scores 50 on the Artificial Analysis Cyber Index, level with GLM-5.3-Flash (50) and behind MiMo-V2.6-Pro (56). Once its weights are released, it will rank among the top three open weights models on the Cyber Index. Its strongest result is on CyberGym-E2E-AA, where it scores 82%, ahead of MiMo-V2.6-Pro (79%) and GPT-6 Luna (max, 78%)
➤ Over 4x the Cost per Task of similar-intelligence open weights models: Mistral Large 4 Preview costs $1.13 per Intelligence Index task with standard pricing of $1.36/$4.18 per 1M input/output tokens, with $0.14 per 1M cached input tokens. For the first two weeks, Mistral Large 4 Preview will be served at a 50% launch discount, bringing its Cost per Task down to $0.57. This is still more costly than GLM-5.3-Flash ($0.25) and DeepSeek V4.1 Flash (max, $0.27)
➤ Strong document and image reasoning: Mistral Large 4 Preview scores 19% on GDP.pdf, on par with MiMo-V2.6-Pro (19%) and behind Kimi K3 (22%). This is an 18-point improvement from Mistral Large 3, partly driven by improvements in their API, which now accepts 100 images per request, up from 8 for previous Mistral models
Key model details:
➤ Context Window: 512k tokens
➤ Multimodality: Text and image input, with text output
➤ Pricing: $1.36/$4.18 per 1M input/output tokens ($0.14 per 1M cached input tokens), with 50% off for the first two weeks ($0.68/$2.09)
➤ Availability: Research Public Preview on Mistral's API, with open weights planned for the end of October
Fabricated Knowledge retweeted
Meet Mistral Large 4, aka Le Chonk.
• 1T parameters, natively multimodal. 49B active.
It is the best open weights model from US or Europe on aggregated benchmarks.
• State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding.
• Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure.
• Available to all via API today. Working with cybersecurity partners privately.
Open weights release end of October.
🤖 Made with AI
Fabricated Knowledge retweeted
Reflection joins the list of Nvidia & Thinking Machines who have released their strongest models and come up behind Chinese counterparts. There's a lot of ways people will overthink this, but the clearest takeaway should be that the Chinese are very very good at building LLMs.
Fabricated Knowledge retweeted
Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active.
- Frontier reasoning efficiency
- Advances the Western open frontier on coding & agentic tasks
- Trained end-to-end from scratch
Full weights release this month.
Learn more about Beam: reflection.ai/beam
Fabricated Knowledge retweeted
BREAKING:
5 hospitals have been closed for quarantines in Siberia due to a possible plague outbreak.
The 28-year-old lab technician Darya Shipilova, died yesterday after breaking a test tube with live Yersinia pestis the Irkutsk Anti-Plague Institute on September 25th while handling samples.
A mask mandate has now been introduced at the huge aluminum plant in Irkutsk.
Some U.S. politicians are now calling for commercial air travel to and from Russia to be stopped until the situation is clarified.
This first symptoms of pneumonic plague typically start about 4 to 7 days after exposure. 200 people are under observation.
Fabricated Knowledge retweeted
Just in:
TSMC sees a path forward in Texas by working with @elonmusk and @SpaceX's Terafab,
@culpium reports exclusively
Read on to see how the venture might play out, and its implications for @intel
culpium.com/p/exclusive-tsmc…
Fabricated Knowledge retweeted
you may ask, why open-source this?
first of all, building gadgets is fun.
second, we want to unleash builders to explore all sorts of new and crazy ideas. we believe muse presents a special moment to imagine new kinds of gadgets, and we are excited to see what y'all build!
🚨 side project alert 🚨
Announcing Muse Gadgets, an open source ESP32 firmware and Linux sdk so that you can make hardware devices that work with Muse.
Grab an API token from gadgets.muse.ai and point your favorite coding agent at the github repo to build your own peripherals for Muse.
lmao this makes me so mad re: the rendering, we are NOT using graphics cards in PCIE bro
I think i tweeted a few months ago saying how come we don't have mac based games yet if AI is so good, and given the recent decomp/recomp from binary for video games... yeah its here
Fabricated Knowledge retweeted
spot the looper
5.6 luna and sol - nope
6 luna and sol - nope
6.1 sol and 6 astra - SUS
