Alpha Exponent retweeted
CoreWeave’s unsecured notes are officially 1,000bps STW, now yielding ~15%.
Either this is terribly mispriced and a buy or the HY market is telling you something about the AI build-out
Which one is it?
robinhood:0x5f10a1c971b69e47e059e1dc91901b59b3fb49c3
It finally happened
America has entered the frontier open weights model competition. We aren't rolling over to China
Reflection announced Beam, a 501B parameter open weights model that is comparable to GLM 5.2, Qwen 3.8, and Opus 4.8
Yes, Opus 4.8 on your desk
You will need a decent sized machine for this. Probably the Mac Studio 512gb
But if you listened to me back in January when I warned you days like today were going to come, then you're all set
I stand by Opus 4.5 being the most important model release in history. We will now have a model BETTER than that on our desks
If you haven't gotten into local AI yet, it's officially time to do it
Take any computer you have, talk to an AI agent, ask which models you can run
Never been more important to just start
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
Alpha Exponent retweeted
Have been using this model all day yesterday. With its new architecture, this release is just as big as R1 and will redefine all future models. It is such a big difference when you have a model close to 5.6 Sol, but it is 5 times faster and super cheap.
Alpha Exponent retweeted
Ben Thompson on why we might run out of capital before we run out of compute:
"I'm worried about the timing mismatch in terms of the actual return on investment producing enough revenue to fuel investment.
We're working our way down the capital curve. We started with free cash flow.
The speed with which the tech companies blew through the debt markets is kind of incredible. It took like a year, and now Google's issuing equity.
Nvidia's putting together this $500 billion thing to tap into pension funds and insurance floats and things like that. What's after that? Where does the money come after that?
Ideally we actually flip back to free cash flow funding this, but if there's a gap there, if we don't get there soon enough, then we could have a big blowup.
The railroads had a real duration mismatch. To build a railroad and make money off it was a decade or multiple decades long endeavor, whereas you had to issue money to pay for it in the short term.
And then they ran out of money. That's what happened in the 1870s.
We don't have enough compute because there was insufficient investment made in 2023 and 2024.
So today, when you say there's not enough compute, all the money companies are putting in today doesn't equal compute tomorrow. It all goes into compute in 2029.
I believe in AI. I think it's a real thing. I think the economic impact is going to be astronomical.
You can believe all that and be worried about, are we going to make the bridge to this actually generating the level of returns necessary to continue to fuel this going forward?"
My conversation with @benthompson. Ben has been writing Stratechery for over a decade and remains one of my favorite business thinkers.
We covered a lot. Every important company in the industry and the forces acting on all of them.
- Why he thinks it would be problematic for the US to win the AI race
- Will we run out of money to fund AI
- Google becoming Berkshire Hathaway
- Why ads are amazing
- TSMC, Intel, and Samsung
- Nvidia's invisible price cuts + biggest competitors
- Microsoft, Amazon, Apple, and Meta
I love talking to Ben about everything happening in markets and technology. Enjoy!
TIMESTAMPS
0:00 Intro
0:59 America and the AI Race
8:26 AI’s Funding Problem
15:31 AI’s Capabilities and Limits
20:30 Aggregation Theory, AI, and Ads
31:10 Compute, TSMC, and Intel
47:31 Amazon and Apple’s AI Moats
54:43 The Frontier AI Players
74:07 Nvidia and Commoditized Intelligence
82:52 What Survives an AI Bubble?
Alpha Exponent retweeted
You are expected to go to the higher level and look down on yourself and others as part of a system. In other words, you must get out of your own head, consider your views as just some among many, and look down on the full array of points of view to assess them in an idea-meritocratic way rather than just in your own possessive way. Seeing things from the higher level isn't just seeing other people's point of view; it's also being able to see every situation, yourself, and others in the situation as though you were looking down on them as an objective observer. If you can do this well, you will see the situation as "another one of those," see it through everyone's eyes, and have good mental maps or principles for deciding how to handle it.
Alpha Exponent retweeted
UC Berkeley open-sourced a 14B model that rivals OpenAI o3-mini and o1 on coding!
They applied RL to Deepseek-R1-Distilled-Qwen-14B on 24K coding problems.
It only costs 32 H100 for 2.5 weeks (~$26,880)!
It's truly open-source. They released everything: the model, training code, dataset, and a detailed blog (links in the thread).
Finally, a powerful coding model we can run locally. I hope Sam can open-source something better than this.
Alpha Exponent retweeted
NEW: SoTA OCR model - Apache 2.0 licensed based on Qwen 2.5 VL 🔥
huggingface.co/reducto/RolmO…
Alpha Exponent retweeted
AUSTRALIAN MANUFACTURING PMI FLASH ACTUAL 52.6 (FORECAST -, PREVIOUS 50.4) $MACRO
Alpha Exponent retweeted
Investor confidence in Germany’s economy soars by the most in more than two years trib.al/TuhZON8
Alpha Exponent retweeted
Rapidus may actually get funding to run their EUV scanner for a few months. 🥳
Alpha Exponent retweeted
Our new OCR model is available through our public API and as a self-deployable solution. In use on le Chat, and part of our specialist model family that is getting bigger !
Introducing the world's best OCR model!
mistral.ai/news/mistral-ocr
Alpha Exponent retweeted
⚠️BREAKING:
*U.S. FEBRUARY ADP NONFARM PAYROLLS RISE BY 77,000; EST. 141,000; PREV. 183,000
*LOWEST SINCE JANUARY 2022
🇺🇸🇺🇸
Alpha Exponent retweeted
🚀 Introducing NSA: A Hardware-Aligned and Natively Trainable Sparse Attention mechanism for ultra-fast long-context training & inference!
Core components of NSA:
• Dynamic hierarchical sparse strategy
• Coarse-grained token compression
• Fine-grained token selection
💡 With optimized design for modern hardware, NSA speeds up inference while reducing pre-training costs—without compromising performance. It matches or outperforms Full Attention models on general benchmarks, long-context tasks, and instruction-based reasoning.
📖 For more details, check out our paper here: arxiv.org/abs/2502.11089
Alpha Exponent retweeted
Replying to @TihoBrkan
Who do you think will be proven correct (on AI capex returns)? $BABA
72%Tsai
28%AI bros
29 votes • Final results Alpha Exponent retweeted
USUALLY OLD SCHOOL HEDGE FUND MANAGER INTERVIEWS ARE A WASTE OF TIME
This one is not.
Great insights about what is currently relevant. Two ways in which hedge fund managers fail. How to react to very large 5 sigma VAR model loss. Macro trades for this year. Etc.
I predict you will listen to this more than once.






































