thomasahle

duping is a great way to show people that even the app layer can be commoditized

Everyone is already cloning the app layer. There are 30+ claude-code clone, and codex work already cloned cowork, grok and gemini is doing the same.

Whereas in the US you only need to go through fingerprinting only once

Once for each arrival.

as long as China doesn't enter the GPU/RAM race

China is obviously in the GPU/RAM race. Heard of Huawei, Moore Threads, Lisuan Tech, CXMT?

Yes, but then it should be easy to check of the result you see match the reasoning you see

TIL:

Many providers build their proxy pools by partnering with device owners who agree to share their bandwidth, while others use embedded SDKs in free apps or VPNs.

WTF. That's just botnets.

Source: https://www.fbi.gov/investigate/cyber/alerts/2026/evading-re...

I got into YC, immediately got a 6M offer from Google, sold and won.

Do you have a source for this, or just rumors?

The responses I get from pro don't feel like ensembles. They are often very one directional.

I used to part time for the (Danish) mail service. The only sorting that was done automatically was the post codes. That was enough to get the letter to the right post office. The rest was done by the mailmen/women early in the morning. It was a lot of fun trying to figure out what was meant by some of the addresses. The older people in particular often knew the story of why certain places were sometimes addressed in certain ways, or could guess the addresses based on the names of the people living there.

After reading the article, the main "case against geometric algebra" I could find in there was that the author does not like the people using/doing research in geometric algebra

Mathematics is a social activity. The research cultures of different branches matter.

Why do you need individual data for gerrymandering? Don't you only need area level?

Ban it from the dataset, add it to the analysis. You can choose your own flavor of noise.

Not sure exactly what you're proposing, but if the noise is added independently to different people, you can just buy multiple copies to reduce it.

There are a lot of ways to do this wrong, which is why so much analysis has gone into differential privacy.

Deepmind and OpenAI have offices in Europe. But I don't think Anthroipc does?

I recently built a very large test bench for System Verilog.

I ran a bunch of different compilers on it, including some open source ones.

Some of them failed some tests, and it was natural to have my LLM (Claude Fable 5) root-cause the issues, and to double-check my test bench wasn't to blame.

But now I stood with all these patches that I couldn't just throw at the upstream maintainers all at once. I ended up just filing a few issues and moved on to other things.

It felt weird to just file issues when my LLM had already spent a lot of time root-causing and fixing the issues. But then, maybe they could just have their LLMs do the same.

Still not sure if it was the right call?

The rate of fundamental, broad-based breakthroughs lifting all LLM applications has clearly slowed with many of the most impactful recent discoveries being in scaling, optimization, tuning and productization toward specific domains.

To me it definitely feels like it's still accelerating, with the most impactful recent discovery being RL training reasoning models (late '24, early '25).

There's an interesting article called "sigmoids won't save you" https://www.astralcodexten.com/p/the-sigmoids-wont-save-you which argues that (unless you have privileged information) you should always assume a process will continue about as long as it’s continued already. (Lindy's Law)

With that in mind the current disruption should last another 10-15 years (assuming it started in '10 or '17.)

Is my website broken?

I'm trying to recreate all the commercial EDA stack in open source. (RTL simulators, synthesis, formal proof tools, etc.)

Building compilers has a _lot_ of parallel tasks agents can work on.

Wish me luck..

He used 600B tokens in 30 days.

I use more than 150B/month with just 15 codex accounts.

60 accounts is "just" $12,000/month. So Peter could "save" 100x by using monthly accounts.

Of course, he doesn't have to, as he works at OpenAI now.

I'm currently choosing between the right formalization for a big hardware project.

I'm considering between SVA, TLA+ and Lean. With the former being more domain specific and the later more general.

Do you think we'll move towards "Lean for everything" or do domain specific formalisms still make sense?

The human savant will remember where they read it and give you credit. It might lead more people to read your work, and ultimately you make money.

The AI won't even know where the page of text it's seeing came from, and people will avoid your book as they can just ask the AI. So you make less money. (Talking about specialized technical books here.)

Does it run on Nvidia or Huawei?

In 1983 David DeWitt (https://en.wikipedia.org/wiki/David_DeWitt) published benchmarking results showing poor performance for Oracle databases. Larry Ellison wasn't happy with the results and it's said that he tried to have DeWitt fired.

Given how difficult it is to fire professors when there's actual misconduct, the probability of Ellison sucessfully getting someone fired for doing legitimate research in their field was pretty much zero. It's also said that, after DeWitt's non-firing,

Larry banned Oracle from hiring Wisconsin grads and Oracle added a term to their EULA forbidding the publication of benchmarks. Over the years, many major commercial database vendors added a license clause that made benchmarking their database illegal.

See also: https://web.archive.org/web/20160719145221/http://sqlmag.com...

This is crazy car-centric legislation.

Now, instead of letting car owners pay for the public space they use (street parking), you are forcing anyone without a car to waste their own private space, in case somebody wants to park there.

Or, you know, they will have improved the safe guards

Good musicians care about music theory / “first principles” as much as good writers care about language theory / grammar.

I don't know anyway using these models everyday who think they are hitting a ceiling.

If anything there's a plateau between each model release.

It's hard to train models in the open. All the big players are using lots of "dodgy" training data. Like books, video, code, destinations. If you did that in the open, the lawyers would shut you down.

Sorry, I said that wrong. Estrin's doesn't reduce the number of multiplications.

Did you try polynomial preprocessing methods, like Knuth's and Estrin's methods? https://en.wikipedia.org/wiki/Polynomial_evaluation#Evaluati... they let you compute polynomials with half the multiplications of Horner's method, and I used them in the past to improve the speed of the exponential function in Boost.

We scaled on "virtually all RL tasks and environments we could conceive." - apparently, they didn't conceive of pelican SVG RL.

I've long thought multi-modal LLMs should be strong enough to do RL for TikZ and SVG generation. Maybe Google is doing it.

To encourage female participation and representation. Most people think it would be good for chess long-term to have a larger female player base.