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IceHegel

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I have always wondered about the origins of the anti nuclear opinion of Germans.

It has Cold War origins to be sure, but what kind?

I suspect American intelligence has been supporting the anti nuclear movement for some time, for non-proliferation reasons - and not just in Germany. I certainly would be, if I ran the State Department.

Claude for Legal 2 months ago

This seems like a shot across the bow for all large Claude API customers, which I'm sure they saw coming.

But still, a TSMC style pure play model provider would win huge business in the space given how many application companies are being eaten by model companies.

I'm surprised more people are not talking about the fact that the two best models in the world, Gemini 3 and Claude 4.5 Opus, were both trained on Google TPU clusters.

Presumably, inference can be done on TPUs, Nvidia chips, in Anthropic's case, new stuff like Trainium.

I despise Facebook and all that it stands for, but if the surplus value that it has extracted from humanity over the last two decades is reinvested intelligently into nuclear energy, I'm actually okay with it.

Despite the hype that you see on Twitter, the hard tech startup scene is actually incapable of large-scale engineering coordination on the level needed for a nuclear power plant, or even a gas turbine.

If any innovation on fission reactors is going to be successfully commercialized, we will need to see billions of dollars of investment over medium to long time horizons.

Of course, the millstone around the neck of nuclear power is that it's a dual-use technology. There's probably a lot more behind the scenes that's been done to stifle the industry effectively for non-proliferation reasons, but masquerading as cost, regulatory problems, environmental concerns, etc.

Given recent high profile redaction events, I think one simple use of AI would be to have it redact documents according to an objective standard.

That should in theory prevent overly redacted documents for political purposes.

An approach that could be rolled out today would be redacting with human review, but showing what % of redactions the AI would have done, and also showing the prompt given to the AI to perform redactions.

Whether or not the patent was actually granted in this case, I have not been able to think of a compelling reason to have patents for software. In fact, I think most intellectual property laws need to be seriously rethought.

If the objective is to maximize investment by protecting successful results, I don't think our system is doing a very good job.

Who can do this with good data controls? I don't want to have to dig through the fine print of some Terms of Service page to figure out if a sequencing company is going to save a copy of my genetic code for possible future use.

I don’t think Rust syntax and patterns (no classes) are especially elegant for many tasks. I can’t express the behavior of a system as cleanly in Rust as TypeScript, C#, go or Python. I know that’s not what it was designed for, but a guy can dream.

But what Rust has is the best tooling bar none(cargo, build system, compile time checks, ease of first use). The tooling is actually more important than the borrow checker and memory safety in my opinion.

If I clone a Rust repo, it’s actually easier to compile, test, and run the code than any other language. It avoided the fragmentation of JS/TS (npm, yarn, pnpm, bun, deno) and dep hell of Python (which was a nightmare until uv).

If Rust didn’t have the syntax warts (macros), it would be eating the world.

The idea that artifacts belong forever to whoever inhabits the land today is going to put under increasing pressure as ancient DNA continues to reveal the number and severity of population replacements over time.

Unless there is a trick that I am missing, I don't think this will work by itself. The fundamental thing is what can the model attend to as it generates the next token.

If you give a summary+graph to the model, it can still only attend to the summary for token 1. If it's going to call a tool for a deeper memory, it still only gets the summary when it makes the decision on what to call.

You get the same problem when asking the model to make changes in even medium-sized code bases. It starts from scratch each time, takes forever to read a bunch of files, and sometimes it reads the right stuff, other times it doesn't.

By batch size, do you mean the number of tokens in the context window that were generated by the model vs. external tokens?

Because my understandings is that, however you get to 100K, the 100,001st token is generated the same way as far as the model is concerned.

There's a chance this memory problem is not going to be that easy to solve. It's true context lengths have gotten much longer, but all context is not created equal.

There's like a significant loss of model sharpness as context goes over 100K. Sometimes earlier, sometimes later. Even using context windows to their maximum extent today, the models are not always especially nuanced over the long ctx. I compact after 100K tokens.

ASCIIFlow 11 months ago

Why is it blurry? If there is one thing I'd expect to be fast and sharp it's an ascii editor.

I really want to like deepwiki, but just looking at the diagrams of repos, they are too handwavy to be useful.

They are a conceptual overview and don’t seem tied down enough to the actual implementation details of a particular project.

Perhaps this could be the improved.

There's a fascinating tension with anti-aging drugs, which is that your preference would obviously be to take them as early as possible, so you spend more time at a younger age as opposed to just prolonging the last years of your life, where you'll be stuck in a nursing home anyway.

But taking experimental drugs while you're young is also much higher risk, and you might see people sacrificing their 20s for the sake of their 70s in a way they end up regretting, even if there aren't any side effects.

Microsoft’s software quality is poor. Azure is extremely bloated and difficult to use, and I suspect only gained market traction due to bundling/anti-competitive tactics. Microsoft inserts tabloids news into its operating system.

GitHub is their most trusted “tech” brand by far, and it has their only successful AI product, Co-Pilot.

It’s almost inevitable that GitHub and all its products will be consumed with Microsoft bloat in the next 5 years as more and more products coast off the GitHub brand.

Expect tabloid news in GitHub products soon.

Open models by OpenAI 12 months ago

Listed performance of ~5 points less than o3 on benchmarks is pretty impressive.

Wonder if they feel the bar will be raised soon (GPT-5) and feel more comfortable releasing something this strong.

Any reasonable understanding of the term "war" obviously includes bombing a country's strategic military sites.

Today Congressmen's main job is soliciting bribes. I expect they want their name on as few pieces of paper connecting them to a conflict as possible. They are not in charge of the government.