causal

Yeah Cloudflare offering has become everything I wanted from AWS. So much simpler to deploy a basic full stack app + files. AWS has become considerably more difficult than self hosting.

Yeah I've been saying this for a while: AI-washing any text will degrade it, compounding with each pass.

"Semantic ablation" is my favorite term for it: https://www.theregister.com/software/2026/02/16/semantic-abl...

You are being pedantic to pretend you don't understand. It's tiring and unproductive.

At the end of the day, people are paying money to utilize the servers within the datacenter. That money is revenue. That revenue ought to be taxed by the state.

I find LLMs make me doubt my own ability to produce quality now. I used to jump in and just write code so eagerly, letting it get messy but discovering the shape of the problem in the process.

But AI can produce beautiful, complete, syntactically perfect code on the first pass that makes my code look juvenile.

I mean, it might be wrong for other reasons, but it makes me feel like I'm programming with crayons next to it.

For a datacenter that generates billions, that is not much.

> In general, data centers only pay corporate income tax if they generate revenue. Not all data centers do this because many don’t sell goods or services; they simply house servers. By qualifying as business expenses rather than revenue generators, they reduce the tax liability of their parent companies.

> Thus, when it comes to income tax, at least, many data centers – especially hyperscale data centers owned by large companies – don’t generate tax revenue because they don’t generate direct operating income.

So I was just Googling this, and apparently most datacenters don't pay any state tax on revenue generated by said datacenter? Huge loophole if true, no wonder capital investment in datacenters is so high. [0]

[0] https://www.datacenterknowledge.com/regulations/how-are-data...

As agents get better at code we trust them to produce more of it. There are still bugs to find, but the haystack gets bigger.

So the number of bugs to find remains constant but the amount of code to review scales with the capability of the agent.

Chatgpt.com?

The same way you test the universe for gods. Hence the irony.

There's something richly ironic about a man who famously spent his career demanding hard evidence for the gods so quickly succumbing to AI psychosis.

Disappointing take from Dawkins. Language is a very narrow piece of human intelligence that most animals don't even have, yet I find they seem much more holistically conscious than any LLM.

I mean, the option is not zero productivity or some productivity: it could be negative.

We doubt the productivity because we have enough experience with Claude Code to know that flooding your organization with that many tokens isn't just unproductive, it's actively harmful.

Was the river used for transportation, or did they just put the giant pond of radioactive waste next to a river for funsies

The problem is that your comment and the one you're responding to can both be true: Just because the rules are heavily enforced does not mean the right rules are in place, starting with the fact that Meta is collecting this data to begin with.

There's also a cooldown period on some deletes (like secrets) to make sure you don't accidentally brick something

Even their explanations are often confabulations. Best case they point to something wrong in your prompt or agents files, but usually it’s just noise.

"How" = it can happen

Without "How" = it will happen

> there might be something else more interesting that is neither obvious nor aliens.

Agreed, and I don't think you understood my comment.

Unfortunate if so, but I'm finding plenty of counterexamples in the past day alone: https://hn.algolia.com/?dateRange=last24h&page=0&prefix=true...

"Not aliens" seems obvious but shouldn't be a basis for dismissing this either. I feel like sometimes we are so determined to dismiss aliens that we accept any plausible alternative too quickly, when there might be something else more interesting that is neither obvious nor aliens.

You seem to be going off the title which is plainly incorrect and not what the paper says. The paper demonstrates HOW different models can learn similar representations due to "data, architecture, optimizer, and tokenizer".

"How Different Language Models Learn Similar Number Representations" (actual title) is distinctly different from "Different Language Models Learn Similar Number Representations" - the latter implying some immutable law of the universe.

Title is editorialized and needs to be fixed; the paper does not say what this title implies, nor is that the title of the paper.

9 nines found somewhere after the decimal point if you measure with enough precision

Yeah! It's such a delightful site, I love these sorts of odes to a niche passion I had not yet learned to appreciate.

This is an interesting topic but reporting on what some random people typed or clicked on social media is such a shallow basis for news. It's a subjective narrative of a subjective trend.

Once again random tweets from insiders being the only clues we have to what Anthropic actual policy is

I think it's probably pointing toward the general harm that thinking only in objects has done to programming as a practice

Exactly. Today "premature optimization" almost always means unnecessary infra or abstractions or some other complexity- not DS&A choices.