Google?

> who invented neural networks

People like Geoffrey Hinton, who was notably at Google Brain from 2013 to 2023?

The people who say Google was ahead were paying attention long before you were.

What gives you an unique perspective and your own voice can be sticking to your thing for a long time and exploring your exact path more deeply than anyone else has. You don't need to take a million random stabs to become "improbable", and there's no reason that should lead to anything authentic.

file:///Users/GermaTW1/BBC%20Dropbox/Thomas%20Germain/A%20Downloads%20and%20Documents/2026/And%20there's%20evidence%20that%20AI%20tools%20are%20being%20manipulated%20on%20a%20wide%20scale.

With the power of LLMs you can Google a standard library function and get an inaccurate summarisation of a Reddit discussion where neither side knows what they're talking about

"No, as one of the top tile layers in the country I can't do that, for your own protection. What if fifty elephants came and wanted to use your bathroom all at once? You'd feel pretty dumb having to reject them instead of me simply automatically adding $1 million to your bill"

e.g. https://en.wikipedia.org/wiki/Cetomimidae

  In early 2009, the Royal Society published an article detailing the discovery "that three families with greatly differing morphologies, Mirapinnidae (tapetails), Megalomycteridae (bignose fishes), and Cetomimidae (whalefishes), are larvae, males, and females, respectively, of a single-family, Cetomimidae."

Although I think the post also self-diagnoses some factors that also help:

  With the Gas Town Mayor, you feel like you’re operating at a special level, a VIP, above all the workers. You are talking to someone important: the mayor of a factory the size of a town. You have access to someone with resources, someone who gets you, someone who appreciates how busy you are.

  Working with regular coding agents just doesn’t give you that special feeling.

Selling drinks in mislabeled containers should warrant a fraud report to your local consumer protection agency. A crowdsourcing app seems like the wrong tool here.

Interesting idea, but the results seem almost suspicious? even accounting for the extra bits used to store the 16-bit start value for each block - ~5% for k=64

The code does funky things, like the encoder updates the reference value for each encoded token, using the non-quantized value! [1] But the decoder just ignored all that. [2] how can this work?

[1] https://github.com/cenconq25/delta-compress-llm/commit/f185f...

[2] https://github.com/cenconq25/delta-compress-llm/commit/f185f...

How much would better would your hire be considering that you managed to check all 1000 of them, rather than just 50?

Assume that candidate fitness is a number normally distributed around 0 (half of them obviously being negative), that both you and the AI can perfectly pick out the best candidate, and that you picked the 50 to interview completely at random. The average actually seems to be around 40% better? Suprisingly decent. Is that improvement worth 1000 man-hours?

So attempt two here: maybe instead of each company sending candidates through an interview, there should be a common gatekeeper. All working age people take the same 1-hour AI interview, and the glorious overseer assigns them to the position they are best suited for.

(An actual answer here is you assess how important it is to get "the best candidate", and you interview enough people to get a reasonable approximation. The hour cost on your side is what keeps you honest. If wasting candidate time is free on your side, you're going to waste 500 man-hours of work for a 5% better result for you.)

Connecting verified humans for a mutually respectful chat is a trust problem that companies like LinkedIn should be creating solutions for, instead of offering both sides automated shovels to shovel slop faster.

Aren't you ignoring the reports of companies receiving thousands of ChatGPT-written resumes, bots sending applications, and interviews with applicants being live coached by AI?

This is a breakdown of trust on both sides.

I strongly assume the long tail is shifting and expanding now and will eventually mostly be software for one-off purposes authored by people who don't know how to code, and probably have a poor understanding of how it actually works.

  - 90 days is a very long time to keep keys, I'd expect rotation maybe between 10 minutes and a day? I don't see any justification for this in the article.
  - There's no need to keep any private keys except the current signing key and maybe an upcoming key. Old keys should be deleted on rotation, not just left to eventually expire.
  - https://github.com/aaroncpina/Aaron.Pina.Blog.Article.08/blob/776e3b365d177ed3b779242181f0045cd6387b3f/Aaron.Pina.Blog.Article.08.Server/Program.cs#L70-L77 - You're not allowed to get a new token if you have a a token already? That's unworkable - what if you want to log in on a new device? Or what if the client fails to receive the token request after the server sends it, the classic snag with use-only-once tokens?
  - A fun thing about setting an expiry on the keys is that it makes them eligible for eviction with Redis' standard volatile-lru policy. You can configure this, but it would make me nervous.

  - none of the "final" fields have changed after calling each method
  - these two immutable objects we just confirmed differ on a property are not the same object

Are any of these statements public, or is this all private communication?

> We are also working with GitButler team to integrate it as a research feature.

Referring to this discussion, I assume: https://github.com/gitbutlerapp/gitbutler/discussions/12274

Just a reminder that "this probably isn't worth replying to" should help a lot. But alas, it would directly reduce precious engangement.