zer00eyz

> As I grow in my career, on a day to day basis I feel like I'm failing or doing things badly.

This is one thing that we should lament about AI generating all the code. You never get to look back at your own "hand crafted" work with the distance of time. Progress or perspective, it does not matter, one would probably find something they could have done better.

I think I'm actually going to miss that feeling.

All I could think of when I looked at that is "Oh this is gonna be how Nvidia's chart looks some day soon(ish)"

> worse experience

This too is subjective.

No one designs for users any more. It's all gas no breaks on the path to enshitification. A lot of this is the motivation of the people building software.

Raise your hand if you ever saw a PM get promoted for removing a bunch of bad and/or unused features?

LOL

My first program was in 2nd grade on an Apple IIe in basic. It was a program to check if a word was worth a dollar (a=1, b=2, c=3...)

It became a family activity (every one taking turns at the computer) every night to just type in words and see what they came out to. It was all very boring.

I was sure I was going to win.

I lost (well 2nd place), to the kid with 6 older brothers, who had that many years of building out the family list.

> For any application at scale it'd be way more accurate to have a dedicated classifier

"at scale" or the above use case of "specialized domain"

Jev being cheaper than an a full LLM call creates places where other tools might work better later - when the volume or the available data warrants it.

System optimal, code optimal and cost optimal aren't always aligned. Pick the right tool for the job - and dont get married to it. On occasion worse is better, and moreso when your testing or it is a one off/disposable.

Caring about something also means you don't want the issue to be misrepresented.

This is the most effective altruist anti AI headline you could get out of this story.

250k trees seems like a lot from you looking out your window. From the perspective of trees we cut down every year (that we account for) it is close to a rounding error. This is a place where they take forest management seriously - and thats the only reason any one even noticed or had to get a permit.

Anthropic: Touch too much security stuff and we ban you, and keep your money.

Kimi: We took out the worst of it so have at it for free.

Everyone else: Back to my ablated model on openrouter for 1/10th the price where I can brute force issues.

> Oof - it's not like goodfire - we have quantitative results and a clearly defined method!

Goodfire is a discovery from research, an ahaha moment.

"concept elements" would have been a better descriptor in both cases. The V for the cats and the cars, and for your idea.

> 16,068 LLM ... The Coherence Model is a 42.8M-parameter transformer trained

My question is this: was this the smallest model you could train on the 16k papers? Isn't there an optimal small size to identify everything that is common?

Wouldn't it make more sense to use such a model to strip OUT the commonality? Get rid of everything where the "existing distribution of expertise and collaboration networks" are already optimal - and what's left is the novelty?

Ultimately I would be curious to see if your existing "atoms" happen to follow Zipfs law...

> and stopped getting talked about a few days later? Yes.

No one was talking about PHP last week either. Till we all got a reminder that a massive chunk of the web is still happily running on it.

Being talked about is a terrible metric for anything other than how much people are talking about something.

If you're going to do this: start with: Dostoevsky, Tolstoy, and "Doctor Zhivago". These are the Poe/Twain/London for Russia (to some extent).

I highly reccomend Russian film as well: Stalker and Solaris (Not Cloonie, the Russian version) are also great. I have a bit of a love of Sci Fi, may not be your tastes.

You should also hunt around for anything and everything you can find on early Russian computing, Cybernetics, their efforts and thoughts on central planning, and the ternary computing projects they did.

> “Formally verified” does not mean “bug-free.”

Is formal verification the path forward? Meh... I dont think so. Does it have applications in some areas: yes. But this is just more robust "unit testing".

Anthropic keeps trying to convince you that "one agent" will do the job. It does so with the statement "We built 36 small verification tasks from real OSS-Fuzz code. Opus 5.5 proves half of them with about 40% fewer tokens than Opus 5. We expect this trend to continue as models are trained on long verification tasks."

But this is not the path forward. Robust E2E, durable (can your app go from python to rust with out loosing tests) Simulation/Emulation tests are the way. This is an "in bulk" and "brute force" activity. Go look at TigerBeetle for an example of this in practice. Go look at how oxide is doing testing.

Can a swarm of cheaper agents write these tests more effectively that Anthropics premium products. I assure you that it can.

If you look at OAI's actions (hugging face hack) and anthropic own publication on its version control AI is not a best of breed solution its a brute force hammer at it till you get what you need solution.