robkop

Worth taking a closer look at what they actually were able to formally verify. No doubt a massive achievement, however after seeing several demos poke holes through it I don’t think they’ve done the level of “formal verification“ that you may be inclined to think they have.

One of the main goals at the moment is to keep thinking human legible. You can imagine how much harder it’d be to do root cause analysis on the recent OpenAI event if we couldn’t even tell what they’re thinking.

Claude design's prompt is trivial to verify. They bundle it in the frontend bundle and send it on every network request.

CoT legibility largely disappears which is quite concerning from a safety perspective

Just saying you’re not alone, very surprised by the reception given how brutally sloppified the OP is.

Interesting problems space but I hope the author just gives dot points next time rather than bloating it and losing most of its meaning.

Could you please elaborate a bit more for my understanding?

What in particular about this method breaks correct token boundaries?

On my first read I read your comment as there are special tokens that require multiple tokens to emit, hence you can't get certain tokens emitted alone - but I don't think that's what you're getting at on a second read?

Interesting that you've found similarities between "d" and the hidden tokens for opening an xml tag, pressing caps lock and the other hidden tokens of note. I haven't run into any trouble extracting "d" tokens, is it a particular model that you see create that pattern?

I use bedrock with 1M context every day. Not sure this is right

A lot of enterprises were doing that but now they hit the 150 user limit on Claude and are paying seat+api rates.

Codex is still going strong but it’s hard to imagine they won’t do similar eventually.

So now im honestly hearing a lot more folk stick it out with cursor while waiting for the dust to settle.

There’s a lot of tradeoffs to play with, those inference ASICs may not carry the gradient but they are still optimised for larger batches and to run any model. They need enough memory for the weights, wide batch inference, and ideally leftovers for kv cache efficiency.

For personal inference you’re given a lot more room to play in - much of it poorly explored today - enough to concern an argument of cost advantages evaporating

You can ablate surprisingly large chunks of a model with near to no effect, you can try this easily - download an open weight model in torch.

Obviously it’s not ideal but you could likely have single digit % of all weights affected and still have a useful model (many caveats here: e.g. locality of damaged weights matters, distribution of errors matters, fail high/low matters, …)

I can’t speak for the states, but in AU I clearly see a massive displacement of undergrad and junior roles (only in AI exposed domains).

I say this as both someone who works with many execs, hearing their musings, and someone who no longer can justify hiring junior roles themselves.

Irrespective of that; if we take this strategy of only taking action once it is visible to the layman - our scope of actions available will be invariably and significantly diminished.

Even if you are not convinced it is guaranteed and do not believe what myself and others see. I would ask you is your probability of it happening now really that close to 0? If not then would it not be prudent to take the risk seriously?

one of their highlights with mythos was it's ability to generate new puns

I took a look and honestly they're the first AI puns that aren't bad

Times are changing

We’ve got a long way to go in optimising our environments for these models. Our perception of a terminal is much closer to feeding a video into Gemini than reading a textbook of logs. But we don’t make that ax affordance at the moment.

I wrote a small game for my dev team to experience what it’s like interacting through these painful interfaces over the summer www.youareanagent.app

Jump to the agentic coding level or the mcp level to experience true frustration (call it empathy). I also wrote up a lot more thinking here www.robkopel.me/field-notes/ax-agent-experience/