zurfer

I do think it's more subtle. AI can replace very few jobs end to end with the same quality, maybe none. But AI can be put to work on high ROI problems. Now when the new marginal job is not obviously as high ROI as putting another 100k of tokens to work, no human gets hired.

Next, comes natural attrition in a company where a certain percentage will leave every year. Will they get replaced with a human or their budget goes into tokens?

Only when these 2 angles are exhausted, a typical company will start thinking about layoffs.

Now, some companies are already stressed: customer buy AI products instead of theirs, AI makes it easier to build what they offer, customers believe they can vibe code things. These companies will layoff first, because of AI. Not because AI will do the persons job but because the money gets spend differently.

Don't fall for it. Its a trick question. Capitalism made everybody replaceable a long time ago. :P

The more interesting question is: Has the ease of replacibility increased because of AI?

Naive question but if it works best wouldn't companies that have a four day work week outperform theirs peers and because of that grow faster, and become more common?

I see the opposite in most startups that have a 6 day work week to get ahead of the "slowly moving" 5 day work week competition.

Anthropic will probably IPO as well

yeah 3t/s seems human. only that i never wrote code perfectly top to bottom.

Kudos to the team. Please consider making the model available via API!

In almost every wealthy country the birth rate has fallen below sustainable, meaning we're shrinking if life expectancy doesn't magically explode.

Viruses btw never reflect on killing the host :P

Techno optimist here who expects the following to make a big contribution to reducing human made future climate change: better batteries+solar/wind, nuclear fusion, self driving cars (we'll need to manufacture less cars for the same amount of miles humanity drives), AI helping with better resource allocation in general (hopefully).

The answer can't be, let's just consume 10x less. We have to engineer our way out of it.

Maybe, or they use the same smartphones as everybody else. The mass market also wants the best model and will pay accordingly.

Bubble or not, this is great!

It's priced at 1/10, but deepseek is probably not profitable, also it's slow.

Even more interesting is the question if we would have a deepseek model without the US frontier models.

And then what's the value of the advantage that the frontier models have. It's definitely 100x more valuable to find zero days 3months earlier. Probably not in every domain but in enough domains having the smartest model is valuable.

Down voted because the comment is not providing any new insights and is just insulting.

salaries are opex, data centers are capex, you can't compare them in the same timeframe.

4B over 5 years is 20B, which is significant.

lots of great stuff, but the plot in the paper is just chart crime. different shades of gray for references where sometimes you see 4 models and sometimes 3.

this is vibe coded :D. the drop down for Python not working.

I remember when we started working on our teams bot in 2023, Microsoft announced that they will stop supporting Python for the teams sdk, which felt super short sighted. Eventually they silently picked it up again and the old sdk never stopped working.

Kudos for turning it around. I believe it'll last this time as AI agents in communication tools are something a lot of people want. and unlike pre LLM chatbots and agents, they are so much more useful now.

Naive question but are you not afraid z.ai will train on your personal data?

Hmm, if the stock keeps falling that might really happen.

original: https://www.axios.com/2026/04/19/nsa-anthropic-mythos-pentag...

They should just fall back to gpt 5.4. would save me the hustle to setup codex.. :P

Really cool. One thing wonder: Are they allowed to search the internet? If so, how do you filter out results after the vuln got published?

As someone working in the field I have to admit that I'm not familiar with the terms differential storage nor do I really understand what hybrid execution means. Maybe you could describe it both from a simple technical point of view and what benefits it has to me as a user?

You know some people grow up in untrustworthy environments and auto didact their way to something like first principles thinking and depending on things shaking out you might only believe what you've personally seen with your own eyes. And well, earth looks pretty flat in daily life.

> Muse Spark is available today at meta.ai and the Meta AI app. We’re opening a private API preview to select users.

too much pressure. the author deleted the real source code: https://github.com/instructkr/claude-code/commit/7c3c5f7eb96...

it's just not binary. today's world is dominated by capitalistic competition and a lot of people earn a living by competing with their labor. If AI + robots can do the labor better, cheaper, faster, most (90%+) of today's jobs are gone without obvious replacement.

"In this scaffold, several other models were able to solve the problem as well: Opus 4.6 (max), Gemini 3.1 Pro, and GPT-5.4 (xhigh)."

I find that very surprising. This problem seems out of reach 3 months ago but now the 3 frontier models are able to solve it.

Is everybody distilling each others models? Companies sell the same data and RL environment to all big labs? Anybody more involved can share some rumors? :P

I do believe that AI can solve hard problems, but that progress is so distributed in a narrow domain makes me a bit suspicious somehow that there is a hidden factor. Like did some "data worker" solve a problem like that and it's now in the training data?

Buy public openai investors, e.g. Microsoft. It's diluted but easy.

this takes long enough for me to give codex a new try

https://status.claude.com/incidents/jm3b4jjy2jrt https://news.ycombinator.com/item?id=47336889

I liked how it read. Not as a perfectly thought out post but more an ongoing conversation.

These are confusing times for engineers as the automators can now automate themselves away at even greater speed. Reminding ourselves to play positive sum games seems relevant.

The cake is too small to divide with humans and AI. We all feel that. Time to make more cakes :)