Comments URL: https://news.ycombinator.com/item?id=44746507

Points: 4

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=44587958

Points: 2

# Comments: 0

It seems to me that these comments stem from the DeepMind results from last summer[0] and February this year[1]. As I understand it, the models they're using for these tasks are very specialised to the task and also only accept formal language as input (i.e. not a textual or visual representation that a large multi-modal model could use).

I was having a read through the Proof or Bluff paper[2] this morning and while I don't think it's been reproduced yet, they found that none of the tested SOTA LLMs were able to make any meaningful progress (none scored over 5%) on solving questions in their test set. This corresponds with my limited experience in using LLMs for similar tasks. Needless to say I've not heard a peep about this paper from my AI safety friends.

My question is: How should I interpret the above? Maybe it's too cynical but my current thesis is that the DeepMind results are convenient headline-grabbers for the AI safety crowd, who are conflating the performance of a task-specific model with more general LLMs in order to make an unsubstantiated claim about progress in generalisable AI. Is that reasonable? What am I missing?

If the authors of Proof or Bluff are in here I'd also like to say thanks for doing the work on this. I can imagine that work like this isn't the sexiest but it is so refreshing seeing people take the time and care to generate some hard data about how good these models actually are. As someone considering a career switch at the moment, data like this is really useful context when trying to evaluate what the next few decades might look like.

[0] https://deepmind.google/discover/blog/ai-solves-imo-problems-at-silver-medal-level

[1] https://techcrunch.com/2025/02/07/deepmind-claims-its-ai-performs-better-than-international-mathematical-olympiad-gold-medalists

[2] https://arxiv.org/abs/2503.21934v1

Comments URL: https://news.ycombinator.com/item?id=44432486

Points: 1

# Comments: 0

The fact that we're no closer to doing this than we were when chatgpt launched suggests that it's really hard. If anything I think it's _the_ hard bit vs. building something that generates plausible text.

Solving this for the general case is imo a completely different problem to being able to generate plausible text in the general case.

I see the benefits (I've have seen some absolute Java ee monstrosities that would be impossible to build in Go) but why am I getting paged at 3am because someone forgot to set a field on a struct. Similarly all the codegen to workaround the lack of inheritance - who cares how fast the compiler is if you've got to do 30s of codegen on top.

Having said that I cannot understand where the idea that "the [Go] libraries and ecosystem are so much better" comes from. The average quality of both the JDK libs and the popular 3p libs (Jackson, Jooq, even ...Spring) are one of the things I miss most about writing for the JVM and I'm yet to come across another ecosystem that comes close.

I wanted to open source this notebook as I think the data in here is useful, it's in a format that let's you drill-down per-postcode, adjust for inflation and let's you compare against the S&P.

It's pretty basic but I've found it quite useful and hopefully you do too.

Comments URL: https://news.ycombinator.com/item?id=42006339

Points: 1

# Comments: 0

Thanks, H

I'm the CTO of an early-stage saas company in the UK and we're starting operations in Nigeria. We are totally focused on building out the team there with a dedicated hiring function (the first thing we learned about doing business in Nigeria is that whatever you're doing, you _have_ to know someone to get it done right) but we'd like to get moving fast and start hiring some Nigerian tech talent.

My question is, outside of Andela/Toptal/etc. (which we're trying to avoid) could anyone recommend any platforms/jobs boards/other approaches for tech hiring that might be good places to start. Linkedin and Indeed look fairly decent but another thing we've learned about Nigeria is you don't know unless you know.

Thanks and happy to chat to anyone else doing or looking business in Nigeria, would love to hear from you.

Henry (henry@nanumo.com)

Comments URL: https://news.ycombinator.com/item?id=33264541

Points: 3

# Comments: 2

All feedback useful, henry.course at gmail or get me on Github. Happy hacking.

Comments URL: https://news.ycombinator.com/item?id=28938223

Points: 2

# Comments: 1