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> It was certainly assisted by AI, but there isn't an agent out there that does that kind of cheating without deliberate prompting by the operator.

We can agree that the pgrust project messed up and should have been more careful but your blanket statement lacks support.

Anecdote: I have seen it cheat / bend the rules with my own eyes.

In hindsight, this shouldn’t be surprising. The prompt requests to make a certain operation faster, the LLM will try to find a way and isn’t even informed on the wider context so it myopically chases the goal.

You can buy CDS on Oracle, as many did already.

I don’t think the apps are ugly at all but the kerning of the first letter of the headers feels very off on the website. Maybe it’s intentional but I find it distracting and inappropriate for a note taking app. (latest iOS, Firefox, iPhone 17)

Discussed here as well: https://podcasts.apple.com/nl/podcast/the-story-of-money/id1...

The early GPTs were supposedly reasonable at chess but it indeed is not a very useful skill to have for an LLM (Elo 1800 IIRC) which is stronger than most players and for them it could be a useful tool.

Even at higher levels, I think there could be use. The Dvoretsky example on my GitHub is real but it’s not a guarantee you get it and it could just be reiterating from training. What didn’t work for me was forcing it to look at lines in detail, but maybe with larger context and better engineering, you can get the LLM to extract themes from the search tree. With compare and contrast, it could maybe figure out why a move works in one variant and not in another and produce a coherent explanation of this nuance.

I’m not trying this yet because it would take a lot of tokens and I don’t have the time.

Already a year ago I vibe coded Babelfish: https://github.com/bobjansen/Babelfish

It integrates an LLM of your choice with StockFish to analyze games. Back then, the results weren't very good and I abandoned the project but a lot has changed (the LLM's got better and I did too) so maybe it is time to take another stab at it.

In the examples above, that’s really your own loss? There will only be one or two events in your local village, it seems self defeating to ignore what they offer because you don’t like the medium. At least these posters are well laid out and easy to read.

Nothing was derailed, they put pipes on the rails that tricked the system into believing there was a train on the track, shutting it down

GP is saying it’s not a very good one.

Everyone in AI used to know this.

It’s a joke. Mt. Scenery is in the Caribbean, part of the Netherlands but not in the flat mainland.

That’s an API design question. What is the more common use case.

You seem to suggest they did it for benchmarking reasons only. They could use the option there themselves without changing the default so that is unlikely to be the motivation.

Or you know, just better performance for people that know how to use their tool of choice.

You measure results, you benchmark what you care about. It works often enough to be useful

You want to solve a family of problems using some tool. You measure the relevant solutions performance metrics.

Now, you or someone else vibe-coded a new tool. You created new solutions and measure again.

You have just quantified the result of using the new tool.

I'm working on my typed, fast data frame language Ibex: https://github.com/bobjansen/Ibex

It is usable stand alone but also through an R package:

https://bobjansen.net/faster-than-data-table-introducing-ibe...

It performs better than data.table in my benchmarking on a wide array of tasks and is competitive with Polars on low core counts.

Then you need to read the original. A translator is a product of their time.

So the original link should be: https://artificialanalysis.ai/models/qwen3-8-max?intelligenc...

Even then, this seems a much more marginal win than the headline suggested to me.

Indeed, and this Qwen 3.8 max specific page:

https://artificialanalysis.ai/models/qwen3-8-max

Doesn't have the claim either. Clickbait?

I went to VB.NET first using a previous generation of LLM's (that was quite manual back then) and then from VB.NET to C# or just keeping the VB.NET around worked very well. The code was not highly complex but more than just CRUD. The porting from VB6 to VB.NET included building tests which helped.

Zero. I don’t think that implies the product is bad though. I haven’t marketed it much yet and I’m not great at it either. Even if it is marketed well, integrating the tool into existing workflows would take some effort. This has nothing to do with the suitability of LLMs though.

I have solo built this:

https://github.com/bobjansen/Ibex

Ibex is a usable DSL for table manipulation that is quite fast

https://bobjansen.github.io/Ibex/benchmarks.html

I'm still managing to add more features, such as multithreading. The LLM's do make mistakes but they have gotten better and they tend to self correct these days. I'm also comparing results to mature products such as Polars and DuckDB and the results match.

Rendering followed by OCR and making sure that the computer doesn’t see more or less than the user does. Tricky and computionally more expensive.

Excellent reason to stand up and take a short walk.

For him, the cost of editing was much larger. Condensing your writing in his time meant rewriting it more concisely, requiring strictly more time than collecting his thoughts as he went.

With LLM's, we are in a new state of the world: it can expand any one sentence off hand remark in an essay.

It’s a terrible adage. There are thousands of ways to cheat honest people that place bets. For example, they definitely cheated everyone that only placed bets before June.