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The dog ships faster because it has zero opinions about the architecture.

Good point

Agreed on ZLUDA being the practical choice. This project is more impressive as a "build a GPU compiler from scratch" exercise than as something you'd actually use for ML workloads. The custom instruction encoding without LLVM is genuinely cool though, even if the C subset limitation makes it a non-starter for most real CUDA codebases.

The filter used to be effort. You had to care enough to spend weeks on something, which meant you probably understood the problem deeply. Now that filter is gone and we get a flood of "I prompted this in 20 minutes" posts where the author can't answer a single follow-up about their own code. The interesting Show HNs still exist, they're just buried under noise.

The 8% one-shot number is honestly better than I expected for a model this capable. The real question is what sits around the model. If you're running agents in production you need monitoring and kill switches anyway, the model being "safe enough" is necessary but never sufficient. Nobody should be deploying computer-use agents without observability around what they're actually doing.

The "native multimodal agents" framing is interesting. Everyone's focused on benchmark numbers but the real question is whether these models can actually hold context across multi-step tool use without losing the plot. That's where most open models still fall apart imo.

That 95% payout only works if you already know what good looks like. The sketchy part is when you can't tell the diff between correct and almost-correct. That's where stuff goes sideways.

Skills are great for static stuff but they kinda fall apart when the agent needs to interact with live state. WebMCP actually fills a real gap there imo.

Agent teams working autonomously sounds cool until you actually try it. We've been running multi-agent setups and honestly the failure modes are hilarious. They don't crash, they just quietly do the wrong thing and act super confident about it.

Hi everyone ! Super happy to release this package. We feel like Evals belong in the CI like unit testing, and should be easy to setup and run automatically. Can't wait to get your feedback !

Free guide, enjoy ! Made with by the Basalt team

Love it. AI is actually really better at judging the quality of content than it is at producing content. Kind of like humans actually :)

This makes total sense. When a country is creating public software, it should be open source by default. This is the only way to create trust. In the long run, open source and closed source government software will probably differentiate dictatorships from democracies

I think it's more a guideline principle for public software, for exemple apps that are used by citizens to declare taxes, renews IDs...

France has an undeserved bad reputation for this stuff. As a french citizen, I'm amazed to see how easy it has become to do anything administrative online, with great tools such as France Connect that allows a single login method for any administrative tool.