supermdguy

The administration promised they'd find a cause by September 2025. I guess that was the best they had at that point?

https://www.cbsnews.com/news/rfk-jr-cause-of-autism-research...

“Do you know what the industry term for a project specification that is comprehensive and precise enough to generate a program?

Code. It’s called code.”

- CommitStrip (https://www.reddit.com/r/ProgrammerHumor/comments/1p70bk8/sp...)

I think if you’re doing it right, the core of your code should be the simplest expression of the underlying business logic. Of course there’s always going to be supporting layers, and maybe those don’t need to be reviewed. But if you haven’t read the code, there’s an extent to which you don’t know the business logic.

We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed.

This is really exciting. I work on voice AI, and we're still using 4.1/4.1 mini since none of the frontier models come close on latency. I'm excited to be able to have more interactive experiences, I think it'll unlock new ways of working with these models.

Agreed, there were also a few where I deduced the correct definition by comparing the options.

One trick I’ve used is creating a folder and then adding a .gitignore inside it with *. Then nothing in that folder gets tracked, without needing to add anything to the public gitignore. Didn’t know about .git/config though!

I agree that current memory systems are pretty bad, and I think that’s because memory is a prompted behavior instead of a learned one. In theory, if memory was an emergent behavior instead of a prompted one, it would be a lot better.

I think you’re right that changing its own harness would be bad and skew towards prompt engineering instead of learned behavior. So maybe instead it could start with a harness with memory CRUD tools and then learn how to most effectively use them.

I think good taste is objective to an extent, especially given a particular production context.

Someone posted a tool that does this recently: https://news.ycombinator.com/item?id=47140042

There was a show HN for something similar a couple months ago[0]. Looks like they shut it down. Probably too difficult/low-margin to run as a business, but I think the co-op model you mentioned has potential.

[0] https://news.ycombinator.com/item?id=47639779

It's interesting because their last model series (Phi) was based around the thesis that high-quality synthetic data is better than a large pre-training corpus.

I think the conduit exception still applies for analog faxes. Which makes no sense, since tapping a fax line is probably way easier than compromising a data center.

Apparently from a third party seller in New York....and tastes really bad. I was surprised steak could be safely mailed in such normal looking packaging!

https://www.delish.com/food/a70539084/temu-meat-review/

Interesting to see this after the recent post about Chrome’s on-device model using up 4gb of storage, which frustrated a lot of people [1].

I agree local models are great, and it’s cool that Apple has models built in now. But I feel like it basically has to be an OS level feature or users are going to get upset. I’d certainly rather have a small utility call out to OpenAI than download its own model.

[1] https://news.ycombinator.com/item?id=48019219

Better auth is great! I love how it's way more hackable than using a something like Clerk. We were able to add a plugin to allow auth via iframe postMessage (embedded in a CRM) and everything worked seamlessly.

I've used it off and on over the last month or so. For more complicated tasks (30+ minutes) it works well, and seems to replace a lot of prompting that I'd normally need to do (e.g. asking questions about requirements, creating specs and implementation plans, staying on task). For simple tasks, it tries to do too much and gets in the way.

There’s a really good analysis here: https://www.lesswrong.com/posts/LBC2TnHK8cZAimdWF/will-jesus...

The Yes people are betting that, later this year, their counterparties (the No betters) will want cash (to bet on other markets), and so will sell out of their No positions at a higher price.

Overall, I'm really impressed by what you accomplished! I'm not a researcher, so not sure if this is that helpful, but here are some thoughts:

- I wonder if the "move" action is difficult for the model to learn to use well. The model sees token location as positional encodings in the embedding, not sparse character offsets. Would be interesting to see something more like "jump to next/previous [token or set of tokens]". Or maybe a find/replace like most coding harness edit tools use?

- I'd move the exact training data generation details to an appendix. Could be summarized to improve the flow of the paper.

Cool concept! I think the hardest part will be getting people in the target audience to use it. A lot of indie hackers make software for other indie hackers, but that isn't true of most other verticals. And honestly building software for indie hackers feels like a losing battle. Any ideas of how to incentivize none-builders to rank projects?

From the most recent comment, looks like this is a bug, triggered by the system inadvertently activating an internal release tool [0]. Still a pretty wild bug, but not as dramatic as the title suggests. Which is kind of unfortunate honestly, the chaos of every gas town instance automatically contributing to itself would be beautiful to see.

- https://github.com/gastownhall/gastown/blob/main/internal/fo...

Next step is to build an analog scientific calculator with only EML gates

Bizarre reading the thread, it feels like their Claude responding to the other posters’ Claudes

If all LLM advancements stopped today, but compute + energy got to the price where the $30 million zettaflop was possible, I wonder what outcomes would be possible? Would 1000 claudes be able to coordinate in meaningful ways? How much human intervention would be needed?

And also OpenAI’s codex spark?

Headline/article is extremely misleading. They still have subscription plans with included usage, but those usage limits are now based on tokens instead of messages.

https://help.openai.com/en/articles/20001106-codex-rate-card

I like this, and think it's true for how humans learn. What's interesting to me is that it seems LLMs are significantly smarter than they were two years ago, but it doesn't feel like they have better "taste". Their failure modes are still bizarre and inhuman. I wonder what it is about their architecture/training that scales their experience without corresponding improvements in taste.

In theory, RLVR should encourage less error-prone code, similar to a human getting burned by production outages like the article mentioned. Maybe the scale in training just isn't big enough for that to matter? Perhaps we need better benchmarks that capture long-term issues that arise from bad models and unnecessary complexity.

Correct URL: https://www.gingerbill.org/article/2026/02/21/does-syntax-ma...

I’ve tried having one “big” task that I’m focusing on with active back and forth while letting other Claude instances handle easier back-burner type tasks that it can effectively one-shot. But I’ve noticed that often turns into me spending more time/focus than I’d want on tasks that aren’t actually that impactful. I still think I get more done than I would otherwise, but I still haven’t found the best management strategy.

Yeah that confused me, but the compression paper also doesn’t make a ton of sense since I doubt Google would have released it if it was actually such a competitive advantage compared to what other labs are doing. So I wonder what’s actually causing the price decrease.

Any other sources on the OpenAI claim? Regardless, it’ll be nice to have cheaper RAM

Okay this is really fun and mathematically satisfying. Could even be useful for tough bugs that are technically deterministic, but you might not have precise reproduction steps.

Does it support running a test multiple times to get a probability for a single commit instead of just pass/fail? I guess you’d also need to take into account the number of trials to update the Beta properly.