I only spent 10 minutes with Handy, and a similar amount of time with SuperWhisper, so pretty ignorant. I tried it both with composing this comment, and in a programming session with Codex. I was slightly frustrated to not be hands free, instead of typing, my hands were having to press and release a talk button (option-space in handy, right-command in superwhisper), but then I couldn't submit, so I still had to click enter with Codex.

Additionally, for composing this message, I'm using the keyboard a ton because there's no way I can find to correct text I've typed. Do other people get really reliable and don't need backspace anymore? Or.... what text do you not care enough to edit? Notes maybe?

My point of comparison is using Dragon like 15 years ago. TBH, while the recognition is better (much better) on handy/superwhisper, everything else felt MUCH worse. With dragon, you are (were?) totally hands free, you see text as you say it, and you could edit text really easily vocally when it made a mistake (which it did a fair bit, admittedly). And you could press enter and pretty functionally navigate w/o a keyboard too.

Its weird to see all these apps, and they all have the same limitations?

Personally, I'd really like god to have a nice childhood. I kind of don't trust any of the companies to raise a human baby. But, if I had to pick, I'd trust Anthropic a lot more than Google right now. KPIs are a bad way to parent.

If you want to raise the money to buy land and build a private highway, price segment away. If you want to price segment a publicly owned and operate commons, it needs to be in the public interest.

The money raised by auctioning access is of some public benefit, but is it enough to offset the deep unfairness of the public granting, for example, software engineers a shorter commute on average than teachers?

The physical aspect I can’t give up is I can hold the phone with my thumb on the bottom and my middle finger on the top and scroll with my index finger to read. Wish I could buy that capability on a new iPhone, maybe one even slightly smaller.

Time to go find out if there’s even a way to downgrade, oof this is slow.

1) a bunch of people who contributed one or two PRs, but it took the maintainers more time to review/merge the PR than the dev time contributed

2) a much smaller set of people who come back and do more and more PRs, eventually contributing more time than it takes to review their work

A major existing reason to review PRs from class 1 "once or twice" contributors (perhaps the main reason?) is that all class 2 "maintainer-level" contributors start as class 1.

I agree there's an awkward middle ground here, now you have to define where the boundary is between class 1 and class 2, but I think if you were able to graph contribution level you'd find there's already something of a bimodal distribution naturally in many projects anyway.

This is based on a loop where user commands, or mouse clicks, are fed to the LLM, and the LLM is instructed to simply render the next frame, as if it was rendering the frame of a video. In this particular case, we actually render static HTML+CSS as the "image" because image output from existing LLMs doesn't have high enough text fidelity.

Computation is done by the LLM itself, the LLM does not "write code" it IS the code.

Comments URL: https://news.ycombinator.com/item?id=44313452

Points: 2

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It takes mouse clicks, sends them to the LLM, and asks it to render static HTML+CSS of the output frame. HTML+CSS is basically a JPEG here, the original implementation WAS JPEG but diffusion models can't do accurate enough text yet.

My conclusions from doing this project and interacting with the result were: if LLMs keep scaling in performance and cost, programming languages are going to fade away. The long-term future won't be LLMs writing code, it'll be LLMs doing direct computation.

How much would AirBnB pay for the intelligence everyone gets all their info from having a subtle bias like this? Sliiightly more likely to assume folks will stay in airbnbs vs a hotel when they travel, sliiightly more likely to describe the world in these terms.

How much would companies pay to directly, methodically and indetectably bias “everyone’s most frequent conversant” toward them?

It's easy to focus on libgraft's SQLite integration (comparing to turso, etc), but I appreciate that the author approached this as a more general and lower-level distributed storage problem. If it proves robust in practice, I could see this being used for a lot more than just sqlite.

At the same time, I think "low level general solutions" are often unhinged when they're not guided by concrete experience. The author's experience with sqlsync, and applying graft to sqlite on day one, feels like it gives them standing to take a stab at a general solution. I like the approach they came up with, particularly shifting responsibility for reconciliation to the application/client layer. Because reconciliation lives heavily in tradeoff space, it feels right to require the application to think closely about how they want to do it.

A lot of the questions here are requesting comparison's to existing SQLite replication systems, the article actually has a great section on this topic at the bottom: https://sqlsync.dev/posts/stop-syncing-everything/#compariso...