WhitneyLand

Sure that’s true. But if something makes sense for a technical benchmark that’s not a guarantee it’s the best way to introduce a concept. I just think other approaches could have been more clear for this case.

I don’t think they are confused either just don’t think it’s a good way to introduce the point.

When good expositors choose motivating questions, say like 3 blue 1 brown, they don’t usually make apples to oranges comparisons. The best examples motivate while making sense before and after you learn.

"The H.264 video, 300 frames long is 175KB. A single frame of that video in PNG is 1015KB. It looks like we're storing 300 times the amount of data in the video. But the file size is a fifth. So H.264 would seem to be 1500x as efficient as PNG. How is this even possible? All right, what's the trick?"

Mostly the trick is they're comparing lossy to lossless compression which doesn't even make any sense.

It didn't really do any better, the difference is well within the error bars for their benchmark.

Thinking someone has made the wrong editor choice is a great example of feeling strongly about something that’s meaningless and likely uninformed.

Find it useful to conjure up cognitive dissonance and practice letting it go.

Yes, most likely. The problem is even if it’s better it has to be super fast/real time to be convincing. That’s the part I think could take a few more hardware generations.

Well, research with users establishes chat as way more convincing than voice systems, no reason to assume one of the groups is much smarter/skilled.

Passing a Turing test over a 5 minute conversation:

- Text interface: Done

- Voice interface: 5-10 years I’ll predict

The demo is nice, but enough obstacles remain that very few people would mistake it for a human over even a 5 min conversation. Chat systems configured to intentionally impersonate can already get people to mistake them for humans most of the time.

There’s been great progress in this area, direct response modeling, parallel reasoning, but last challenges are huge.

The reality is LLMs still seem dumb much more often without significant reasoning time (test time inference). On that point alone they are still an order of magnitude too slow for convincing interactive latency.

Of course they don’t need to meet this bar to be useful, systems are good enough today for lots of applications. It will just be interesting to see what the final delta ends up being.

Yes, see the car design analogy above. Because of the context it's appropriate to mention Mononoke and Sapling.

They didn’t mention Mononoke.

If I credit my newly introduced car as inspired by Corvette, then sure, it might be ok not to mention the engine (Mononoke is the server part of Sapling)

However if my new car's engine is a near copy of the one in the Corvette, and my announcement gushes about the engine using the same terms the Corvette design team invented...

Then can you see how a mention might be nice?

It’s not a stinker.

It’s not meant to be an engineering improvement, it’s an important theoretical result because it casts doubt on things that were previously thought to be impossible.

Even if you’re whitelisted you get only 6 accesses a day on a standard account, have to pay for a dev account to get 200/day which still isn’t great.

For my Figma needs, having Codex do computer use seems just as good as their mcp. I can tell it, “go download the assets for what I need and take a few screenshots for reference”.

Yes, to be more specific, every tool like this has benefits offered and then taxes to be considered. For example, what's the tax for:

- Maintaining a significant new moving part in the dev process. KMP updates, management, integration, futures awareness, this all takes non-zero time.

- If an iOS dev wants to work on a KMP project what's the ramp up time? How much less efficiently can they contribute compared to a pure native app?

- How much time is spent on problems, bugs, issues, related to KMP. This is guaranteed non-zero for any tool.

- Is there less benefit to KMP with coding agents? Previously with two native apps, a bug fix had to be done twice. Currently, say a fix in done on Android, it's quite easy to say "propose an equivalent fix for the iOS repo". I do not claim this removes all benefits of a single code base, just that some things are not as bad now.