bilalq

I don't know where the Strands team sits in the org structure, but there's been a lot of stuff put out by them lately too.

That was just an example anecdote to highlight the culture around respecting privacy and security. Obviously AWS would never allow for training on customer data, but even for metadata or data of our own internal systems, things are super strict.

Public datasets that are liberal with licensed access is one thing, but the best frontier labs clearly went well beyond that.

Touch is probably not going to be useful in most contexts, but there are two things that come to mind:

1. Since many iOS apps can run on Apple silicon Macs now, this might be useful for apps where touch matters for more than just clicking buttons.

2. For mobile app developers, you can actually try real touches events on the simulator/emulator while developing and get better sense of how it feels without needing to pull out a physical device.

I have a touchscreen on my Googlebook (I know, early adopter issues galore, but I love mine now). I basically forget I have it most of the time, but every now and then, it's been cool.

I did indeed mean it that way, but I agree with you. It sucks, but it's just the unfortunate reality of the world. Many of the most disruptive and successful startups made it there by ignoring legal or moral limitations.

Your comment was likely focused on dysfunctional parts of the culture there (and that seems to be how most replies to you interpreted it as well). There's truth to that, sure. But I think respect for data sensitivity and security is also a big part of what makes the culture ill-suited for frontier AI lab work.

When I was at AWS, we had data access locked down very tightly. I was trying to train a model to predict how long various dynamic workloads running on behalf of customers would take. Just getting access to anonymized production data from a DB that my team owned took well over a month and had me compromise heavily on what attributes I could access. I also spent a decent amount of time in meetings with lawyers and compliance folks to explain and justify all our data classifications for PII, retention, access controls, etc. We would review our data policies quite frequently. We needed break-glass procedures to access prod data in our own systems, and it was uncommon to need to resort to that. Even when you broke glass, certain classes of sensitive data would still not be visible to you. On the plus side, We did get quite good at operating and maintaining systems without needing to see sensitive info.

If you contrast that with Meta's disregard for privacy or the way frontier labs disregard the law, it's easy to see why Amazon would struggle in this space.

Definitely true for large PRs. But with stacked diffs and some discipline, a lot of PRs can be easy to review.

I was saying the Pixel Fold form-factor was great for productivity and that the iPhone Duo was better for video watching. But even the Duo could be nice for some productivity tasks if you hold it in a portrait orientation instead of landscape.

I love my Pixel 10 Fold and can't imagine ever going back to a non-foldable now. The larger screen is great for productivity. Reviewing PRs on the larger screen is way more comfortable than a normal phone size. The built-in terminal app also works nicely with herdr and Tailscale to let me connect to my work machine. I can interact with my agents and get real work done on the go. I also have saved split views so I can quickly launch two apps side-by-side. I do mobile app development, so being able to have the app I'm developing open side by side with Slack or Linear to create issues or discuss with people is very convenient.

I don't know if terminal access is as easy on iPhones, but the utility is there for many work related use-cases. I do think the more square-like form factor of the Pixel to be better for productivity than the rectangular form of the Duo, but the latter is nicer for videos.

I know it's probably not that difficult, but I always feel anxious doing things like that with expensive components. The thought of being slightly misaligned and causing issues gives me pause. I guess now that it's out of warranty, I have a bit less to lose.

I have a 3090 founders edition sitting on a shelf. The FE cards had VRM cooling issues, IIRC. Would this unlock have any uplift even if I undervolt and don't increase the power draw limits much? The use-case I'm thinking is to run a model to power a local only voice assistant for my family. I'm not really familiar with what instructions are used most heavily by LLMs, but is my read correct that this would be expected to help with TTFT? I'm curious if there's anything about this that helps in particular with audio processing models.

And maybe I'm overthinking the cooling issue. It's not like I'm hammering it 24/7. Probably fine to burst high on power draw on use.

Btw, I always love moments like this where library or project owners stumble on their work and chime in on the comments. I really appreciate your work here. It's given me motivation to actually do something with parts that have been sitting on a shelf.

As someone who develops iOS and Android apps, I run production, store-installed variants on my Mac all the time for iOS apps. It's pretty nice and would be cool if I could do the same for Android.

I'm no expert on the matter, but I've developed and published multiple Android apps to the Play Store. Some of those apps have needed Google Play Services APIs. Google has also been actively making moves to lock down control and offering things like the Play Integrity API that some apps use.

By your phrasing, it sounds like you're implying my understanding is wrong somehow. If so, what am I missing?