kwindla

We started getting customer pings at 6:15 PT. This is impacting some large ISPs (AT&T) in the US and globally.

This is the topic of almost every conversation I'm having with friends who are programmers right now. The compiler analogy (we basically never read compiler output) is the thing I keep thinking about.

Yes, but also ... the analogy to assembly is pretty good. We're moving pretty quickly towards a world where we will almost never read the code.

You may read all the assembly that your compiler produces. (Which, awesome! Sounds like you have a fun job.) But I don't. I know how to read assembly and occasionally do it. But I do it rarely enough that I have to re-learn a bunch of stuff to solve the hairy bug or learn the interesting system-level thing that I'm trying to track down if I'm reading the output of the compiler. And mostly even when I have a bug down at the level where reading assembly might help, I'm using other tools at one or two removes to understand the code at that level.

I think it's pretty clear that "reading the code" is going to go the way of reading compiler output. And quite quickly. Even for critical production systems. LLMs are getting better at writing code very fast, and there's no obvious reason we'll hit a ceiling on that progress any time soon.

In a world where the LLMs are not just pretty good at writing some kinds of code, but very good at writing almost all kinds of code, it will be the same kind of waste of time to read source code as it is, today, to read assembly code.

Happy to answer questions about this (or work with people on further optimizing the open source inference code here). NVIDIA has more inference tooling coming, but it's also fun to hack on the PyTorch/etc stuff they've released so far.

The Twilio integration made me smile. (For context, the default way to use this is a WebRTC connection from your mobile device to talk to Claude Code, but any network transport supported by Pipecat works.)

I'm trying to come up with a use case where I need to call my Claude on the phone, rather than connect to it in a more modern way.

I honestly can't tell if this is trolling. LEGO bricks are pretty new technology, in the scheme of things. The original LEGO company "binding brick" was created in the late 1940s.

Of course you don't "need" an LLM to have a great toy. You also don't "need" injection-molded plastic. But if you have access to one or both, that can be pretty great!

Source: I wrote the spec for the first version of the LEGO Mindstorms programming language. These days I build a lot of voice+LLM stuff, some of it for big companies, some of it for myself and my kid.

I've done a fair amount of fine-tuning for conversational voice use cases. Smaller models can do a really good job on a few things: routing to bigger models, constrained scenarios (think ordering food items from a specific and known menu), and focused tool use.

But medium-sized and small models never hit that sweet spot between open-ended conversation and reasonably on-the-rails responsiveness to what the user has just said. We don't know yet know how to build models <100B parameters that do that, yet. Seems pretty clear that we'll get there, given the pace of improvement. But we're not there yet.

Now maybe you could argue that a kid is going to be happy with a model that you train to be relatively limited and predictable. And given that kids will talk for hours to a stuffie that doesn't talk back at all, on some level this is a fair point! But you can also argue the other side: kids are the very best open-ended conversationalists in the world. They'll take a conversation anywhere! So giving them an 8B parameter, 4-bit quantized Santa would be a shame.

I 100% agree with Sean that the computer is an exploration machine. There are lots of net positive things for kids (and non-kids) that LLMs make possible. Just like there were lots of net positive things that an Internet connection makes possible.

Of course there are things technologies can do that are bad. For kids. For adults. For societies. But I build this kind of voice+LLM stuff, too, and have a kid, and the exploration, play, and learning opportunities here are really, really amazing.

For example, we are within reach of giving every child in the world a personalized, infinitely patient tutor that can cover any subject at the right level for that child. This doesn't replace classroom teachers. It augments what you can do in school, and what kids will be able to do outside of school hours.