rryan
rryan on Hacker News
HN is not your therapist, but possibly your decision making is driven by branding instead of judging technology on its merits? Easy mistake to make ;)
CircleMUD was my first intro to C and network programming. I was at a computer camp for 8-10 year olds that taught BASIC. One of the counsellors was doing their undergrad at caltech and pulled the students who were bored by BASIC into a separate group to learn C by editing CircleMUD.
Hacking up a pre-existing MUD was the perfect mix of immediacy / interactivity and fun to hook me. So thankful to that guy, wherever he is. He probably changed the course of my life.
Disagree. The abstractions they are talking about aren't like, the y-combinator. They're talking about boring software engineering abstractions.
I know nothing about the PhD candidate and professor who co-authored this, but I don't think this statement makes sense in general.
Typically CS labs at universities contain people who have not spent a significant amount of time exposed to large industry codebases and the corresponding complexity. I think the post would have more credibility coming from e.g. the platforms team at a tech company with a monorepo.
agents are unlike humans in many ways but they have their own limitations. it's magical thinking to believe that they are able to cope with zero software abstractions, especially as a codebase increases in size and complexity
and today's agents increase codebase size and complexity much faster than humans do via traditional software engineering methods, so this is likely to hit a wall faster than if human software teams were to do this experiment.
As a human emdash enjoyer, I'm pretty damn grumpy that everyone assumes I'm a chatbot now. :P
I think the super long timelines in automotive make it really hard to succeed. Really impressed with what ClearMotion accomplished given that
Posted by
rryan on Tuesday April 07, 2026 @11:07AM
from the blog.zacka.io dept.
Don't make me tap the sign: There is no such thing as "bytes". There are only encodings. UTF-8 is the encoding most people are using when they talk about modeling "raw bytes" of text. UTF-8 is just a shitty (biased) human-designed tokenizer of the unicode codepoints.
RMSNorm is pretty insigificant in terms of the overall compute in a transformer though -- usually the reduction work can be fused with earlier or later operations.
ML 101: Do not evaluate on the training data.
Yes of course it can, because they fit in the context window. But this is an awful test of the model's capabilities because it was certainly trained on these books and websites talking about the books and the HP universe.
Thanks for everything, Rich. You inspired me repeatedly.
Yea uh, don't know what was going on there but there are roles with direct reports that aren't in mountain view (unless you mean, like in 2004). NYC has 1000s of googlers.
This is ... not what I expected. It's basically wiring up pre-trained models to ChatGPT via a router and "modality transformations" (a.k.a speech-to-text and text-to-speech).
I expected it to be a GPT-style model that processes audio directly to perform a ton of speech and maybe speech-text tasks in a zero-shot manner.
Except when your doctor won't prescribe it you offlabel because you don't have a condition they were taught about in med school
In the past few months I've been getting much more fake order / payment spam.
I agree that a Transformer is an example of a "reflexive" behavior because it learns to react in a context (via gradient descent rather than evolution as the learning algorithm). It's a conditional categorical distribution on steroids.
I also agree it's not much different than what's going on in this petri dish with pong.
But I don't think that's a profound statement.
What I'm saying is that calling what a Transformer does "language development" isn't accurate. A Transformer can't "develop" language in that sense, it can only learn "reflexive" behavior from the data distribution it's trained on (it could never have produced that data distribution itself without the data existing in the first place).
There's a huge difference between fitting a probabilistic model to a data distribution then sampling from it (what GPT-3 is) and agents that invent language and use it to communicate.
You're using a pointwise loss, which means you are treating each timepoint as conditionally independent. That's a deeply flawed assumption, probabilistically.
Try an autoregressive model of the joint probability distribution of the sine wave timepoints -- like WaveNet [1]. It will nail your sine wave -- just as it nails mixtures of sine waves (speech and music). :)
[1] https://arxiv.org/abs/1609.03499
"I could go pro, but nah" -- I read this and closed the tab. What a whingefest from a free tier user.
The Reddit crawling problem is because Reddit rate limits their crawling so they have to prioritize the most popular feeds. What's the problem with linking your account, or making a dedicated feedly throwaway for crawling?
Been a pro user since the beginning because I want the service to stick around. It works just as well as it always has and I don't mind that they're adding new features even if they aren't for me.
Sheesh.
That makes no sense. Why is "YouTube Premium" capitalized?
> The main source of income for youtube isn't ads. YouTube revolves around the merchandise and YouTube Premium subscriptions.
> If you are talking about creators who are not earning money for using vanced, you should know they won't make millions out of those ads.
... right. Feel free to keep telling yourselves that.
* YouTube Kids with allowlist.
* App Timer of zero minutes on YouTube app.
Straw man argument. OP was suggesting you pay for YT premium, which does away with the ads completely. Removing your web adblocker is a non sequitur, and exposes your computer to malware / spyware in addition to ads.
Parents are treated equally. If you give birth you get an additional 6 weeks of
medical recovery leave. If two parents (any gender) adopt a child then both receive an equal length
baby bonding leave.
I've taken parental leave twice at Google and used the full amount. No ill effects, as far as I can tell. Everyone I work with and my management chain was fully supportive.