izzygonzalez

ur welcome

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https://twitter.com/ShopifySupport/status/172416611008424349...

This is absurd.

In the spirit of CCRU, me and a few dozen other people have been having ongoing discussions on related topics under the banner of effective extropianism. I think it’s important to figure out how the landscape of rapidly evolving tech fits into our lives and vice versa. We’re working on a repository of adjacent texts.

If you’re interested, my Twitter handle is in my hn bio.

“This comparison was done by running multiple hypothesis tests, such as the Kolmogorov-Smirnov test. These tests, combined with our visual analysis of the data yielded the result that repositories containing swearwords exhibit a statistically significant higher average code-quality (5.87) compared to our general population (5.41).”

Abstract:

Theory of mind (ToM), or the ability to impute unobservable mental states to others, is central to human social interactions, communication, empathy, self-consciousness, and morality. We administer classic false-belief tasks, widely used to test ToM in humans, to several language models, without any examples or pre-training.

Our results show that models published before 2022 show virtually no ability to solve ToM tasks. Yet, the January 2022 version of GPT-3 (davinci-002) solved 70% of ToM tasks, a performance comparable with that of seven-year-old children. Moreover, its November 2022 version (davinci-003), solved 93% of ToM tasks, a performance comparable with that of nine-year-old children.

These findings suggest that ToM-like ability (thus far considered to be uniquely human) may have spontaneously emerged as a byproduct of language models' improving language skills.

It’s an error. You can get around the limit by scheduling a tweet a minute into the future or using the API to tweet/reply.

This may be true today, but the rate of progress on these tools is hitting a curve. Text and image generation are already basically indiscernible from human creations, and the entire space is now turning its attention to audio in tandem.

I think you’re right that code models are a vital research path toward AGI.

The steps you elucidated are all expressible in natural language, and we see models like Codex Edit making headway there. One of the most fascinating parts of this is that once access to the known baselines are provided to high-level engineers, they then go on to do much more than what the models alone can do.

The main hinderance to enterprise was compliance but the move toward Azure, etc, will dissolve those barriers this year.

I don’t know what your argument is exactly, but it seems to be something like, “Software engineering is really hard so computers can’t do it.”

A variation of that argument props up most common AI skepticism. I don’t think there’s anything out right now that would convince you, but from what I know, everything you pointed out will be solved within the next few years.

That’s objectively wrong.

Codex, AlphaCode, both surpassed by CodeRL on the challenging APPS benchmark last year. Meta working on InCoder. Microsoft working on UniXCoder…

Future research directions are pretty clear from where we stand. That includes iterative methods, reinforcement learning, text diffusion, etc. No one is stuck.

I’m not sure if the rest of the responses here are reflexive self-soothing, or just caught on the “ChatGPT” product itself, but unequivocally, your anxiety is warranted.

Code generation is moving extremely fast. This tech didn’t freeze in time at Codex or Copilot or ChatGPT. It’s one of the most exciting and difficult domains in AI and the smartest people are all set on solving it.

I’m sorry you’re feeling distress. You’re in good company. A lot of the world is going to have to deal with these problems very soon.

Can you elaborate on what sort of damage you’re imagining, or give an example?

This aspect of loss of ego, extinction before subsumption of the remaining space by the superego, is precisely what has made certain types of Buddhism palatable to Western capitalism. It is not inimical to the Protestant work ethic, it is not inimical to the transient demands of leaders, it is not broken by the suffering of every day life.

The perfect soldier, citizen, human, is a faceless, egoless pupil.

This is what I aim for when writing documentation. It’s more fun to make and people are more likely to read it!

Winding down now, hope it was fun! Will post on Twitter again in a day or so with next iteration. Will try to maintain an endpoint for interested researchers

Early demo working out server and model kinks. Refresh to get new generations, change the username to try to get generations for other public Twitter accounts

At certain scales that’s true but there’s plenty you can experiment with with just Colaboratory or Kaggle… at least to get some intuition before jumping to spending money.

arXiv https://arxiv.org/abs/2211.02515

Discussion https://old.reddit.com/r/math/comments/y93a86/eliundergradua...

https://mathoverflow.net/questions/433949/consequences-resul...

New Yorker article https://www.newyorker.com/magazine/2015/02/02/pursuit-beauty

No, apparently we don't. There's no reason to spread FUD about tools that increase productivity. There are still a lot of people in the world who don't have enough to eat.

Long stretches of automaticity definitely give my brain a chance to simmer whatever ingredients are in it at the moment. One of the luckiest times in my first few years of work was being able to listen to audiobooks and podcasts for almost 40 hours a week, for several years. I think that gave me a little bit of a wide range of the world to begin building a complex systems model of it in my mind.

Because it hasn't happened

What big companies are you referring to? Protecting data takes effort, so by virtue of that, intent is a necessary precondition.

Most companies probably don't take care of these things at the rate or level you seem to be assuming that they do.