I still get made-up Python types all the time with Gemini. Really quite distracting when your codebase is massive and triggers a type error, and Gemini says
"To solve it you just need to use WrongType[ThisCannotBeUsedHere[Object]]"
and then I spend 15 minutes running in circles, because everything from there on is just a downward spiral, until I shut off the AI noise and just read the docs.
Gemini unfortunately sucks at calling tools, including ‘read the docs’ tool… it’s a great model otherwise. I’m sure Hassabis’ team is on it since it’s how the model can ground itself in non-coding contexts, too.
I think this is a classic old-vs-new tale. I started my PhD in biochemical research where analyzing data by hand was definitely a "craft" in some aspects. Later I forewent going to the lab entirely and instead spent all my time on developing machine learning for automated data analysis. But just like field work, you still need people in labs who can continue the craft.
The article should perhaps introspect a bit more instead of setting up a false dichotomy between "rainforest field work or computers".
But that’s more of a theoretical truth than a practical one, isn’t it? High quality novels are easily found. TikTok videos of equally high quality and depth? Perhaps not so, or exceedingly rarely.
Infinite monkeys with infinite time could surely also produce something spectacular and eye-opening, statistically speaking. But umm, you’d have to wait infinite time for it to be done, so it’s not really efficient when time is a finite resource.
"On X, anyone can pay to obtain the ‘verified' status without the company meaningfully verifying who is behind the account, making it difficult for users to judge the authenticity of accounts and content they engage with."
As stated in you source the EU is (among other things) not happy about Twitter calling users 'verified' while the meaning of 'verified' switched from "we did sth. to make sure the account owner is indeed the thing/person they say they are" to "the account owner is paying a monthly fee".
I’m interested in earnings correlating with feature releases. Maybe you’re pushing 100% more bugs, but if you can sell twice as many buggy features as your neighbor at the same time, it could be that you could land more contracts.
It’s definitely a raise to the bottom scenario, but that was already the scenario we lived in before LLMs.
I second the persistence. Some of the most persistent code we own is because it’s untested and poorly written, but managed to become critical infrastructure early on. Most new tests are best-effort black box tests and guesswork, since the creators have left a long time ago.
Of course, feeding the code to an LLM makes it really go to town. And break every test in the process. Then you start babying it to do smaller and smaller changes, but at that point it’s faster to just do it manually.
The crusade against gluten probably did it. Tofu lives as un-refrigerated grey blobs and tempeh never even made it to the shelf, probably because of hormone-disrupting soybeans. But hyper-engineered single cell meat? Now that’ll sell.
I think group 3 is a bit of a reach. Most people just treat it as a commodity. You need a break after shopping? Coffee. Meeting someone to talk over something for 30 minutes? Coffee. Need a cozy place to sit and get some work done? Coffee. For none of these do people have to engage with the community or be caffeine addicts.
> We shall be able to rid ourselves of many of the pseudo-moral principles which have hag-ridden us for two hundred years
Still haven’t gotten rid of work for work’s sake being a virtue, which explains everything else. Welfare? You don’t “deserve” it. Until we solve this problem, we’re not or less heading straight for feudalism.
"To solve it you just need to use WrongType[ThisCannotBeUsedHere[Object]]"
and then I spend 15 minutes running in circles, because everything from there on is just a downward spiral, until I shut off the AI noise and just read the docs.
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