8,294 karma · joined August 5, 2012
Working on Fully Homomorphic Encryption at Google (see https://heir.dev)
Come say hi at j2kun@mathstodon.xyz
Perhaps we should be more ambitious in the types of problems we try to solve, and the types of value we try to provide with the software we build.
Nobody cares if hobbyists make a "Star Wars but make it Monet" art piece with AI and put it on their wall. It's the part where bosses fire John Smith and then ask the LLM, "please write 100 articles in the style of John Smith." It's the part where an actor is hired once, their face scanned, and then their likeness is used (unpaid) in a hundred films.
Out of curiosity, which companies embraced quality journalism and failed because of it?
I think this is key. If AI wasn't force-fed into every industry in a rapacious grasp for more profits, our society might have been able to grow into a healthier equilibrium where AI is a useful tool for creative professionals.
Even the insiders I talk to at big AI labs express the opinion, "nobody likes where we're going, but the pressures are too strong."
A very small fraction of people who get math degrees actually continue to do math in their careers. They usually have to get other jobs in order to survive (actuary, teacher, finance, etc.). Academic math funding was already drying up for last few years, and now AI will probably cause more cuts. Not to mention that academic math positions have never paid particularly well.
I feel bad for anyone who can't find a job, but the software industry as a whole has been the cushiest industry for decades, and the current turbulence seems more temporary (and driven by corporate greed) than a systematic destruction of the trade.
The implication here is that you wasted your time learning that math, and the fact you learned that will not actually help you contribute to anything.
Now maybe you are closer to understanding the feelings expressed in the article?
It's not like the options are write software or starve. Billions of people find jobs and can feed their families without writing software.
I also don't often meet junior software engineers who actually have families to feed. Most juniors work in the industry for a few years before deciding to get married and have kids.
Perhaps it's more that "consumer startups that want to become a unicorn" are hard.
That said, I would probably follow this same approach if I were to do this, but with extensive randomized testing as well.
(For example, your approach would not necessarily catch all the same overflow behaviors; the OP expressly claimed that "replicating all bugs" was also important, and many bugs are caused by certain overflow behaviors)
I don't see how it's related to quality at that point. Call your technique "the banana method" and wait to see OpenAI invent "the banana method"