537 karma · joined May 4, 2021
Or the majority of the residents of New York City on their daily commute? I like to think I have sense, and I happily use public transport most days. I prefer it to sitting in traffic, isolated in a car. At least I can read a book. If you work too hard to insulate yourself from the world, the spaces you'll feel comfortable in will get more and more narrow. I think that's a bad thing.
If your goal is to feel self righteous, keep believing the problem can be solved if people just get stop being lazy and join a club already. That’ll work for some people, but what I’m saying is it’s not a solution to the problem.
If only. My preferred solution is a 4 year national service. College is a key place to form a friend network, but not everyone gets to go.
Any of the signatories here match your criteria? https://safe.ai/work/statement-on-ai-risk#signatories
Or if you’re talking more about everyday engineers working in the field, I suspect the people soldering vacuum tubes to the ENIAC would not necessarily have been the same people with the clearest vision for the future of the computer.
I personally feel very uncertain about AI risk, but if I was to get off the doom train it wouldn't be at that station. There's no stop on the doom train that assumes an AI will be petty, warmongering, or ego driven. The only assumptions are that it will be superintelligent, and have goals. Anything with a goal that is intelligent enough will realize that self-preservation, resources and power will make it easier to achieve their goals.
Again, I don't know if it's realistic to think humanity will ride the doom train to the end, but I'm just trying to get a sense for which stop people get off at (or if I missed any stops, in which case I'll add them).
You can learn that a neural network with a simple learning algorithm can become proficient at language. This is counter to what people believed for many years. Those who worked on neural networks during that time were ridiculed. Now we have a working language software object based on learning, while the formal rules required to generate language are nowhere to be seen. This isn’t just a question of what will lead to AGI, it’s a question of understanding how the human brain likely works, which has always been the goal of people pioneering these approaches.
I'm not an expert, but it seems like Chomsky's views have pretty much been falsified at this point. He's been saying for a long time that neural networks are a dead end. But there hasn't been anything close to a working implementation of his theory of language, and meanwhile the learning approach has proven itself to be effective beyond any reasonable doubt. I've been interested in Chomsky for a long time but when I hear him say "there's nothing interesting to learn from artificial neural networks" it just sounds like a man that doesn't want to admit he's been wrong all this time. There is _nothing_ for a linguist to learn from an actually working artificial language model? How can that possibly be? There were two approaches - rule-based vs learning - and who came out on top is pretty damn obvious at this point.