Nice! Although if you have new young team - things look different. Also, to be fair, agentic dev is something that might be just the right answer for the future.
Actually not worried about unemployment. This is an awesome development thing - called technological progress.
PS: Compare Assembly with Python - for sure the ration is more then 10x. Still we need much more devs compared to early days. For me the question is what the future software dev looks like (if the job still exists).
Agree, especially a review is always an knowledge update/exchange and for juniors a learning experience. If it is AI generated, its just not worth the time.
Not sure tbh. The labs which are creating the AI - definitely know what they are doing, and its incredible. Would just argue that the AI will become only better in the future
There seems to be two likely outcomes. First the value of education drops, since studying becomes much easier. Second, we will have few young genius level people, who were able to learn very quickly with help of AI.
How about elliptic curve cryptography then? I just think coming with a formula is not really understanding. Actually most often the “real” formula is the end step of understanding through derivation. ML does it up side down in this regard
Sure agree, for bi directional websocket communication it is the way to go.
It's just that you have to really think it thorough when using it. Like using asyncio.sleep instead of sleep for example and there are more little things that could easily hurt the performance and advantages of it.
You can’t just plug and play it. As soon as you introduce async you need to have the runtime loop and so on. Basically the whole architecture needs to be redesigned
Counterargument. So far bigger have proven to be better in each domain of AI. Also (although hard to compare) the human brain seems at least an order of magnitude larger in the number of synapses.
This looks like a nice application to get inductive bias into the model. But I think right now there is no solution to get fine grained motor skills besides tele operating and doing behavior cloning. And even then it is far from perfect..
The claim about sample efficiency sounds a bit strange, since they did not include the state of the art sample efficient algorithms. Like dreamer or tdmpc. Also PPO is known to be not efficient, just compute efficient.
Isn't most the time consumption in the airport anyway? Like people supposed to be ther 2-3 hours ahead. If you could get 10m before the flight to the airport that would save so much more time.