Description of the term: https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fx.com%2Fkarpathy%2Fstatus%2F...
About him: https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fen.wikipedia.org%2Fwiki%2F...
I suggest that people go ahead and learn how to use it or be left behind.
I’ve stopped arguing with people about it (mostly haha) for this reason. They’re either going to have to figure it soon enough without our help, or as you say be left behind.
4. Writing the first core version of a service or UI. I’ll typically use close to 100% of those generated lines, and then continue building with LLM assistance where it makes sense. It makes a big difference to development velocity.
5. Finding bugs. If some bug isn’t obvious to me, provide the code to an LLM and describe the problem. Its success rate is high.
6. Working with tech I’m not particularly familiar with (an extension of your #3, i.e. learning)
7. Writing documentation.
8. Reverse engineering existing code, i.e. describe some code to me so I don’t have to dig through it in detail.
9. Writing unit tests.
Her attitude, and loud mouth - not so much.
What do you object to, her support for equality or her opposition to genocide? Or is it that a woman stated an opinion?
LLMs can perform tasks that look like reasoning
So, the functional equivalent of reasoning?
This is why code generating LLMs need to make heavy use of external tools.
Are you saying that ChatGPT, Claude, Deepseek etc. “make heavy use of external tools” to write code? Because they all write pretty good code, up to a certain size of program. Certainly far better than the average human, who can’t code at all; or the average software developer, who isn’t really very good.
In 2011 Microsoft piad Nortel $7.5m for IPv4 address space ($11.25 per address).
MS paid the shell company handling Nortel's bankruptcy that money. Nortel as an actual company was gone by then.
What this country needs is a good five cent microcomputer.
