`harness` is a term invented/borrowed to describe a vague vision of applying llm in a more controlled manner, suitable for semi organized, complex work. the sad part is then people shift the attention from the real problem but seeking inspiration from the terminology.
the real problem: is there a general framework to allow llm with limited context size to approach problems, just like a capable newbie integrated into a chaotic code base? how does it work?
I think it's an epistemic problem, and my fork of pi: pie (github.com/wangii/pie)
good observation! however, I'd argue it's the distribution channel and installation friction did the job in the cases you mentioned.
given how easy it's to replace LLM API in claude code, and how easy it is to write a claude code clone with itself (Fable is pretty good!), the collapse is coming.
Ted Chiang is a great Sci-Fi author, but his remark `GPT-3 and similar models as a "blurry JPEG of the Web"` was misleading at the best.
I share the view with others the term `consciousness` is not well-define yet, therefore his assessment is pointless. Maybe the real question to ask, if consciousness is merely an illusion at the macro level, when the observers not looking at the tech/implementation level deep enough, just like the term "intelligence" itself, might be more precisely captured by drifting amongst high dimensional manifold pitches.
Ted Chiang is a great SF author, but it's bizarre how much foggier and more obfuscated his thoughts about thinking machines got, once those machines became real. Same with several other SF authors.
The idea of software developers' job is to translate specification into codes is dying. Now what I'm experimenting is to make my developers into competing project manager and developers are replaced by AI. I think the key advantages of developers, junior or senior, are the process + data oriented style of thinking, therefore way ahead of people from many other domain.
I told my developers: the day of making good money by sitting in front of computer and typing is long gone. Go to the clients' scenes and build the whole thing from scratch, with some assistant from sales and domain experts. Now you are the PM.
I tried to play with GPUI for making a scratchpad like app with zed and It was one of the most rough experiences out there. They mention it in the readme though that it has rough edges but I hope that they make in the future more easier to tinker around.
It's all about the right mind set at the very top level. At the beginning of the PC era, nobody would bet IBM to lose. Same in the dawn of internet, all money was on MS. so it happened to Nokia and Ericsson.
Google is a giant without a direction. The ads money is so good that it just doesn't have the gut to leave it on the table.
she's done pretty important work but since then obsessed with the vague term `spatial intelligence`. what does it mean? there isn't a clear definition in the piece. it seems very intuitive & fundamental but tbh not *rigorous*, nor insightful.
It's rare for one person to achieve many things. Her ImageNet was certainly HUGE. But she is a researcher. I think the true power of researchers is to persist. I also often think that researchers are too much absorbed into their topics. But that is just their purpose.
It could be a dead end for sure. I just hope that someone figures out the `spatial` part for AIs and brings us closer to better ones.
I have only one problem w/ the S1: the creators just not have the guts to kill Mother or Father. Don't get me wrong, I like them but it could make the whole series more distant and cold.
the real problem: is there a general framework to allow llm with limited context size to approach problems, just like a capable newbie integrated into a chaotic code base? how does it work?
I think it's an epistemic problem, and my fork of pi: pie (github.com/wangii/pie)