singingfish

I'm only concerned with the input efficiency, but the output energy efficiency is quite bad too. I can not see a pathway to generating economies of scale for this stuff.

Maybe I shouldn't have been pissed of by your commient. In which case - the excess costs of the training, output, feedback, and training cycle of artificial neural networks seem to prohibit the nightly training consolidation cycle (i.e. sleep) that is an important part of natural neural networks.

I can't make sense of your comment. Firstly because of the obvious massive over-build of GPU infrastructure the AI companies are engaging in. Secondly because the instance of the LLM in the data centre that users interact with is only a small part of the story. The training phase is clearly prohibitively expensive, thus the fact that these things have no way to learn from experience except by smoke and mirrors.

Also your comment feels like the classic climate denial discourse - say something a bit complicated and a bit difficult to follow that looks at a very small out of context part of the story to cast doubt.

I can't see a pathway for these things to be able to learn from experience in any meaningful way - the energy budget seems to prohibit it. Artificial neural networks are already many orders of magnitude more energy intensive than natural neural networks. Despite this, large nervous systems are very energy intensive as well. For example in humans 20% of the energy budget goes to the brain which is 5% of the body weight.

So I refrer to LLMs as language extrusion confabulation machines. Language extrusion was a term I heard the linguist Emily Bender use. Confabulation because my observation is that talking to an LLM is very much similar to my experience of interacting with Korsakov syndrome patients some years ago.

I look forward to the hype settling down to see what we end up with.

Meta's bots are spectatularly awful, and if your organisation needs to use facebook advertising, they're also unblockable. There are ways around it that doesn't exactly block them but does clearly communicate they should GTFO, but it just shows you what an awful company Meta is.

It was brought to my attention that the phrase "terminal, degenerative, sexually transmitted condition" returned no results from my search engine. So I tried to fix it.

as a rule the interviewee should be assessing for goodness of fit, as well as the interviewer. If my simplified nuanced answer to why I limit my usage of LLMs was poorly received, I wouldn't want to take a job somewhere likely to make me miserable.

aka LLMs can not learn from experience - this is a fundamental limitation. c.f - individuals with Korsakov's syndrome - who also confabulate in a similar manner.

Both Yamaha and Roland keep a long back catalogue of reasonably priced parts for at least their mid-range pianos and up as well. I should check Korg too I guess.

I've had some impressive customer service from Yamaha concerning decades old saxophones that they have zero prospect of generating revenue from in the future, for an unrelated (musical) data point.

Of course they do - it's the same as bookmakers or other gambling syndicates, it only makes sense to operate at a certain scale otherwise the rounding errors and stochasticity will kill you.

If you want to just stop yourself from shooting yourself in the foot in your current checkout and maintain privacy around your own stupidity, you can add patterns to `.git/info/exclude`

and long may he idle