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Comment Re: So we all know the guy is selling snake oil (Score 1) 31

I'm all in favor of space travel, but that's not going to solve the social problems on earth, and we don't yet have the ability to run a small self-sufficient stable society in an off-earth environment.

I do support space habitats, but I tend to think of that as a "next century" (or after the singularity) kind of thing.

What a large war does is kill of a large proportion of the most aggressive young males. It's one of the traditional ways the current crop of alpha-male primates keep control.

Comment Re:This is how it should be (Score 1) 3

Google announced roughly the same thing, on device models for phones a couple weeks ago at their developer conference. The 1b model is fine for basic tasks like turning on lights, checking email, social media notifications etc and runs ok on midrange phone hardware. The 4b model technically runs but it's borderline unusable speed but it can answer questions like "how does a microwave work?" with moderate accuracy at a semi-scientific level which is impressive. I suspect most devices will be able to run a 1b and by the end of the decade most everything will run a 4b model at least at talking speed. There's a concept that all AI processing will be done in the datacenter, I suspect 80%+ of consumer LLM will happen on the device, and more complex tasks will get routed to the cloud. For a lot of end users (high school students, etc) 98%+ of requests will be on-device.

Comment Seems to fall apart above 200 LOC (Score 1) 60

LLMs are really good at stuff, better and faster than humans, as long as the complexity isn't much more than ~200 LOC (lines of code). 250-300 LOC and things start falling apart quickly. Sometimes (1/50) you'll get ready and it'll pop out 400 LOC without major errors but that seems to be the absolute limit of the current statistical model family everyone is using.
 
LLMs are really good at analyzing and summarizing text though, it has no problem analyzing 20-30 page PDFs of economic or financial data.
 
But yeah there was this idea that if you just kept training on bigger datasets for longer eventually you'd just arrive at AGI and it's pretty obvious via many many research papers that the error limit right now is ~1% and getting below that is really really dang hard. We're going to need a new breakthrough to get the ball further down the field.

Comment Re:I have a sneaking suspicion... (Score 1) 60

It was applied, you just need a slightly more basic definition of evolution. Rather than "survival of the fittest" consider "survival of the stable". With that slight modification it handles the evolution of planets, reproducing molecules, life, species, stars, etc. And "the fittest" was always defined in terms of being stable in a particular environment.

Comment Transitioning to touch typing (Score 1) 188

Before I learned to touch type, I had managed to get pretty fast (I would estimate maybe 20-40 wpm) using a primitive hunt and peck technique. I more or less knew where they keys were, so I could use both hands and multiple fingers to type, but I needed to switch from looking at the screen to looking at the keyboard in order to not make mistakes.

After learning to touch type (on an electric typewriter - not a word processor), I probably tripled my speed, but the biggest advantage was being able to stay in context by looking at the screen instead of switching between the keyboard and the screen, and being able to fix mistakes while I was typing instead of having to go back and fix them after looking back up at the screen.

Of course, this was all pre mouse/gui, when memorizing and using keyboard shortcuts was not just a way of speeding up your workflow, but a requirement for basic functionality unless you wanted to continuously have the reference card taped to your desk.

In today's world, with continuous autospell correction, word and sentence completion, and even automated message reply suggestions... you can argue that actually typing as a form of communication is starting to become as antiquated as handwriting. The human is now more of a middle manager to all the machine tools, trying to put their individual stamp on the work of their electronic underlings (including LLM output).

Up until now, communication between humans was still a necessary and valuable skill. What happens when it is just bots writing memos to be read and summarized by other bots? I've already run into problems with people just refusing to read things and wanting meetings instead. Meetings don't scale, but apparently reading is just too hard... In that context, does it still make sense to put your skill points into writing things when people refuse to consume that output?

Comment Re:US total research is going down too. (Score 1) 56

It's not a coincidence, but the causation is not direct. It's just that both are driven by another cause. Both funding cuts to research, arbitrary decisions about visas, etc. are driven by xenophobic paranoia.

This *isn't* to claim that there aren't real concerns, but the real concerns are a trivial proportion.

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