The industry accepts there are 10x engineers But it hasn’t yet accepted there are 10x engineering *prompters* IMO it’s a real thing - and I’m not talking software factory token maxxers
The first thing I do is I try to make sure that if there is a summary at the very end, here are all the decisions that were made, I will read through that end to end. If there hasn't been, I will prompt for that decision process.
I would say, sometimes, I don't know if it's controversial, that very few developers understand memory management. And that makes it even harder to debug memory problems. And so the state of the art around memory debugging hasn't evolved all that much over the years.
I think one reason why um the the AIs have been scaled up less than you would have otherwise expected and like for example cost of of per token hasn't increased as much as you might have thought is because there's a benefit to doing more of your um work at small scale where you can run more training runs and get more cycles in
In other words, the absence of calcium is not the same as the absence of disease—it may simply mean the disease hasn’t reached the stage CAC is designed to detect.
So there have been lots of studies where they've done cooling hypothermia in people after traumatic brain injuries and concussions hasn't really shown much of an effect. What seems to be important is preventing hyperothermia.
we've gotten to a point now where it's generally accepted that potentially half of cases of dementia are preventable and I think the majority of that falls into those first two buckets Alzheimer's and vascular dementia
So one of the things is that the pace of development is definitely accelerated. One thing I wonder the pace of business hasn't accelerated though and that mismatch is going to become more and more apparent.
And if you're doing a 1.0 and the world hasn't seen you, you're not going to get that from consumers, ever. You have to ship it, and you have to build the entire kind of ecosystem so those consumers see it in the fullness so that when they do the evaluation and they spend their own money, then you're getting real feedback.
I think that, you know, the model that we've put together collectively about the relationships between archaic and modern humans is sort of accreted over time. There was this, you know, idea that modern humans are distinct and that Neanderthals and Denisovans are like sisters of each other. And then over time we developed and detected additional mixture events like this modern human into Neanderthal and then this other ones I didn't even talk about like super divergent lineage going into Denisovans and like all this other stuff.
Um so yeah, the the the um the core of what I do, like actually solving um the most difficult part of of a math problem, that hasn't changed too much. I still use pen and paper for that.
if you have to choose between, well, I could believe this thing and be ostracized or criticized or outcast from my community, or I could believe this other thing, which may not be that accurate, but it will get me praised and rewarded and accepted by my community. A lot of the time, the desire to belong overpowers the desire to understand.
I think um yeah, they're not very good at code that hasn't never been written before maybe is like one way to put it, which is like what we're trying to achieve when we're building these models.
He hasn’t posted since January, but I hope he gets back to it. We need more musings, especially musings I strongly disagree with so I can think about and explain why I disagree with them.
AI is really great at spewing out code that does something that a million GitHub repositories already do because it's learned the underlying pattern. It's notoriously hard to get to do something new that hasn't been done before, especially when it's a complex task.
Accepted practice is that for any given model that is a notable advancement, you're going to do two to 4x compute of the full training run in experiments alone.
So Tesla hasn’t found a different, better way to bring driverless technology to market. Waymo is just so far ahead that it’s dealing with challenges Tesla hasn’t started thinking about.
the way to be on the hook is to say, "This is only for people who are like this." Because if those people hate it, then you were wrong. Whereas if you say, "This is for everyone," you're allowed to hide behind, "Well, everyone hasn't found it yet."
while decoherence has the potential to solve this aspect of the measurement problem, it hasn't yet been satisfactorily done. Decoherence also certainly does not return us to Local Causality.
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