He kind of left his prime I think, the humor becoming alternatingly a bit too esoteric or a bit too obvious, and kind of stale in general. Nothing particularly objectionable about the author comes to mind otherwise.

Math competitions need to start assigning problems that require counting the letters in fruit names.

Nice result, not too shocking after IMO performance. A friend of mind told me that this particular competition is highly time constrained for human competitors, i.e., questions aren’t impossibly difficult per se, but some are time sinks that you simply avoid to get points elsewhere. (5 hours on 12 Qs is tight…)

So when you are competing against a data center using a nuclear reactor vs 3 humans running on broccoli, the claims of superhuman performance definitely require an * attached to them.

Also accidentally posted in an old thread:

Hot take: If a text extruder’s winning gold medals at your contest, that’s not a sign the text extruder’s good at something, that’s a sign your contest is worthless for determining skill.

Have they ever discussed how much they take on average?

Cultish and Magical Overthinking are top shelf.

Urgh, I couldn’t even get through the whole article, it’s too disgusting. What a surprise that yet another “no politics at work”-guy turns out to support fascism!

@mawhrin just casually pitching “great replacement theory” there. What a little Nazi

just yesterday I saw this toot and now I know why

(I mean, they probably should’ve bounced the guy a decade ago, but definitely even more time for it now)

(sees YouTube video)

I ain’t [watchin] all that

I’m happy for u tho

Or sorry that happened

The commentator who thinks that USD 120k / year is a poor income for someone with a PhD makes me sad. That is what you earn if you become a professor of physics at a research university or get a good postdoc, but she aged out of all of those jobs and was stuck on poorly paid short-term contracts. There are lots of well-paid things that someone with a PhD in physics can do if she is willing to network and work for it, but she chose “rogue intellectual.”

A German term to look up is WissZeitVG but many academic jobs in many countries are only offered to people no more than x years after receiving their PhD (yep, this discriminates against women and the disabled and those with sick spouses or parents).

It’s because of research in the mid-80s leading to Moravec’s paradox — sensorimotor stuff takes more neurons than basic maths — and Sharp’s 1983 international release of the PC-1401, the first modern pocket computer, along with everybody suddenly learning about Piaget’s research with children. By the end of the 80s, AI research had accepted that the difficulty with basic arithmetic tasks must be in learning simple circuitry which expresses those tasks; actually performing the arithmetic is easy, but discovering a working circuit can’t be done without some sort of process that reduces intermediate circuits, so the effort must also be recursive in the sense that there are meta-circuits which also express those tasks. This seemed to line up with how children learn arithmetic: a child first learns to add by counting piles, then by abstracting to symbols, then by internalizing addition tables, and finally by specializing some brain structures to intuitively make leaps of addition. But sometimes these steps result in wrong intuition, and so a human-like brain-like computer will also sometimes be wrong about arithmetic too.

As usual, this is unproblematic when applied to understanding humans or computation, but not a reasonable basis for designing a product. Who would pay for wrong arithmetic when they could pay for a Sharp or Casio instead?

Bonus: Everybody in the industry knew how many transistors were in Casio and Sharp’s products. Moravec’s paradox can be numerically estimated. Moore’s law gives an estimate for how many transistors can be fit onto a chip. This is why so much sci-fi of the 80s and 90s suggests that we will have a robotics breakthrough around 2020. We didn’t actually get the breakthrough IMO; Moravec’s paradox is mostly about kinematics and moving a robot around in the world, and we are still using the same kinematic paradigms from the 80s. But this is why bros think that scaling is so important.

Not sure if analog turing machines provide any new capabilities that digital TMs do, but I leave that question for the smarter people in the subject of theorethical computer science

The general idea among computer scientists is that analog TMs are not more powerful than digital TMs. The supposed advantage of an analog machine is that it can store real numbers that vary continuously while digital machines can only store discrete values, and a real number would require an infinite number of discrete values to simulate. However, each real number “stored” by an analog machine can only be measured up to a certain precision, due to noise, quantum effects, or just the fact that nothing is infinitely precise in real life. So, in any reasonable model of analog machines, a digital machine can simulate an analog value just fine by using enough precision.

There aren’t many formal proofs that digital and analog are equivalent, since any such proof would depend on exactly how you model an analog machine. Here is one example.

Quantum computers are in fact (believed to be) more powerful than classical digital TMs in terms of efficiency, but the reasons for why they are more powerful are not easy to explain without a fair bit of math. This causes techbros to get some interesting ideas on what they think quantum computers are capable of. I’ve seen enough nonsense about quantum machine learning for a lifetime. Also, there is the issue of when practical quantum computers will be built.

this is one of those things that’s, in a narrative sense, a great way to tell a story, while being completely untethered from fact/reality. and that’s fine! stories have no obligation to be based in fact!

to put a very mild armchair analysis about it forward: it’s playing on the definition of the conceptual “smart” computer, as it relates to human experience. there’s been a couple of other things in recent history that I can think of that hit similar or related notes (M3GAN, the whole “omg the AI tricked us (and then the different species with a different neurotype and capability noticed it!)” arc in ST:DIS, the last few Mission Impossible films, etc). it’s one of those ways in which art and stories tend to express “grappling with $x to make sense of it”

The idea that a smart computer will be worse at math (which makes sense from a storytelling perspective as a writer, because smart AI who also can do math super well is gonna be hard to write)

personally speaking, one of the ways about it that I find most jarring is when the fantastical vastly outweighs anything else purely for narrative reasons - so much so that it’s a 4th-wallbreak for me ito what the story means to convey. I reflect on this somewhat regularly, as it’s a rather cursed rabbithole that instances repeatedly: “is it my knowledge of this domain that’s spoiling my enjoyment of this thing, or is the story simply badly written?” is the question that comes up, and it’s surprisingly varied and complicated in its answering

on the whole I think it’s often good/best to keep in mind that scifi is often an exploration and a pressure valve, but that it’s also worth keeping an eye on how much it’s a pressure valve. too much of the latter, and something™ is up

AGI: I’m not a superintelligence, I’m you.

@Soyweiser @BlueMonday1984 seems plausible tbh

This isn’t an idea that I’ve heard of until you mentioned it, so it likely hasn’t got much purchase in the public consciousness. (Intuitively speaking, a computer which sucks at maths isn’t a good computer, let alone AGI material.)

@PMMeYourJerkyRecipes @BlueMonday1984

The guy from the Federalist *doesn’t* want more ideological diversity in academia, he wants *less*. But he’ll settle for more as an interim goal until he can purge the wrong-thinkers.

In collaboration with cryptocurrency outfits Coinbase, MetaMask, and the Ethereum foundation, Google also produced an extension that would integrate the cryptocurrency-oriented x402 protocol, allowing for AI-driven purchasing from crypto wallets.

what could possibly go wrong

In either case, the goal is to maintain an auditable trail that can be reexamined in cases of fraud.

Which is a thing that you only need to worry about if you use these types of agents.

Which in any case you can’t, because

The protocol is built for a future in which AI agents routinely shop for products on customers’ behalf and engage in complex real-time interactions with retailers’ AI agents.

Pretty sure that’s a strawman.

I guess keeping in theme, “vibe replying”