VanillaCafe

It's called a lower bound.

Trying to understand it... if by comparison I'm using tmux then switching to something like this adds mouse based window (panel) management?

> For anyone wondering why it takes so long to actually switch this stuff out

One counterpoint is do we really NEED to have brightly colored foods? It's a hard problem if you need a food to be bright red. But, that has to boil down to strictly to improving sales, right? Hypothetically, if all the artificial food dyes were banned, then all food companies would be on the same level playing field.

I thought this might be a useful article because I've often had a similar question. But there's a diagram that has text:

> More simply put: imagine that you have red, green, and blue light sources. What is the intensity of each one so that the resulting light matches a specific color on the spectrum?

> ...

> The CIE 1931 color space defines these RGB color matching functions. The red, green, and blue lines represent the intensity of each RGB light source:

This seems very oddly phrased to me. I would presume that what that chart is actually showing is the response for each color of cone in the human eye?

In which case it's not a question of "intensity of the light source" but more like "the visual response across different wavelengths of a otherwise uniform intensity light source"?

... fwiw, I'm not trying to be pedantic, just trying to see if I'm missing the point or not.

> Unless you could somehow make an Alcubierre warp drive.

Even if you can make it, even though it's theoretically possible that the warp bubble could move through space faster than the speed of light, it's a separate and completely open question as to how you might actually get it to move that fast to begin with.

There are a lot of real world caveats that go into those range estimates. I just took my long range Tesla Model Y with an advertised 326 mile range on a multi-day road trip and I was stopping to charge about every 100 miles. I would love to get something with 3x the advertised range.

A pet nit, and the standards probably don't permit this, but for encoding 128-bit numbers, I prefer base-57 in my own implementations. 22 characters for a 128-bit encoding, same as base-64. You can split it into two 11-character 64-bit encodings. You can avoid the two non-alphanumeric characters in base-64 as well as the similar-looking characters like l1 and oO0. And it takes less visible space, so a bit easier for debugging and tabular output with otherwise no loss of generality.

Evidence suggests that none of this is true. Just look at how Google Fiber wasn't able to navigate the myriad regional regulatory roadblocks thrown up by local governments when lobbied by incumbent ISPs. It's reasonable to expect exactly the same scenario to play out if Google tries to make a competitive ride sharing service from scratch.

I think there is true emergence coming from these newest large language models, which is something that can't be captured by reducing the system to merely a mathematical Plinko machine. To understand emergent behaviors, the system really does need to be treated like a black box and experimented on.

And a secondary point, what if a large fraction of our intelligence comes from language, not the other way around. If that's true, then we might be well on our way to building the spark of an AGI.

Love the demo jitters as he picks up the frosted flakes, "Well that's working. That's good."

I can't seem to find the reference, but I seem to recall that Valve had specialized rendering logic for the power lines in Half Life 2?

I presume that's basically the same fundamental problem as rendering line art and star fields...

> They successfully show that Niemann was playing many games with a high percentage of "engine perfect" moves, but they do not do enough to show that this is inconsistent with what top players usually do.

I thought the video very much did make that case. A single known cheating game had a 98% correlation (Sebastien Feller Paris 2010), other GMs have generally at most 75% average correlation. The analysis had more than half a dozen games with Niemann at 100% correlation. If that's cherry picking, it seems like there are a lot of cherries to pick.

The real problem isn't the veracity of the information, but the consensus protocol we use to agree on what's true. Before the internet, we were more likely to debate with their neighbors to come to an understanding. Now, with the large bubbles we can find ourselves in, afforded by the internet social media, we can find a community to agree on anything, true or not. It's that lack of challenge that allows false information to flourish and is the real problem we need to solve.

> Maybe it would be worth spending some mental cycles thinking about the impacts this will have and how we design these systems.

Regardless if the bot is actually sentient, a portion of the population may _believe_ the bot is sentient.

If in practice the bot reflects back to each user their own views but perhaps more extreme, then this could be a terrible recipe for reinforcing and amplifying negative and socially destructive thinking -- equivalent to social media bubbles on steroids.

This can occur even without explicit bad actors trying to tip the scales toward a specific outcome. This kind of AI bot as-is has the potential to bring out the very worst in at least some percentage of the population.