Yes, Google is profitable now. Tremendously so. But they're at risk of losing revenue and ceasing to be profitable as people cease using Google search and switch to asking questions of their AIs. So to retain their position as the place people go first for information, they have to stay ahead of the AI race. Well, they could also just sit back and wait to see if their competitors are overwhelmed by the query volume, but that risks losing traffic and then having to win it back. It's much better to keep it. And Google is better-positioned to win this race than its competitors both because of its existing infrastructure and expertise and because it already has the eyeballs.

In addition, you seem to be assuming that doubling serving capacity means doubling cost. Clearly Google is not planning to increase their annual operating expenses by 1000X. As the summary actually says in the third paragraph, Google is also going to have to improve efficiency to achieve the growth rate, with better models and better hardware. This is what the AI chief is challenging the employees to do; he's not challenging them to write bigger OPEX checks, that's his job.

I know a few. I don't know what it may or may not mean. It may be relevant that the ones I know used a community-based approach, where groups of homeschooling families worked together to create something akin to a school, with different parents teaching different subjects. This meant that while the kids socialization groups were small, they did hang out with and learn with other kids, not just their siblings.

It's more than that. Research into the possibility of a link between vaccination and autism has been done, and no correlation found. This is evidence that there is no connection and it's entirely different from a case where no research has been done. One is evidence of absence, the other is absence of evidence. The GP is equating them, but they're not remotely the same thing.

Show me all of the studies that have evaluated the correlation between FSM action and autism. There has been a lot of research on the possibility of a correlation between vaccination and autism, and no evidence of correlation has been found. There is an enormous difference between "We've looked hard and found no connection" (evidence of a negative) and "We haven't looked at all" (lack of evidence).

In addition, there's no need for the CDC to debunk a claims that are not being made, or non-harmful claims. To pick a less-ludicrous example, there's no significant population claiming that eating grapes causes autism, so there's no need for the CDC to address it. Further, if there were an anti-grape lobby touting a connection with autism, the CDC probably still wouldn't need to address it because some people avoiding grapes doesn't create significant health risks to others.

But there is a significant population claiming -- against strong scientific evidence -- that vaccines cause autism, and that claim is causing them to reject vaccines, which does create significant health risks for others. So, the CDC absolutely does need to address it, since public health is their job.

Your analogy is terrible, in every way.

Laser Cooling is very cool.

Modding me down doesn't make me wrong, mods.

My opinion as a pragmatist is that most western institutions do a passably good job most of the time, but are imperfect and need to be constantly scrutinized to make sure they're serving the interests of the taxpayers. But what I'm talking about here is trust. There are many things that institutions could do to communicate in a way that doesn't do so much harm to their trustworthiness. I think that's an area where people are still learning how to do it "the right way." We're not there yet.

Wait, I thought Tylenol caused autism. Is there Tylenol in the vaccines? What's going on? LOL

First of all, trust in institutions is falling everywhere across the western world, not just in the US, and that drop in trust is bipartisan in the US. Secondly, there are real reasons for a general decline in institutional trust. In medicine, but also in economics, with the 2008 financial crisis that was caused by a failure of the institutions that are supposed to regulate such things. The rush to label anyone who questioned the origin of the COVID-19 virus as racist, only to have most authorities eventually admit that a Wuhan lab leak was not only possible, but likely, was another example. Again, the falling trust isn't a left or right issue. Does it help when RFK Jr. is running the CDC? Obviously not. But do you really think the state governments are immune to this falling trust? Definitely not.

What's funny is that the CDC still publishes measles data but I wonder how long that will continue.

While I count myself among the tribe of people who think we should govern ourselves based on evidence-based logic and reason, I have to admit, my tribe is a rather small minority. If the majority of the people in a democracy will not buy into an idea simply because you've provided a sound and well-reasoned argument, then we're going to have to fall back on practical lessons. You'd think measles coming back would be a pretty good object lesson, but apparently not.

Another article where we see that things started getting worse in the 2012 to 2014 timeframe. Which just happens to be when a lot of teenagers started to get smartphones. It's not a coincidence.

You don't understand the problem. The LLM won't "rip off" content from a website like GoodFood. That's now how it works. It doesn't copy stuff wholesale. It's a text generator that tends to generate text that looks like its training data, in a similar way that a person retelling a story or a joke will retell it from memory, but the memory isn't a facsimile, just like our memory isn't verbatim. When outputting the text, it'll be similar, but it won't be identical. I mean, it might be, but it might output something completely different just due to a neural net weight that was affected by some other training data that was kinda similar.

Exactly. As technologists, we need the output of computers to be precise and accurate. LLMs might be precise, but they're very often inaccurate, and that's not acceptable to us.

The average person doesn't live in a world where accuracy matters to them. A colleague said she used AI all the time, and I asked her how. She said she often tells it the contents in her fridge and asks it for a recipe that would use those ingredients. She said, "yeah, and it's really accurate too." I don't know how you measure accuracy on a test like that, but it doesn't really matter. If you're just mixing some ingredients together in a frying pan, you probably can't go too far wrong. As long as you don't ask it for a baking recipe, it'll work out.

And I think that's what's going on. The people who love AI don't know enough to realize when it's wrong, or are just asking it open ended questions, like you would ask a fortune teller, and it spits out something generic enough that you can't disprove it anyway.

Bullshit. I live in the western US and have regularly driven through some of the least-populated areas of the country, but I've never seen an area you can go 500 miles without encountering any infrastructure. You might be able to accomplish it if you take careful note of where the truck stops are and go out of your way to avoid them, but on any realistic route you'll encounter truck stops -- if not towns -- at least every 150 miles.

As for charging infrastructure, if you stay on the interstates I don't think there's anywhere in the country you can go more than 100 miles without finding a Tesla Supercharger. Those aren't designed for truck charging, but this demonstrates that building out the infrastructure isn't that hard.