Unless the poorest can afford the stuff because their jobs were automated to cut costs. Unless there is a universal income, full AI automation will cost more than just money, it's going to cost lives. We already let people starve imagine what will happen when we no longer have any leverage to bargain for better pay.

those who have power over the algorithms - governments and companies - will be the winners and basically everyone else will be losers to different degrees.

unless societies change and become much more democratic. and i mean direct democracy, not electing people who then govern everybody else.

plus democratization of economy and workplaces.

i see no other alternative.

So for my own understanding, how is Google going away? Are you saying that OpenAI will always be an ad-free alternative to Google, or that OpenAI will replace Google once they strike new deals with publishers?

Because if it’s the latter, then why would publishers want a different deal than the terms they get from Google. OpenAI would start moving closer to what Google is in terms of results being influenced and Google can always close the gap on the technical side to get closer to OpenAI.

> The problem with all of this is that the grid has to be transformed.

Yes, and that will be an enormous amount of effort, both to replace generation and to upgrade transmission.

At the same time, though, maintaining the existing grid is also an enormous amount of work. A large fraction of the power infrastructure will need to be upgraded or replaced by 2050 anyway, and the existing grid relies on enormous effort to extract hundreds of millions of tons of coal and gas every year.

"It will be a lot of effort" is true of anything to do with the overall grid, so it's not a useful argument against any particular proposal -- there is no easy option.

> To add in hundreds of millions of cars to the grid is going to break most of them.

“A future grid will absolutely be able to handle a future demand of transportation electrification.”

In fact, since EV charging has such flexible timing, it's a great option for easily integrating larger amounts of variable renewables such as wind and solar via time-of-use pricing (this article goes into more detail).

> I expect that many of the grids will require voltage changes. Going from 120 in the states to 220-240. Otherwise we will have to adapt millions of transformers for higher loads.

How would that help?

Changing home voltage from 120v to 240v is unlikely to do anything to help the grid, as the higher-voltage transmission lines would carry the same amount of energy (and current) either way. Running more transmission lines where needed is almost certainly a better option, and it's one the industry is already very familiar with deploying to address increased consumption.

The article mentions a gateway. What do you guys think this “gateway” is? Is this a long enough answer to allow me to post in this forum yet?

"Democracy is the worst form of government (except for all the others that have been tried).”

Why transfer when you can experience life through multiple bodies, wouldn’t that be something?

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Kind of a reach. I think the tech is revolutionary, but still a pretty niche product, especially when Google is so ubiquitous that you can type in just about any blank field on a screen and instantly do a Google search. I mean, Google is literally synonymous with 'internet search'. Let's come back in a year.

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The reason capitalism works now is that billionaires need workers, so they pay people to work, and those people use the money for things they need.

When they don't need workers anymore, because they can use AI, the vast majority of humans won't have a way to contribute to society well enough to earn a living.

The church will lose as we all realize their God does not exist because we are God's.

The goal of automation is to drive down the cost of labor. Historically speaking workers don't win when automation comes in, it drives down the cost of labor and makes them inherently less valuable which weakens their bargaining position when it comes to negotiating for wages.

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If you'd like to study a really good example of this, read about the luddites. Plenty of other good historical examples out there too if that's too old for your tastes.

How does this comment add value to your prior comment? I still don't understand after reading why billionaires are going to win because of AI.

With every rise in automation under capitalism, the losers will be the workers and the winners will be the capital owners. It has always been like this in the industrial revolution going back to when the loom replaced the weaving guilds and drove down the cost of labor which is the goal of automation.

Teachers would be medium term winners I think. AI has a ton of potential to automate or ease some of the most annoying parts of the job (generating material, lesson plans, emails) allowing them to focus on the more rewarding parts of the job.

Eventually AI could start to replace teachers but I think it will be a long while before parents are comfortable with a robot watching over their kids

Losers: Data analysts, entry level programmers, accountants

lol, sounds like the go programs are designed to massage your ego a bit

(Humans have been hopelessly left behind by Go AI for at least 5 years now, not even the top pros have any chance at all against go-playing computers)

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I agree with what you say about celebrity billionaireism but it's already starting to look like billionaires are going to find out first about how much they're really worth and the followers will have to find something more significant to worship.

Submission Statement: “Hydrogen (H₂) is expected to play a crucial role in reducing greenhouse gas emissions. However, hydrogen losses to the atmosphere impact atmospheric chemistry, including positive feedback on methane (CH4), the second most important greenhouse gas.”

With more and more governments subsidizing hydrogen production, we need to really be certain it won't cause more problems than it will solve.

> Unfortunately I brought a child into this world in 1990 before I learned of how serious the impending climate catastrophe was, and now I must accept that she could have children, and her children's children will have to bear this terrible burden as survival becomes nearly intolerable for most life on the planet.

You're carrying around way more guilt and anxiety about the situation than is supported by the science.

Take a look at the data in those links above. The world has changed. The consensus of science-based estimates is that the world will see about 2C of warming, leaving it far from the "intolerable for most life" scenario you fear.

Climate change is real, and will cause quite a lot of suffering for quite a lot of people, but the science-based projections for our future are very different than they were 20, 10, or even just 5 years ago, and for the better. If you tuned out in the past due to a lack of progress, now's a good time to tune back in and update your views in light of new and very different data.

Telling the truth, instead letting people indulge in naive optimism, adds something of value. Once humans are no longer needed because the people with power have machines to do everything for them, they'll leave the rest of us to starve in the streets.

Too many worship billionaires and hate their fellow humans (especially those of another color, religion, sexuality, etc.) to try to do anything to stop it. The hateful morons will stop any attempts to organize to make post-AI capitalism non-genocidal because they'd rather see others suffer, then not suffer themselves.

is this still the one that essentially had people look at 10 pictures while being scanned and then with that data, it could recreate almost more or less if these specific people were looking at those specific 10 images?

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The claims are interesting, but far more modest than people here seem to realize. This is what they say about their evaluation process:

we conducted two-way identification experiments: examined whether the image reconstructed from fMRI was more similar to the corresponding original image than randomly picked reconstructed image. See Appendix B for details and additional results.

So, if I understand correctly, they claim that if you take a randomly-generated image and an image generated by their system from an fMRI scan, then their generated image more closely matches what the subject actually saw than the randomly-generated image only 80% of the time.

This is statistically significant (random guessing would give only 50%), but the practical significance seems pretty low. In particular, that's waaaay far form a pixel-perfect image of what you're dreaming. The paper has only cherry-picked examples. The full evaluation results are apparently in Appendix B, which I can not locate. (I'm wondering wether the randomly-generated images had some telling defect, for example.) Also, the paper seems measured, but this institution seems to very aggressively seek press coverage.