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Among “the jobs once done by God [that] can be done by natural entities” there is life after death. Dawkins “frequently affirms that there is no life after death”, but Steinhart shows that this is inconsistent with Dawkins’ own convictions. Dawkins “should have argued that false religious theories of life after death can be replaced with more plausible scientific theories of life after death” [**].

Steinhart describes two plausible scientific theories of life after death: promotion to the higher level of reality of the simulators, and revisions of entire lives in new universes, each better than the previous life and universe. Worth noting, promotion could preserve memories and implement “the ancient idea of the resurrection of the body.” These theories of life after death are only sketched in this book, see Steinhart’s previous book “Your Digital Afterlives: Computational Theories of Life after Death” for more. See also my review of “Your Digital Afterlives” in “Tales of the Turing Church” (Chapter 12).

In summary, Steinhart builds a thorough and philosophically consistent spiritual naturalism, inspired by Dawkins, which offers the main mental benefits of religion. I like (actually I love) philosophy, but I try to keep mine as simple and working-class as possible, because many people don’t have the patience (or the time) for too much philosophical sophistication. I think the two approaches are complementary. So I use the term “religion” for the spiritual naturalism of Dawkins and Steinhart, and I use the simple term “God” now and then.

Tesla held Investor Day 2023 this week and announced the construction of a new plant in the Mexican state of Nuevo Leon. The new facility will be Tesla’s largest production facility.

Here’s What We Know

Elon Musk’s company will invest $5 billion to build the Mexican plant and create 5,000–6,000 jobs. Over time, however, the amount of investment and the number of jobs will double.

Humanoid robots are one of those ideas that never truly goes out of style — it does, however, tend to ebb and flow across the decades. Whatever you happen to think about the project or the company that built it, Tesla’s Optimus prototype has revived the conversation around the form factor and efficacy and viability of general-purpose robots. Boston Dynamics founder Marc Raibert told me in an interview this week, “I thought that they’d gotten a lot more done than I expected, and they still have a long way to go.”

It’s also reopened the debate. When I spoke to Playground Global partner Peter Barrett last week, he was quick to point out that our bodies aren’t exactly the hallmark of efficiency or product design, even if they made us sufficiently capable of outsmarting or out-running a wooly mammoth back in the day. The flip side of that conversation certainly makes sense however: We built our environment with us in mind, so it follows that we’d make robots in our image to perform our jobs.

Figure, which comes out of stealth this week, is very much in the second camp. Back in September, we broke the news of the startup’s existence. Founded by Archer co-founder Brett Adcock (who has also funded the company to the tune of $100 million), the startup is spending lot of time and money to build a general-purpose bipedal humanoid robot. It’s not an easy dream in any respect, of course. That no one has yet managed to crack the code certainly isn’t for lack of trying.

‘Losing jobs to ChatGPT will never happen. The human mind is the most flexible instrument — so what you should do is, use ChatGPT as the base and then show your creativity!’ says Infosys Founder NR Narayana Murthy on whether ChatGPT is likely to take away coders’ jobs. Speaking to the press on the sidelines of the Nasscom Technology and Leadership Forum, Narayan Murthy said, “In 1977–78 there was a thing called program generators. Everybody said the youngsters will lose all jobs, it didn’t happen… The human mind is the most flexible instrument. It can adapt very well. And all that happened was people start solving bigger and bigger problems, which these program generators could not handle.” Murthy said that ChatGPT is good and one should welcome it…

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Costing tens of thousands of dollars, these robots were clearing tables and keeping cafeterias clean.

If human workers have been complaining about robots taking over their jobs, the macroeconomic situation has now put robots out of work.

Over a hundred robots at Google’s parent company, Alphabet, have allegedly been fired after the team maintaining them was shut down, Wired reported.


After a dip in advertisement revenues last year, Google’s Alphabet is preparing for the worse by firing expensive robots. Over a hundred robots have already been fired after the team maintaining them was shut down.

Nice. But I’m more concerned about the jobs that will be lost from this.


#Zoox #youtube #ai #yahoofinance.
This segment originally aired on February 17, 2023.
Zoox CEO Aicha Evans joins Yahoo Finance Live anchors Dave Briggs and Seana Smith to discuss approval of its self-driving auto by the California DMV, the state of the autonomous vehicle industry, and Amazon’s ownership of the company.
Don’t Miss: Valley of Hype: The culture that built Elizabeth Holmes.
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About Yahoo Finance:

A second problem is the risk of technological job loss. This is not a new worry; people have been complaining about it since the loom, and the arguments surrounding it have become stylized: critics are Luddites who hate progress. Whither the chandlers, the lamplighters, the hansom cabbies? When technology closes one door, it opens another, and the flow of human energy and talent is simply redirected. As Joseph Schumpeter famously said, it is all just part of the creative destruction of capitalism. Even the looming prospect of self-driving trucks putting 3.5 million US truck drivers out of a job is business as usual. Unemployed truckers can just learn to code instead, right?

Those familiar replies make sense only if there are always things left for people to do, jobs that can’t be automated or done by computers. Now AI is coming for the knowledge economy as well, and the domain of humans-only jobs is dwindling absolutely, not merely morphing into something new. The truckers can learn to code, and when AI takes that over, coders can… do something or other. On the other hand, while technological unemployment may be long-term, its problematicity might be short-term. If our AI future is genuinely as unpredictable and as revolutionary as I suspect, then even the sort of economic system we will have in that future is unknown.

A third problem is the threat of student dishonesty. During a conversation about GPT-3, a math professor told me “welcome to my world.” Mathematicians have long fought a losing battle against tools like Photomath, which allows students to snap a photo of their homework and then instantly solves it for them, showing all the needed steps. Now AI has come for the humanities and indeed for everyone. I have seen many university faculty insist that AI surely could not respond to their hyper-specific writing prompts, or assert that at best an AI could only write a barely passing paper, or appeal to this or that software that claims to spot AI products. Other researchers are trying to develop encrypted watermarks to identify AI output. All of this desperate optimism smacks of nothing more than the first stage of grief: denial.