It’s important to understand AI’s “Ghost In The Machine” amid huge spending

Machine Learning


As most of the world’s biggest companies spend hundreds of billions of dollars in the race to achieve artificial general intelligence, the following documentary has been released. ghost in the machine It premiered at this week’s Sundance Film Festival, questioning both the dubious roots of AI in eugenics and racial “science,” the exploitation of workers in slums around the world, and the possibility that all this spending is a bit of a waste.

“It’s machine learning. The only difference now is that they have an enormous amount of computing power,” director Valerie Vich told me in a recent interview. “This movie pushes back on this story about superintelligence. It’s this AI Dwemer, will he become a god-like being or will he become something terrifying that will destroy humanity?”

In fact, feeding more and more compute to AI models has been a big push by multitrillion-dollar companies lately. Together, these companies plan to spend an estimated $1.4 trillion to build dozens of data centers in the U.S., despite concerns about the limits of water and power available to run all the centers and whether the results will actually achieve the results claimed by leading AI hipsters.

Ghost, The approximately two-hour book is structured around loosely connected “chapters” that examine AI’s deep roots, current issues, and uncertain future.

The first half or so of the film is about how we learned from Francis Galton’s attempt to use his cousin Charles Darwin’s new theory of evolution to legitimize British imperialism by measuring skulls to the American eugenics movement, which was eagerly emulated by Nazi Germany up until the birth of statistics, but Galton’s founding scientist Karl Pearson was a protégé of Galton’s and a conspicuously vile racist.

This lineage continues from efforts to measure intelligence such as the Binet-Simon test, which generates IQ scores, to Alan Turing’s creation of early computer systems to generate superhuman intelligence. The computer industry was primarily founded in the original Silicon Valley after William Shockley, a lifelong Palo Alto resident, co-developed the transistor, won the Nobel Prize, and founded companies in the region, producing notable spin-out companies such as Fairchild Semiconductor and later Intel.

Shockley was also a vocal and notorious scientific racist and eugenicist, and his views were amplified by early venture capitalists in Richard Draper’s Pioneer Fund. The push for superintelligence sits pretty comfortably next to the beliefs of the universe’s technology masters who seek to maximize their appearance and lifestyle for eternal life.

Later chapters explore the involvement of major AI organizations in recruiting desperate slum dwellers in Nairobi, Buenos Aires, India and elsewhere to perform the painstaking input task of training AI to be more human, and the resulting campaign in Kenya to push back on the situation.

The final section of the documentary details the uncertainty of whether all this spending will actually achieve the goals expected by its biggest backers. A clip of OpenAI CEO Sam Altman being asked what he would do if general artificial intelligence were introduced. He admitted he didn’t know. He will likely ask GenAI tools to build even better tools to find solutions.

Veatch’s documentary premiered in a week in which some of the world’s biggest companies deeply involved in AI in a desperate race for leadership announced quarterly results and large capital investments expected to continue.

For example, Meta directed that $115 billion to $135 billion be spent this year to accelerate lagging AI success using the open source Llama large-scale language model. Llama is underperforming despite being well-positioned to take advantage of Meta’s AI tools for ad-supported social media and messaging services.

Brad Gerstner, a frequent contributor to CNBC and a prominent supporter of AI investments in Silicon Valley, used his bullish pulpit on the cable channel to say, “If anything, we’re running out of computing. Sam Altman has been saying for two years that we don’t have enough computing, and now we don’t.”

At one point in my conversation with Veitch, I suggested that her film might want viewers to use an important variation of science fiction writer Theodore Sturges’s adage, “Ask me the next question.” Instead, we may need to “ask different questions” about AI and what we are trying to accomplish with all of this spending.

Her eyes lit up and she said she might steal it. Then I double checked my references and found a lot of validation results from sites like this one. This site includes a copy of Sturges’s 1967 essay on the subject. star trek He is a screenwriter and author of 11 books.

We also confirmed what ChatGPT thought was the source. The magazine claimed that the phrase was most reminiscent of Isaac Asimov, a highly prolific chemistry professor who wrote more than 200 science and science fiction books during Sturgis’s mid-century era. Asimov wrote extensively about non-human intelligence in books and short stories. me, robotappears in the first scene of the Vitch movie, etc.

Asked about Asimov’s involvement in “Ask the Next Question,” ChatGPT asserted that it “summarizes (Asimov’s) belief that progress comes not from final answers, but from continually questioning assumptions and moving inquiry forward. This idea also resonates strongly with his classic short stories.” last question (1956) focuses on humans asking ever deeper questions of an evolving supercomputer, but that exact phrase appears more often in his nonfiction commentary than verbatim in the story. ”

So, as the Veatch film suggests, you should ask the next question, ask another question, and even double-check the answers you get from AI tools because they might be wrong. Similarly, ChatGPT claimed that Veatch’s husband was “supposedly” a professor of sociolinguistics at King’s College, London. He’s not, Veach said.

That said, Veatch’s film features a variety of computer scientists, historians, and philosophers, many of them people of color, who have decidedly less exaggerated views of both the potential of AI and the roots of its problems. At least someone is thinking of asking a different question about one of the biggest problems of our time.



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