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So far this series has found it training and agriculture – Two important challenges for the future of the human race – do not open up potential opportunities for artificial intelligence (AI) to show its great power. This last part of the series examines another headline area of AI – cars – cars – and examines the challenges that AI faces due to the nature of the high-tech industry itself.
One can often hear the assumption that AI will one day control transport. Imagine cars that are not just electric. Railways and planes are controlled by the impersonal robot AI, another of which is likely to serve peanuts to planes and punch tickets on trains, riding in the middle aisle, demanding payment, especially on their cousins: bullet trains.
Union Pacific ( UNP) and the Canadian-Pacific (
KP) need to look forward to. Subways, ships, even bicycles and cars would move flawlessly. No accidents, no train delays, no rude taxi drivers, no problems. Clear messages about which track to find, where to sit down, unmistakable destination information, everything on time, etc.
Of course, in this digital world of dreams many thousands would be left without work. In fact, the first attempts to build such a system proved disappointing. Accidents, human errors and other factors make success unbelievable because people are always afraid of danger. As proponents of nuclear power know, the bad press is damned. One report on cars with a car shows 9.1 accidents per million miles driven compared to 4.1 for conventional cars.
Imagine a fast taxi running on a highway or highway, and a slow futuristic bus driving on an orthogonal track. One electronic fume can cause a malfunction. The self-government system will have several real people at the scene: drivers (replaced by robots), police (replaced by digital cardboard mannequins), medics (placed on electronic clipboards inside ambulances) to recognize the problem and respond.
As we saw in the discussion about AI and Agriculture (Part 2 of the Series), a person’s real successes include a lot of hard work, expense and trial and error. The Los Angeles Dodgers baseball team was originally called the Trolley Dodgers in the Brooklyn era. This is because trolleybuses were prone to almost colliding with real people. Robots can obey their programming and interact quite well with other robots, but they have problems with the unpredictable reactions of real people, like the former Brooklyns, who ignored beeps, whistles and police and did things their own way. Human error would be everywhere and would cause considerable resistance to the actual introduction of such a dangerous system.
Such a world, which allows you to fully carry AI, also requires obedience from people. People would be reluctant to object if self-government killed several dogs or even a random person. In the end, such a system would be considered flawless.
AI is not a top priority among high-tech giants
Distinguished high-tech giants and the way they work form a major barrier to AI development. Intel ( INTC), Amazon ( AMZN), ABB ( ABB), Yaskawa Electric Corporation YASKI) and IBM ( IBM) got what they have by developing very attractive products and services: fast computers, smartphones, great software, fast delivery, accurate payroll systems, robots, tracking devices, etc.
AI is something extra, not the center of what these rich companies are doing right now. The giants are trying to single out every small, promising AI campaign they can find. In part, they want to prevent another tech giant from owning AI and knocking them out of their nearly trillions of estimates. The creation of this industry could lead to the development of AI. It could also lead to the use of brains acquired from acquired companies in other areas related to the core businesses of the industry’s current giants. Instead of introducing a new learning system, the public can see a robot that runs twenty-four hours, door-to-door, truck-driven, deliveries driven by artificial intelligence. This will save you a lot of money in the long run.
Many years ago, companies resisted acquisitions; now they welcome it altogether. Such a setting could actually slow down the development of useful AI products and services. Small companies with good ideas can’t resist being bought by a giant, making a profit and heading into the future with attractive long-term contracts. However, the giants are unlikely to divert their attention to major businesses to create a new industry.
In addition, the current technology giants are already at risk of being broken. Which one is the real monopoly? Microsoft ( IFFT) has no competitors in office software. Metaplatforms ( FB) has bought many companies and has not been challenged by other technology giants as a champion on social media, no matter what he calls himself. (However, watch out for TikTok, owned by Byte Dance). Meta was also accused of conspiring with Google ( GOOGL) to avoid competition.
Investors understand that technology giants are huge. Because people like to post on Facebook Meta and search on Google, and the Internet itself is free, few worry about the huge size of corporations that own these important parts of daily life. That may change, and a government backed by a long-standing legal tradition is ready to pounce.
Following this model, AI can also be divided into separate camps. (To use high-tech language, you have to say “tongue and groove.”) Google will have aspects of AI in its search engine, and others will have their own bunkers with minimal overlap. The government is also not an alternative to promoting AI. Washington tends to spend money on unfeasible ideas. Private companies, at least, stick to profits, which does not allow them to spend huge sums of money.
We hope you found this series insightful, showing that AI’s great prospects may be much more limited than its stellar fans suggest. The next entry will move on to another issue in business and finance.
Michael McTag, Ph.D., is the executive vice president Capable global partners in New York, a private investment company.
Stock News Contributor: Michael McTag, Ph.D.
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