More Tech Leaders are Learning that AI Cannot Replace Humans – Efficiency and Accuracy Are Actually Getting Worse
If you were offered a choice between keeping your existing hands, or having them amputated and replaced with “new and improved” robotic hands, which would you choose? Image source.
by Brian Shilhavy
Editor, Health Impact News
When I began writing about the AI bubble and the future Big Tech collapse at the end of 2022 with the launch of ChatGPT’s first LLM (Large Language Models) AI app, I was just one of a handful of writers who have worked in Technology that was warning the public about the dangers of relying on this “new” technology.
There were a few dissenting voices besides myself back then, but now two-and-a-half years later and $trillions of dollars of LLM AI investments, barely a day goes by where I do not see articles documenting the failures of this AI, and reporting factual news about what its limitations and failures are, rather than pumping up the hype.
While the AI LLMs are truly revolutionary in what they actually can do, it is the faith in science fiction and what people’s perspectives and beliefs are about the future of AI that is ultimately going to destroy the U.S. economy, and most of the rest of the World’s economies as well, because they are literally betting on this science fiction actually becoming true one day.
Here are some recent articles that provide more than enough evidence that the AI “revolution” is going to come crashing down at some point, much like the many planes we have been watching fall from the skies due to tech failures and our over-reliance on computers over humans.
Air traffic and aviation accidents have actually INCREASED, and significantly so, since the advent of AI LLMs in early 2023, making air travel MORE dangerous, rather than safer.
Using AI to Write Computer Code
Much of the recent news about the problems with relying on AI have been regarding using AI to generate computer code.
AI Can Help Companies Become More Efficient—Except When It Screws Upby Martin Peers
The InformationExcerpts:
Artificial intelligence really does make mistakes—sometimes big ones.
Last weekend, I put half a dozen emails with details of airplane and hotel bookings for an upcoming vacation into Google’s NotebookLM and asked it to write me an itinerary.
The resulting document read great—until I realized it listed a departure date 24 hours later than the actual one, which could have been disastrous.
Similarly, my colleague Jon Victor today wrote about how some businesses using AI coding tools discover serious flaws in what they end up developing.
This point seems worth remembering as more businesses talk about the labor savings they can achieve with AI.
On Wednesday, for example, a Salesforce executive said AI agents—software that can take actions on behalf of the user—had “reduced some of our hiring needs.”
Plenty of companies are heeding suggestions from AI software firms like Microsoft that AI can cut down on the number of employees they need. More alarmingly, Anthropic CEO Dario Amodei told Axios in an interview this week that AI could “wipe out half of all entry-level white-collar jobs” in the next few years, even as it helps to cure cancer.
To be sure, not every job cut nowadays is caused by AI. Business Insider on Thursday laid off 21% of its staff, citing changes in how people consume information, although it also said it was “exploring how AI can” help it “operate more efficiently.”
We’re hearing that a lot: When Microsoft laid off 3% of its staff this month, it denied AI was directly replacing humans, but it still said it was using technology to increase efficiency.
This is where AI’s errors would seem to be relevant: Isn’t there a danger that AI-caused mistakes will end up reducing efficiency?
Leave aside the more existential question of why we’re spending hundreds of billions—and taxing our power grid—to create a technology that could create huge unemployment.
The more practical question may be whether businesses should use AI to replace jobs right now if they want to be more efficient.
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(Source.)
AI hallucinations: a budding sentience or a global embarrassment?Dr. Mathew Maavak
RT.com
Excerpts:
In a farcical yet telling blunder, multiple major newspapers, including the Chicago Sun-Times and Philadelphia Inquirer, recently published a summer-reading list riddled with nonexistent books that were “hallucinated” by ChatGPT, with many of them falsely attributed to real authors.
The syndicated article, distributed by Hearst’s King Features, peddled fabricated titles based on woke themes, exposing both the media’s overreliance on cheap AI content and the incurable rot of legacy journalism.
[…]
The trend seems ominous. AI is now overwhelmed by a smorgasbord of fake news, fake data, fake science and unmitigated mendacity that is churning established logic, facts and common sense into a putrid slush of cognitive rot.
(Full article.)
Some signs of AI model collapse begin to reveal themselvesby Steven J. Vaughan-Nichols
The Register
Excerpts:
I use AI a lot, but not to write stories. I use AI for search. When it comes to search, AI, especially Perplexity, is simply better than Google.
Ordinary search has gone to the dogs. Maybe as Google goes gaga for AI, its search engine will get better again, but I doubt it.
In just the last few months, I’ve noticed that AI-enabled search, too, has been getting crappier.
In particular, I’m finding that when I search for hard data such as market-share statistics or other business numbers, the results often come from bad sources.
Instead of stats from 10-Ks, the US Securities and Exchange Commission’s (SEC) mandated annual business financial reports for public companies, I get numbers from sites purporting to be summaries of business reports. These bear some resemblance to reality, but they’re never quite right. If I specify I want only 10-K results, it works.
If I just ask for financial results, the answers get… interesting,
This isn’t just Perplexity. I’ve done the exact same searches on all the major AI search bots, and they all give me “questionable” results.
Welcome to Garbage In/Garbage Out (GIGO).
Formally, in AI circles, this is known as AI model collapse.
In an AI model collapse, AI systems, which are trained on their own outputs, gradually lose accuracy, diversity, and reliability.
(Full article.)
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Bankrupt Microsoft-Backed ‘AI’ Company Was Using Indian Engineers To Fake It: Report
Excerpts:
Last week, British AI startup backed by Microsoft and the Qatar Investment Authority, Builder.ai, filed for bankruptcy after its CEO said a major creditor had seized most of its cash.
Valued at $1.5 billion after a $445 million investment by Microsoft, the company claimed to leverage artificial intelligence to generate custom apps in ‘days or weeks,’ which would produce functional code that had less human involvement.
Now they’ve gone cloth-off… as Bloomberg reports they had a ‘fake it till you make it’ strategy while having inflated 2024 revenue projections by 300%. Instead of AI, the company was actually using a fleet of more than 700 Indian engineers from social media startup VerSe Innovation for years to actually write the code.
Requests for custom apps were based on pre-built templates and later customized through human labor to tailor the requests sent to the company – whose demos and promotional materials misrepresented the role of AI.
According to Bloomberg, Builder.ai and VerSe Innovation ‘routinely billed one another for roughly the same amounts between 2021 and 2024,’ in an alleged practice known as “round-tripping” that people said Builder.ai used to inflate revenue figures that were then presented to investors.
In several cases, products and services weren’t actually rendered for these payments.
(Full article.)
Human Robot Assistants are Still a MythAI Agents Fall Short on ShoppingBy Ann Gehan
The Information
Excerpts:
Artificial intelligence heavyweights including OpenAI and Perplexity, along with commerce giant Amazon, are painting visions of AI tools acting as personal shoppers that can seamlessly buy stuff across the internet.
But the handful of AI agents that have so far been released have had trouble with online shopping, since they’re easily tripped up by variations in retailers’ product listings and checkouts, investors and founders say.
It’s also tough for retailers to distinguish between an agent and a malicious bot, so some merchants are more inclined to block AI tools from checking out rather than make their sites friendlier for AI to navigate.
“There are still a lot of instances where AI can’t make the transaction, or it can’t scrape information off a website, or you’re trying to deal with a small business or a mom-and-pop shop that is not AI optimized,”
said Meghan Joyce, founder and CEO of Duckbill, a personal assistant startup that helps users in part by using AI. (Source.)
Much of the current hype surrounding AI that new startups and investors are banking on are computer robots that they believe will soon be in the homes of most people doing routine household chores, watching your kids, and many other science fiction scenarios.
But there is no such robot currently on the market, and when you see video demos of what currently is in development, you are usually either viewing a robot following a carefully written script, such as the “dancing robots” Elon Musk showed off recently, or they are being remotely controlled by humans.
You cannot buy a personal robot today to live in your house and reduce your workload. They don’t exist, and probably never will.
Consider this story recently published about a new startup that is one of the first companies to just work on developing one part of a human robot: hands.
While this was published no doubt to create excitement and investment opportunities for the future, where the belief is that there will somehow be billions of these robots around the world, it actually does the opposite, depending on your point of view, as it shows just how far away we still are to developing a human robot that can do the same things humans can do, because they don’t even have hands yet that come anywhere close to operating like human hands.
The Startups Developing Robot Hands; OpenAI’s Revenue HopesBy Rocket Drew
The Information
Excerpts:
Humanoid robot hype is in full swing. The latest evidence is Elon Musk’s prediction Tuesday that by 2030 Tesla will be cranking out over a million of its Optimus humanoids—despite the fact that it has only said it was using two of them as of last year.
As the saying goes, in a gold rush, sell shovels. Now startups are trying to capitalize on the humanoid boom by developing robotic hands. In fact, some founders have recently left these bigger robot makers to focus on the parts.
“99.5% of work is done by hands,” said Jay Li, who worked on hand sensors for Tesla’s Optimus line before he co-founded Proception in September to develop robotic hands.
“The industry has been so focused on the human form, like how they walk, how they move around, how they look,” he noted.
But humanoid companies have overlooked the importance of hands, he said.
Hands are hard to get right. Think about the mix of pressure and deftness it takes to peel an orange (and not mash it to a pulp in the process).
(Source.)
While AI does have some useful purposes, it is still early in development to even make it reliable, and most of the investment in AI today is in what the AI idolaters believe AI will do, in the future.
And if that future never arrives, we are going to see the biggest collapse of modern society we have ever seen, and a “Great Reset” that is not exactly what the Globalists had in mind.
The Big Tech crash is coming, and when it happens, the cost of human labor will skyrocket, and there will not be enough humans to meet the demands of the public who have falsely depended upon the technology for all these years.
AI will not replace humans, and humans will be needed to clean up their messes and take out the trash with human hands.
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