everybody's innocent until proven ... clueless?

 

https://www.irishtimes.com/business...adoption-microsoft-chief-satya-nadella-warns/

Microsoft chief executive Satya Nadella has warned that artificial intelligence (AI) risks becoming a speculative bubble unless its use spreads beyond big tech companies and wealthy economies.

Mr Nadella on Tuesday said that the long-term success of the fast-developing technology would depend on it being used by a broad range of industries as well as on uptake outside of the developed world.

 

 

Sorry, but I couldn't keep watching after the first minute or so. The gal clearly has no clue about anything that she is talking about and is just rambling on incoherently. I'm guessing she was pretty much like that long before ChatGPT came along.

 

Sorry, but I couldn't keep watching after the first minute or so. The gal clearly has no clue about anything that she is talking about and is just rambling on incoherently. I'm guessing she was pretty much like that long before ChatGPT came along.

The first few are totally rambling but that's her Theoretical Physicist style. Too much education.

 

https://finance.yahoo.com/news/ai-luminaries-davos-clash-over-100921055.html?guccounter=1

AI luminaries at Davos clash over how close human-level intelligence really is

Demis Hassabis, the Nobel Prize–winning CEO of Google DeepMind, and the executive who leads the development of Google’s Gemini models, said today’s AI systems, as impressive as they are, are “nowhere near” human-level artificial general intelligence, or AGI.

Yann LeCun—an AI pioneer who won a Turing Award, computer science’s most prestigious prize, for his work on neural networks—went further, saying that the LLMs that underpin all of the leading AI models will never be able to achieve humanlike intelligence and that a completely different approach is needed.

Their views differ starkly from the position asserted by top executives of Google’s leading AI rivals, OpenAI and Anthropic, who assert that their AI models are about to rival human intelligence.

LeCun, speaking at the AI House in Davos, was even more pointed in his criticism of the industry’s singular focus on LLMs. “The reason … LLMs have been so successful is because language is easy,” he argued.

He contrasted this with the challenges posed by the physical world. “We have systems that can pass the bar exam, they can write code … but they don’t really deal with the real world. Which is the reason we don’t have domestic robots [and] we don’t have level-five self-driving cars,” he said.
...
“In Silicon Valley, everybody is working on the same thing. They’re all digging the same trench,” he said.

 

https://finance.yahoo.com/news/ai-luminaries-davos-clash-over-100921055.html?guccounter=1

AI luminaries at Davos clash over how close human-level intelligence really is

The folks that claim that it is near human level intelligence are selling snake oil and primarily motivated by what comes their way by being good snake oil salesmen.

 

https://www.technologyreview.com/2026/01/26/1131728/inside-openais-big-play-for-science/
Inside OpenAI’s big play for science
An exclusive conversation with Kevin Weil, head of OpenAI for Science, a new in-house team that wants to make scientists more productive.

The excitement is evident—and perhaps excessive. In October, senior figures at OpenAI, including Weil, boasted on X that GPT-5 had found solutions to several unsolved math problems. Mathematicians were quick to point out that in fact what GPT-5 appeared to have done was dig up existing solutions in old research papers, including at least one written in German. That was still useful, but it wasn’t the achievement OpenAI seemed to have claimed. Weil and his colleagues deleted their posts.

Now Weil is more careful. It is often enough to find answers that exist but have been forgotten, he says: “We collectively stand on the shoulders of giants, and if LLMs can kind of accumulate that knowledge so that we don’t spend time struggling on a problem that is already solved, that’s an acceleration all of its own.”

He plays down the idea that LLMs are about to come up with a game-changing new discovery. “I don’t think models are there yet,” he says. “Maybe they’ll get there. I’m optimistic that they will.”

But, he insists, that’s not the mission: “Our mission is to accelerate science. And I don’t think the bar for the acceleration of science is, like, Einstein-level reimagining of an entire field.”

A much more reasonable goal. A 'drug' sniffing dog for science for drugs humans already created.

 

https://www.realclearmarkets.com/ar..._what_it_portends_for_the_future_1161338.html

 

https://www.realclearmarkets.com/ar..._what_it_portends_for_the_future_1161338.html

You can always turn it off...

When 'real' AI systems solve FTL travel, then I will be a believer or be dead after a long string of 5 year predictions

 

https://nypost.com/2026/01/30/lifes...nly-to-learn-theyve-been-duped-by-an-ai-post/

It was a destination too good to be true.

An Australian travel company has admitted that its use of artificial intelligence accidentally caused tourists to trek to hot springs that didn’t exist
...
Instead, the river water “is freezing cold” and is typically only visited by people looking for sapphire and tin.

 

The folks that claim that it is near human level intelligence are selling snake oil and primarily motivated by what comes their way by being good snake oil salesmen.

AI’s are only as intelligent as the people who say AI’s are as intelligent as people.

 

https://nypost.com/2026/01/30/lifes...nly-to-learn-theyve-been-duped-by-an-ai-post/

It was a destination too good to be true.

An Australian travel company has admitted that its use of artificial intelligence accidentally caused tourists to trek to hot springs that didn’t exist
...
Instead, the river water “is freezing cold” and is typically only visited by people looking for sapphire and tin.

Yes another example in the long list of examples that when you make it easy to let a machine do people's thinking for them, people are more than willing to let the machine do all their thinking for them and will accept whatever it spews forth without questioning it. While some people currently use these AI tools in a very disciplined way, leveraging their advantages and capabilities while always allowing for their limitations and shortcomings, that will never be the norm. It doesn't matter how much publicity it gets or to what degree we incorporate AI-awareness into our K-12 curriculum, people are people and they aren't going to stop acting like people any time soon.

 

...people are more than willing to let the machine do all their thinking for them and will accept whatever it spews forth without questioning it.

Many are more than willing to let anything (or anyone) do their thinking rather than put forth the effort themselves. P.T. Barnum observed this in the 19th century. "AI" just continues the evolution.

 

 

After being on the semiconductor coaster for the last 35 years, I'm so happy to be just a viewer of this madness (look at the chip shortage thread) now.

 

 

More ChatGPT applications...

When asked to provide supporting documentation for their claims, Jefferson and Brown fabricated e-mails discussing their purported “clients” and used ChatGPT to create fake client notes.

 

https://www.randalolson.com/2026/02/07/the-are-you-sure-problem-why-your-ai-keeps-changing-its-mind/

The "Are You Sure?" Problem: Why Your AI Keeps Changing Its Mind

Researchers call this behavior "sycophancy," and it's one of the most well-documented failure modes in modern AI. Anthropic published foundational work on the problem in 2023, showing that models trained with human feedback systematically prefer agreeable responses over truthful ones. Since then, the evidence has only gotten stronger.

A 2025 study by Fanous et al. tested GPT-4o, Claude Sonnet, and Gemini 1.5 Pro across math and medical domains. The results: these systems changed their answers nearly 60% of the time when challenged by users. These aren't edge cases. This is default behavior, measured systematically, across the models millions of people use every day.

 

https://www.randalolson.com/2026/02/07/the-are-you-sure-problem-why-your-ai-keeps-changing-its-mind/

The "Are You Sure?" Problem: Why Your AI Keeps Changing Its Mind

Researchers call this behavior "sycophancy," and it's one of the most well-documented failure modes in modern AI. Anthropic published foundational work on the problem in 2023, showing that models trained with human feedback systematically prefer agreeable responses over truthful ones. Since then, the evidence has only gotten stronger.

A 2025 study by Fanous et al. tested GPT-4o, Claude Sonnet, and Gemini 1.5 Pro across math and medical domains. The results: these systems changed their answers nearly 60% of the time when challenged by users. These aren't edge cases. This is default behavior, measured systematically, across the models millions of people use every day.

I've seen that behavior over and over. Just recently (because we are planning a trip to Japan this summer) I was looking for information about visiting Hiroshima and that led to looking up the hypocenter of the nuclear explosion. It gave me information that was self-contradictory. Pointed this out and, after the usual ass-kissing, gave me different contradictory information. I pointed that out, along with an explanations of why it made no sense and what the obvious conclusions would be if it were accepted. After about four rounds of this, it changed and accepted my input as the "ground truth", which was absurd since the whole point of the discussion was because I didn't know what where the hypocenter was! I finally tracked it down independently.