https://cacm.acm.org/news/the-impact-of-ai-on-computer-science-education/

Reminiscent of how The Three Little Pigs used straw, sticks, and bricks to build their houses with very different results, Klopfer allowed one group to use ChatGPT to solve the problem, while the second group was told to use Meta's Code Llama LLM, and the third group could only use Google. The group that used ChatGPT, predictably, solved the problem quickest, while it took the second group longer to solve it. It took the group using Google even longer, because they had to break the task down into components.

Then, the students were tested on how they solved the problem from memory, and the tables turned. The ChatGPT group "remembered nothing, and they all failed," recalled Klopfer. Meanwhile, half of the Code Llama group passed the test. The group that used Google? Every student passed.

"This is an important educational lesson," said Klopfer. "Working hard and struggling is actually an important way of learning. When you're given an answer, you're not struggling and you're not learning. And when you get more of a complex problem, it's tedious to go back to the beginning of a large language model and troubleshoot it and integrate it." In contrast, breaking the problem into components allows you to use an LLM to work on small aspects, as opposed to trying to use the model for an entire project, he says. "These skills, of how to break down the problem, are critical to learn."

 

https://www.technologyreview.com/2025/03/26/1113802/china-ai-data-centers-unused/

China built hundreds of AI data centers to catch the AI boom. Now many stand unused.
The country poured billions into AI infrastructure, but the data center gold rush is unraveling as speculative investments collide with weak demand and DeepSeek shifts AI trends.

Just months ago, a boom in data center construction was at its height, fueled by both government and private investors. However, many newly built facilities are now sitting empty. According to people on the ground who spoke to MIT Technology Review—including contractors, an executive at a GPU server company, and project managers—most of the companies running these data centers are struggling to stay afloat. The local Chinese outlets Jiazi Guangnian and 36Kr report that up to 80% of China’s newly built computing resources remain unused.
...
For now, many data centers in China sit in limbo—built for a future that has yet to arrive. Whether they will find a second life remains uncertain. For Fang Cunbao, DeepSeek’s success has become a moment of reckoning, casting doubt on the assumption that an endless expansion of AI infrastructure guarantees progress.

That’s just a myth, he now realizes. At the start of this year, Fang decided to quit the data center industry altogether. “The market is too chaotic. The early adopters profited, but now it’s just people chasing policy loopholes,” he says. He’s decided to go into AI education next.

 

https://www.datacenterdynamics.com/...1bn-data-center-plans-in-licking-county-ohio/
Microsoft pauses $1bn data center plans in Licking County, Ohio
Another data center project bites the dust

The company later added that it will continue to own the land and intends to proceed with the development at some unspecified time in the future. In the meantime, land at two of the sites will be kept in a state that allows it to be used for farming, and the company is moving forward with its agreements for roadway and utility upgrades.

Farming should be good after all that hype BS being dumped on the ground about this project.

Keep it a farm and its taxed at farmland rates.

 

https://www.npr.org/sections/shots-...artificial-intelligence-mental-health-therapy
The (artificial intelligence) therapist can see you now

 

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This comment is hilarious :

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The capital of the state containing Dallas is ...?

The answer could just have easily been, Salem, in Oregon. It looks for the most popular/likely answer, not all possibilities.
It's not even wrong, it's pseudoscience or bad science to say these programs have human type intelligence or reasoning.

https://en.wikipedia.org/wiki/Dallas,_Oregon

 

The capital of the state containing Dallas is ...?

The answer could just have easily been, Salem, in Oregon. It looks for the most popular/likely answer, not all possibilities.
It's not even wrong, it's pseudoscience or bad science to say these programs have human type intelligence or reasoning.

https://en.wikipedia.org/wiki/Dallas,_Oregon

Wouldn't it also be right to say that the answer is Austin, Texas?

 

Wouldn't it also be right to say that the answer is Austin, Texas?

If the question was. The capital of a state containing Dallas is ...?
Yes, but the question was the state.

 

My head's gonna explode... this must be a linguistic problem

 

My head's gonna explode... this must be a linguistic problem

It just shows that linguistic issues (they don't really understand anything) don't matter much to these types of programs in queries, only statistical probabilities of the main tokens that are computer selected. Whats in-between is frosting to be discarded.

 

https://techcrunch.com/2025/04/18/openais-new-reasoning-ai-models-hallucinate-more/
OpenAI’s new reasoning AI models hallucinate more

OpenAI’s recently launched o3 and o4-mini AI models are state-of-the-art in many respects. However, the new models still hallucinate, or make things up — in fact, they hallucinate more than several of OpenAI’s older models.

Hallucinations have proven to be one of the biggest and most difficult problems to solve in AI, impacting even today’s best-performing systems. Historically, each new model has improved slightly in the hallucination department, hallucinating less than its predecessor. But that doesn’t seem to be the case for o3 and o4-mini.

According to OpenAI’s internal tests, o3 and o4-mini, which are so-called reasoning models, hallucinate more often than the company’s previous reasoning models — o1, o1-mini, and o3-mini — as well as OpenAI’s traditional, “non-reasoning” models, such as GPT-4o.

Perhaps more concerning, the ChatGPT maker doesn’t really know why it’s happening.

A nice way of saying the new models are lying more because these things don't reason or understand anything.

 

Anysphere is the company that developed the AI code editor Cursor. Recently, users found that when using Curson, they could not switch machines without having their session terminated. On checking with the company through its tech support, they were told that it was company policy not to allow this because of security concerns. But they had no such policy. The tech support was AI-powered and had confabulated * this policy, apparently because of a bug it could not reconcile. Subscribers of Cursor did not know this and assumed it was valid. Frustrated at this "policy", they cancelled their subscription. Anysphere became aware of this because of user posts on Reddit expressing their frustrations.

https://www.wired.com/story/cursor-...c=MARTECH_ORDERFORM&utm_term=WIR_Daily_Active

* similar to hallucinations. When AI is faced with a lack of specific knowledge, it tries to fill in this gap to complete a required response.

https://www.yahoo.com/news/customer-support-ai-went-rogue-120000474.html
A customer support AI went rogue—and it’s a warning for every company considering replacing workers with automation

For now, headline-making hallucinations have been limited to AI chatbots, but experts warn that as more enterprises adopt autonomous AI agents, the consequences for companies could be far worse. That’s particularly true in highly-regulated industries like healthcare, financial, or legal—such as a wire transfer that the counterparty refuses to return or a miscommunication that impacts patient health.

The prospect of hallucinating agents “is a critical piece of the puzzle that our industry absolutely must solve before agentic AI can actually achieve widespread adoption,” said Amr Awadallah, CEO and cofounder of Vectara, a company that offers tools to help businesses reduce risks from AI hallucinations.

 

https://www.msn.com/en-us/money/oth...al-books-before-canadian-election/ar-AA1DnI4l
AI Floods Amazon With Strange Political Books Before Canadian Election

AI didn't do this, humans attempting to manipulate an election did. Blaming it on AI is click-bait reporting.

 

https://www.ibm.com/think/insights/ai-agents-2025-expectations-vs-reality
AI agents in 2025: Expectations vs. reality

 

These AI helpers have their limits like all systems, but they are truly helpful when trying to rapidly get information.

Previously some questions would require a lot of web searching, gathering sources, reading them carefully then based on what you read perhaps further searching to refine your understanding.

This has been replaced by AI and saves a ton of time, I can actually ask a fairly involved question whereas before I had to search for terms, phrases, names and so on.

I also began to notice a change in how search engines were responding to searches starting a couple of years ago and I think they were trialing these LLM systems on the public by hiding them behind the search engine interface.

Here's a good example, I'm not an expert in this area and recently asked this, the answer was likely something that would have required a lot of digging two years ago:



here's another, a quick clear question that ordinarily requires trawling through manuals and datasheets:



Of course these system are not perfect but when used sensibly are extremely helpful.

 

It even knows that it isn't self aware, that's intelligence!

 

Look at this, an obscure subject yet it "understood" the question, responded within seconds and generated APL code!

 

Ok, by that standard, a calculator has intelligence.

 

 

View attachment 347731

Exactly, calculator intelligence.