MAROKO133 Hot ai: ChatGPT attempts 2,400-year-old Plato problem, surprises with ‘learner-l

📌 MAROKO133 Breaking ai: ChatGPT attempts 2,400-year-old Plato problem, surprises

AI chatbot ChatGPT-4 attempted a “doubling the square” problem, a 2,400-year-old mathematical challenge from Plato.

The University of Cambridge found that ChatGPT exhibited surprising “learner-like” behavior, improvising solutions and making distinctly human errors.

The ancient doubling the square problem, first described by Plato around 385 BCE, is considered a key lesson in mathematics education. 

The maths challenge

The puzzle has long fueled philosophical debate about the origins of knowledge.

As Plato once described, Socrates taught an uneducated boy how to double the area of a square. 

The boy initially made the error of thinking that doubling the side length would double the area. Through a series of questions, Socrates guided the boy to the correct solution: the new square’s sides must be the same length as the diagonal of the original square.

Researchers Dr. Nadav Marco and Professor Andreas Stylianides put this same challenge to ChatGPT-4. 

They tested ChatGPT-4’s problem-solving skills by posing a series of questions in the style of Socrates. Then, the chatbot was progressively challenged by introducing errors and new versions of the problem.

The central question was whether the chatbot would solve the problem by drawing on its vast training database or developing solutions. 

The team noticed that ChatGPT tended to “improvise its approach and, at one point, also made a distinctly human-like error.”

“When we face a new problem, our instinct is often to try things out based on our past experience. In our experiment, ChatGPT seemed to do something similar. Like a learner or scholar, it appeared to come up with its own hypotheses and solutions,” said Marco. 

Geometrical solution issue

ChatGPT is said to be typically weak at geometric reasoning due to its text-based training. But the researchers fully expected it to recognize this well-known problem and reproduce Socrates’ classical geometric solution.

“If it had only been recalling from memory, it would almost certainly have referenced the classical solution of building a new square on the original square’s diagonal straight away,” Stylianides said. “Instead, it seemed to take its own approach.”

Surprisingly, the chatbot initially opted for an algebraic method, a technique “unknown in Plato’s time.”

It resisted attempts to be steered toward the geometrical solution. 

Only when the researchers expressed their “disappointment” did the chatbot finally produce the geometric alternative. 

Even so, when directly questioned about Plato’s work, ChatGPT proved that it had a full understanding of it.

The researchers further presented two new challenges: doubling the area of a rectangle and a triangle. In both cases, ChatGPT again favored an algebraic solution, ignoring the researchers’ preference for a geometric one.

When pushed on the rectangle problem, it mistakenly claimed that no geometric solution was possible, even though there are.  

The researchers believe this error was not from its knowledge base but was an improvised guess based on their prior conversation about the square’s diagonal. 

However, after further prompting on the triangle problem, it eventually provided a correct geometric answer.

AI limitations

The researchers concluded that, from a user’s perspective, ChatGPT‘s behavior blended data retrieval with “on-the-fly reasoning.”

The team compares the chatbot’s behavior to the “zone of proximal development” (ZPD) educational concept. This is the space between “what a learner already knows” and what they can learn with help. 

Students can turn the AI’s limitations into a learning opportunity. 

The team says students should use prompts encouraging collaborative problem-solving, such as “Let’s explore this problem together,” rather than simply asking for the answer.

This would help develop their own critical thinking and reasoning skills. 

The study was published in the International Journal of Mathematical Education in Science and Technology.

🔗 Sumber: interestingengineering.com

📌 MAROKO133 Eksklusif ai: Anthropic Report Finds Dire News About AI's Effects

As businesses across the economy rush to adopt AI, a new report from OpenAI’s competitor Anthropic reveals what the tech is really being used for: instead of helping augment human labor, companies are mainly using AI to automate their jobs.

In numbers, an overwhelming 77 percent of businesses using Anthropic’s Claude AI software showed signs of automation, like “full task delegation,” according to the report released by the company this week. Only 12 percent of AI usage appeared to leverage the tech in an augmentation role, like learning or asking the bot for feedback. The report was based on data from Anthropic’s application programming interface, or API, through which customers access the AI software.

The findings are a stark reflection of businesses’ intentions by using AI, and add to the mounting anxiety of how the tech could affect the economy. While many AI leaders have warned that AI will severely disrupt the job market, it’s often balanced by the sunny promise that it will work alongside human workers to make their jobs easier. But if over three-quarters of the companies in the report are using AI for outright automation, it portends much darker implications.

That said, the report only concerns Anthropic’s Claude AI and may not necessarily be indicative of how other AI models, like OpenAI’s ChatGPT or Microsoft Copilot, are being used. As one of the leaders in the industry, however, Anthropic’s data provides a useful barometer.

According to the report, the plurality of what businesses are using AI for is coding at 44 percent, with office and administrative tasks a distant second at 10 percent. A proclivity towards full-blown automation appears to be business specific, with a comparatively smaller 50 percent of Claude usage from individuals showing automation of tasks.

The report also found that users are entrusting AI with more autonomy, with the proportion of requests in which users delegate entire tasks to Claude jumping from 27 to 39 percent over eight months. Meanwhile, countries with high adoption rates tended to show less automation, and more augmentation.

Among tech figureheads forecasting tough economic times ahead has been Anthropic’s own CEO Dario Amodei. This summer he predicted that AI could wipe out 50 percent of entry-level white collar jobs. OpenAI’s Sam Altman echoed that AI will destroy entire categories of human professions.

As seriously as these warnings should be taken, they’re also classic Silicon Valley overpromises. Six months ago, for example, Amodei also predicted that by now, AI would be writing 90 percent of all code. That’s nowhere close to being true.

In reality, there are still serious questions over the usefulness of AI tech and the quality of its work. Large language models still hallucinate false claims frequently, and the industry still has no idea how to make that issue go away. AI models also often ignore instructions and break their own guardrails, wreaking havoc like in the case of an AI “vibe coding” tool accidentally deleting a company’s key database. More capable autonomous AI agents remain painfully slow and limited in what they can do. The tech that we’re all being told will transform society as we know it seemingly doesn’t have what it takes to even take orders at a drive-thru.

On the other hand, there are also clear signs that AI is already having severe impacts on the job market, even if it mostly seems to be making things sloppier and worse.

AI-generated profiles and résumés are drowning out authentic applicants who are often applying at job postings that are themselves AI-generated. Then if you make the cut, you might be asked to interview with an AI system before you even get a sniff at trying to impress a human employee. And those with a job aren’t much better off, as bosses are openly gloating about replacing their human grunts with AI agents. Then again, many of these business owners are scrambling to hire employees to fix an AI’s broken messes or rehiring the workers they just fired.

When Bloomberg asked if the report supported Amodei’s prediction that AI will wipe out 50 percent of entry-level jobs, Anthropic’s head of external affairs refused to give a hard answer.

“We don’t know,” Sarah Heck told the newspaper. “This data shows something new is happening.”

More on AI: Man Applies for Job, Sits for Interview, Then Realizes They’re Trying to Peddle “Mock Interviews With an AI Interviewer”

The post Anthropic Report Finds Dire News About AI's Effects on Job Market appeared first on Futurism.

🔗 Sumber: futurism.com