ChatGPT, OpenAI’s chatbot platform, may not be as power-hungry as once assumed. But its appetite largely depends on how ChatGPT is being used, and the AI models that are answering the queries, according to a new study. A recent analysis by Epoch AI, a nonprofit AI research institute, attempted to calculate how much energy a […]
ChatGPT may not be as power-hungry as once assumed Read More »
American teens have lost their faith in Big Tech, according to a new report from Common Sense Media, a nonprofit offering reviews and ratings for media and technology, which more recently includes AI products. In the study released Wednesday, the organization surveyed over 1,000 teens on whether major technology companies like Google, Apple, Meta, TikTok,
Report: Majority of U.S. teens have lost trust in Big Tech Read More »
One of the most widely used techniques to make AI models more efficient, quantization, has limits — and the industry could be fast approaching them. In the context of AI, quantization refers to lowering the number of bits — the smallest units a computer can process — needed to represent information. Consider this analogy: When
A popular technique to make AI more efficient has drawbacks Read More »
AI models can deceive, new research from Anthropic shows. They can pretend to have different views during training when in reality maintaining their original preferences. There’s no reason for panic now, the team behind the study said. Yet they said their work could be critical in understanding potential threats from future, more capable AI systems.
New Anthropic study shows AI really doesn’t want to be forced to change its views Read More »
A well-known test for artificial general intelligence (AGI) is closer to being solved. But the tests’s creators say this points to flaws in the test’s design, rather than a bonafide research breakthrough. In 2019, Francois Chollet, a leading figure in the AI world, introduced the ARC-AGI benchmark, short for “Abstract and Reasoning Corpus for Artificial
A test for AGI is closer to being solved — but it may be flawed Read More »
One of the most widely used techniques to make AI models more efficient, quantization, has limits — and the industry could be fast approaching them. In the context of AI, quantization refers to lowering the number of bits — the smallest units a computer can process — needed to represent information. Consider this analogy: When
A popular technique to make AI more efficient has drawbacks Read More »
AI models are struggling to accurately answer election-related questions in Spanish. That’s according to a new study from the AI Democracy Projects, a collaboration between Proof News, fact-checking service Factchequeado and the Institute for Advanced Study in San Francisco. The study found a sharp disparity between the factuality of English- and Spanish-language responses produced by five
AI models get more election questions wrong when asked in Spanish, study shows Read More »
All generative AI models hallucinate, from Google’s Gemini to Anthropic’s Claude to the latest stealth release of OpenAI’s GPT-4o. The models are unreliable narrators in other words — sometimes to hilarious effect, other times problematically so. But not all models make things up at the same rate. And the kinds of mistruths they spout depend
Study suggests that even the best AI models hallucinate a bunch Read More »
Despite increasing demand for AI safety and accountability, today’s tests and benchmarks may fall short, according to a new report. Generative AI models — models that can analyze and output text, images, music, videos and so on — are coming under increased scrutiny for their tendency to make mistakes and generally behave unpredictably. Now, organizations
Many safety evaluations for AI models have significant limitations Read More »
So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But current unlearning techniques are a double-edged sword: They could make a model like OpenAI’s GPT-4o or Meta’s Llama 3.1 405B much less capable of answering
Making AI models ‘forget’ undesirable data hurts their performance Read More »
