Group items tagged

"Rather than being "taught" medical knowledge, the AI was asked to learn using unsupervised deep neural networks, known as autoencoders, without being given any medical knowledge. The researchers developed a method for translating the features found by the AI-only numbers initially-into high-resolution images that can be understood by humans."

"The paper, co-authored by researchers inside and outside Google, contended that technology companies could do more to ensure AI systems aimed at mimicking human writing and speech do not exacerbate historical gender biases and use of offensive language, according to a draft copy seen by Reuters."

"Ah, but isn't creativity a slippery concept - something that's hard to define but that we nevertheless recognise when we see it? That hasn't stopped psychologists from trying to measure it, though, via tools such as the alternative uses test and the similar Torrance test. And it turns out that one LLM - GPT-4 - beats 91% of humans on the former and 99% of them on the latter. So as the inveterate artificial intelligence user Ethan Mollick puts it: "We are running out of creativity tests that AIs cannot ace.""

"A POPULAR news outlet has been publishing articles written by AI since November, keeping it on the down low. Tech media site CNET has been publishing the articles since November, and lots of readers don't seem to have noticed."

"It is building a new robotics laboratory at Milton Park near Oxford, focused on the automation of chemistry and biology to accelerate drug development and its declared goal is "drugs designed by AI, made by robot"."

"And Israeli company Optimove is helping. It normally gathers customer data to create targeted online ads, but as a service to gambling companies it has trained its AI to flag the online players who are most at risk.  It analyzes the behavior patterns characteristic of gambling addicts, which include the hours of the day and night when they place bets, the time they spend on the betting site, and how much they keep on playing to 'chase their losses'."

"Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called "AI hallucinations". We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems."

"To find more glyphs, researchers led by archaeologist Masato Sakai of Yamagata University trained an AI program to identify relief-type glyphs in high-resolution drone images taken of the entire region. The program identified 1309 possible geoglyphs, and the team confirmed 303 of them with on-the-ground surveys, almost doubling the number of known geoglyphs of this type, the researchers report today in the Proceedings of the National Academy of Sciences."

"Or, as the New York Times summarised it, "doctors who were given ChatGPT-4 along with conventional resources did only slightly better than doctors who did not have access to the bot. And, to the researchers' surprise, ChatGPT alone outperformed the doctors." More interesting, though, were two other revelations: the experiment demonstrated doctors' sometimes unwavering belief in a diagnosis they had made, even when ChatGPT suggested a better one; and it also suggested that at least some of the physicians didn't really know how best to exploit the tool's capabilities. Which in turn revealed what AI advocates such as Ethan Mollick have been saying for aeons: that effective "prompt engineering" - knowing what to ask an LLM to get the most out of it - is a subtle and poorly understood art."

"The climate crisis could prove AI's greatest challenge. While Google publicises AI-driven advances in flooding, wildfire and heatwave forecasts, like many big tech companies, it uses more energy than many countries. Today's large models are a major culprit. It can take 10 gigawatt-hours of power to train a single large language model like OpenAI's ChatGPT, enough to supply 1,000 US homes for a year."

"Generative AI chatbots fail to adequately reflect fossil fuel companies' complicity in the climate crisis, a Global Witness investigation has found"

"The results are unfortunately not surprising - countless studies have shown that facial recognition is susceptible to bias. A paper last fall by University of Colorado, Boulder researchers demonstrated that AI from Amazon, Clarifai, Microsoft, and others maintained accuracy rates above 95% for cisgender men and women but misidentified trans men as women 38% of the time."

"To thwart such hackers, Elon Musk's OpenAI and Pennsylvania State University released a new tool this week called "cleverhans," that lets artificial intelligence researchers test how vulnerable their AI is to adversarial examples, or purposefully malicious data meant to confuse the algorithms. Once the vulnerability has been found, a defense to the attack can automatically be applied."

"Lexplore claims its technology is new-particularly the algorithm that separates typical from atypical readers. But the concepts it's based on aren't. Its tech draws from a deep well of previously-conducted research stretching back decades, which is generally supportive of using a combination of eye tracking and machine learning to screen for dyslexia. "Eye movements is one of the best ways to index reading ability at an incredibly in-depth level," says Julie Kirkby, a psychology professor at Bournemouth University in the United Kingdom, who has studied eye tracking and dyslexia for years."

"Whereas most machine learning algorithms can't hone their skills beyond an initial training period, the researchers say the new approach, called a liquid neural network, has a kind of built-in "neuroplasticity." That is, as it goes about its work-say, in the future, maybe driving a car or directing a robot-it can learn from experience and adjust its connections on the fly."

"The point of creating this vast portfolio of digital gun art is to feed an algorithm made to detect a firearm as soon as a security camera catches it being drawn by synthetically creating tens of thousands of ways each gun may appear. Arcarithm is one of several companies developing automated active shooter detection technology in the hopes of selling it to schools, hotels, entertainment venues and the owners of any location that could be the site of one of America's 15,000 annual gun murders and 29,000 gun injuries."

"However, since machine learning algorithms are what they eat (in other words, they function based on the training data they ingest), they inevitably end up picking up on human biases that exist in language data itself."

"The dark forest theory of the web points to the increasingly life-like but life-less state of being online. Most open and publicly available spaces on the web are overrun with bots, advertisers, trolls, data scrapers, clickbait, keyword-stuffing "content creators," and algorithmically manipulated junk. It's like a dark forest that seems eerily devoid of human life - all the living creatures are hidden beneath the ground or up in trees. If they reveal themselves, they risk being attacked by automated predators."

"Some Facebook users who recently watched a Daily Mail video depicting Black men reported seeing a label from Facebook asking if they were interested in watching more videos about "primates." The label appeared in bold text under the video, stating "Keep seeing videos about Primates?" next to "Yes" and "Dismiss" buttons that users could click to answer the prompt. It's part of an AI-powered Facebook process that attempts to gather information on users' personal interests in order to deliver relevant content into their News Feed"

"According to tweets from DeepMind founder Demis Hassabis, however, this time AlphaGo really did make mistakes. The AI "thought it was doing well, but got confused on move 87," Hassabis said, later clarifying that it made a mistake on move 79 but only realized its error by 87. AlphaGo adjusts its playing style based on its evaluation of how the game is progressing."