How much energy does AI use compared to humans? Surprising study ignites controversy

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bt Bryson Masse - venturebeat -- AI’s carbon footprint is no open-and-shut case, according to scientists from the University of California-Irvine and MIT, who published a paper earlier this year on the open access site arXiv.org that shakes up energy use assumptions of generative AI models, and which set off a debate among leading AI researchers and experts this past week. The paper found that when producing a page of text, an AI system such as ChatGPT emits 130 to 1500 times fewer carbon dioxide equivalents (CO2e) compared to a human.

The paper concludes that the use of AI has the potential to accomplish several significant activities with significantly lower emissions than humans. However, an ongoing dialogue among AI researchers reacting to the paper this week also highlights how accounting for interactions between climate, society, and technology poses immense challenges warranting continual reexamination. From blockchain to AI models, environmental effects need to be measured In an interview with VentureBeat, the authors of the paper, University of California at Irvine professors Bill Tomlinson and Don Patterson, and MIT Sloan School of Management visiting scientist Andrew Torrance, offered some insight into what they were hoping to measure.

Originally published in March, Tomlinson said that the paper was submitted to the research journal Scientific Reports where it is currently under peer review. The study authors analyzed existing data on the environmental impact of AI systems, human activities, and the production of text and images. This information was collected from studies and databases that study how AI and humans affect the environment. For example, they used an informal, online estimate for ChatGPT based on traffic of 10 million queries generating roughly 3.82 metric tons of CO2e per day while also amortizing the training footprint of 552 metric tons of CO2e. As well, for further comparison, they included data from a low impact LLM called BLOOM. On the human side of things, they used both examples of the annual carbon footprints of average persons from the US (15 metric tons) and India (1.9 metric tons) to compare the different per-capita effects of emissions over an estimated amount of time it would take to write a page of text or create an image.

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Elon Musk’s Neuralink begins accepting human patients for trials of its brain implant

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by Carl Franzen -- venturebeat.com -- Do you want to put an implant designed by Elon Musk’s company Neuralink — perhaps best known for killing 1,500 test animals — into your brain? Are you at least 22 years old and do you have quadriplegia (loss of function in four limbs) from a spinal cord injury, or amyotrophic lateral sclerosis (ALS)?

Then you may qualify to participate in the first-ever volunteer human trials of Neuralink’s first brain-computer interface, which has begun recruitment for participants, as the company announced on its website today. “The PRIME Study (short for Precise Robotically Implanted Brain-Computer Interface) – a groundbreaking investigational medical device trial for our fully-implantable, wireless brain-computer interface (BCI) – aims to evaluate the safety of our implant (N1) and surgical robot (R1) and assess the initial functionality of our BCI for enabling people with paralysis to control external devices with their thoughts,” explains the blog post. The company has courted controversy for testing its implant on monkeys that allegedly resulted in their death (Musk has posted on his social network X, formerly Twitter, that the monkeys were terminally ill, anyway), but that apparently isn’t stopping it from moving forward to try the tech on humans, next, after receiving an exemption from the U.S. Food and Drug Administration in May.

What’s involved in the Neuralink implant human trials?

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Does daytime napping affect your brain health?

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ALBAWABA - by Mayar Alkhatieb -- According to a study by the University of California and the University of the Republic of Uruguay, regular napping may result in better and greater brain health. The research findings suggest a correlation between napping and larger brains, which has been linked to lower risks of dementia and other diseases. The study aimed to investigate if a link exists between napping and brain health. According to the study, a daytime nap can provide an additional bonus to maintain brain health by slowing down the rate of brain shrinkage as we age. Victoria Garfield, the lead researcher at the University of California, suggested that short daytime naps may be essential in maintaining brain health as we grow older. The research aimed to break the "medical myths" surrounding daytime napping and its health benefits.

The study analyzed data from people between the ages of 40 and 69, and it showed that those who take small naps during the day have better and greater brain health than others. Additionally, the study suggests that people who nap for 30 minutes or less benefit the most from napping. The study further suggested that napping earlier in the day may be less likely to disrupt sleep during the night. Research from various other universities like in the Netherlands and the United Kingdom showed that approximately a third of adults aged 65 or over take regular naps. However, taking naps regularly is likely not going to be an option for all people, especially those who have jobs and tasks to attend to, and napping later in the day may affect their sleep schedule, so as good as daytime naps are, the reality would be that not everyone will be able to find time for them.

Today’s AI is ‘alchemy,’ not science — what that means and why that matters |

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The AI Beat by Sharon Goldman ----  A medieval alchemist wearing a gray robe with a long white beard and glasses adjusts a machine made of beakers and vats A New York Times article this morning, titled “How to Tell if Your AI Is Conscious,” says that in a new report, “scientists offer a list of measurable qualities” based on a “brand-new” science of consciousness. The article immediately jumped out at me, as it was published just a few days after I had a long chat with Thomas Krendl Gilbert, a machine ethicist who, among other things, has long studied the intersection of science and politics. Gilbert recently launched a new podcast, called “The Retort,” along with Hugging Face researcher Nathan Lambert, with an inaugural episode that pushes back on the idea of today’s AI as a truly scientific endeavor. Gilbert maintains that much of today’s AI research cannot reasonably be called science at all. Instead, it can be viewed as a new form of alchemy — that is, the medieval forerunner of chemistry, that can also be defined as a “seemingly magical process of transformation.”

Like alchemy, AI is rooted in ‘magical’ metaphors Many critics of deep learning and of large language models, including those who built them, sometimes refer to AI as a form of alchemy, Gilbert told me on a video call. What they mean by that, he explained, is that it’s not scientific, in the sense that it’s not rigorous or experimental. But he added that he actually means something more literal when he says that AI is alchemy. “The people building it actually think that what they’re doing is magical,” he said. “And that’s rooted in a lot of metaphors, ideas that have now filtered into public discourse over the past several months, like AGI and super intelligence.” The prevailing idea, he explained, is that intelligence itself is scalar — depending only on the amount of data thrown at a model and the computational limits of the model itself.

But, he emphasized, like alchemy, much of today’s AI research is not necessarily trying to be what we know as science, either. The practice of alchemy historically had no peer review or public sharing of results, for example. Much of today’s closed AI research does not, either. “It was very secretive, and frankly, that’s how AI works right now,” he said. “It’s largely a matter of assuming magical properties about the amount of intelligence that is implicit in the structure of the internet — and then building computation and structuring it such that you can distill that web of knowledge that we’ve all been building for decades now, and then seeing what comes out.”

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AI can help screen for cancer—but there’s a catch

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by MIT Technology Review by Cassandra Willyard -- Just last week Microsoft announced that it had partnered with a digital pathology company, Paige, in order to build the world’s largest image-based AI model for identifying cancer. This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here. I just had a birthday, and you know what that means—I’m newly eligible for a screening colonoscopy. (#milestones!). I’ve been thinking about cancer screening a lot recently, because I’ve seen a handful of headlines in the past few months about how AI will revolutionize cancer detection. Just last week Microsoft announced that it had partnered with a digital pathology company, Paige, in order to build the world’s largest image-based AI model for identifying cancer. The training data set for the algorithm contains 4 million images. “This is sort of a groundbreaking, land-on-the-moon kind of moment for cancer care,” Paige CEO Andy Moye told CNBC.

Well, it might be. Last month, results from the first clinical trial of AI-supported breast cancer screening came out. The researchers compared two methods for reading a mammogram: a standard reading by two independent radiologists, and a system that used a single radiologist and an AI to assign patients a numerical cancer risk score from 1 to 10. In the latter group, those who scored a 10—the highest risk—then had their images read by two radiologists. The AI-supported model reduced workload by 44% and detected 20% more cancers. That sounds like a good thing. In theory, catching cancers earlier should make them easier to treat, saving lives. But that’s not always what the data shows. A study published in late August combed the literature for randomized clinical trials that compared mortality (from any cause, not just cancer) in two groups: people who underwent cancer screening and people who did not. For most common types of cancer screening, they found no significant difference. The exception was sigmoidoscopy, a type of colon cancer screening that involves visualizing only the lower portion of the colon.

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17 Doctors Failed to Diagnose This Boy’s Severe Pain. ChatGPT Came Up With the Answer

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by Diane Herbst -- today show -- For three years, her young son suffered from increasing pain and other symptoms – with no answers from 17 doctors. “We saw so many doctors. We ended up in the ER at one point. I kept pushing,” the boy’s mom, Courtney, who did not wish to reveal her last name for privacy concerns, told Today. Earlier in the year, this frustrated mom turned to ChatGPT to input information from her son Alex’s medical records, including notes from his MRI. “I really spent the night on the (computer) … going through all these things,” she told Today. Courtney finally discovered a correct diagnosis from the artificial intelligence technology. When ChatGPT suggested that Alex, whose medical odyssey started at the age of 4, could be suffering from tethered cord syndrome, a rare neurological condition associated with spina bifida, “it made a lot of sense," she told Today.

Her hunch was confirmed by a pediatric neurosurgeon: After viewing Alex’s MRI, “she said point blank, ‘Here’s occula spinal bifida, and here’s where the spine is tethered,”’Courtney recalled to the outlet. With the diagnosis, Courtney felt "every emotion in the book, relief, validated, excitement for his future,” she told Today. Tethered cord syndrome is caused by tissue attachments limiting the movement of the spinal cord within the spinal column, causing abnormal stretching of the cord, according to the American Association of Neurological Surgeons. Dr. Holly Gilmer, a pediatric neurosurgeon at the Michigan Head & Spine Institute who treated Alex, told the outlet that the condition is hard to diagnose in young children “because they can’t speak.” Several weeks ago, Alex underwent surgery to repair his tethered cord syndrome and is still recovering, according to Today.

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