Jeff Bezos is backing Flourish, a new "neuro AI" startup with $500 million in funding and a reported $2.5 billion valuation, that aims to reinvent AI by studying the brain's architecture and building systems that learn continuously while using far less power than today's large language models. The company's long-term bet is that neuroscientists and AI researchers working together can uncover the brain's "core algorithm" and eventually create brain-inspired AI that runs on a tiny fraction of current compute. Wired reports: Rob Williams knows how to pitch Jeff Bezos: You write a press release as if your product has already been built. Bezos reads it and gives a thumbs up or down. Williams went through this process a lot as an executive on Amazon's "S-team," in charge of software products such as Alexa, until his departure last fall. But the pitch he made a few weeks later -- in December 2025 -- was different. Now he was collaborating with Thomas Reardon, a neuroscientist and repeat startup founder, and approaching Bezos as a funder, not a boss. Here's what Bezos, sitting on his yacht somewhere, read while Williams anxiously watched on Zoom: "Flourish is a neuro AI company that is solving the two most difficult problems facing AI today: power efficiency and continuous learning. We are building Cortex AI, the first synthetic intelligence system designed to match the computational capacity, learning efficiency, and power budget of the human brain." A month later, I'm lunching with Reardon and Williams in the Flatiron neighborhood in New York City. Reardon gets right to the point. AI has dug itself into a hole, he says. Though increasingly powerful, large language models are greedy consumers of computer power and data. Though the inspiration for LLMs was rooted in biology, current frontier models have little in common with the human brain. A person uses about 20 watts of energy to process information; a single chip in an AI training cluster uses more than 30 times that amount. The hyperscalers require thousands of chips and gigawatts of energy, enough to power small cities. And those models need to suck up virtually all of what humans have written. Each new model requires more, more, more. For all of that, the models don't learn. Once you train them, they're stuck. The goal, Reardon tells me, is to build "a synthetic artificial intelligence brain that runs on 50 watts or less." It should adapt to its conditions, be as nimble as a human mind, and burn a tiny fraction of an LLM's compute power and energy. The proof of concept is thriving inside our skulls. "There's something fundamentally wrong with saying, "I need to basically read every book ever written 20 times over in order to learn English,'" Reardon says. "A human baby does it with a couple hundred thousand utterances." Reardon and Williams haven't figured out yet how to build systems that match the magic of a human brain. What they have is a belief that an expert, well-resourced team -- of AI researchers and neuroscientists working essentially side by side -- can find the answer. The neuroscientists will conduct original wet lab experiments with some of the most advanced lab equipment available, to hunt for usable intel on the brain's architecture. They plan to release the models they're currently developing as near-term products on the path to a full reinvention of AI. The fuzziness of the proposal didn't bother Jeff Bezos. After reading Williams' two-pager, he chipped in $50 million. Other funding came from Lux Capital, Google Ventures, and Catalio, among others. Bezos then almost doubled his initial stake and told Reardon he'd have given more if they'd asked. Now with a war chest of $500 million and a reported valuation of $2.5 billion, Flourish just needs to invent a new way to do AI.

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"A DNA-editing feat involving editing the genes of early stage embryos was announced this week," reports the Wall Street Journal. They describe the feat as "a far cry from designer babies, but nevertheless a step in that direction." Dieter Egli, an associate professor of developmental cell biology at Columbia University and his co-authors, including Nathan Treff of Nucleus Genomics, a New York-based DNA-testing startup, say the technology could help fix disease-causing mutations in embryos. "We're not throwing the final 'OK, you will have gene-edited babies tomorrow' at the public," said Egli. "That is a process that can occur through discussion matched with scientific progress...." Previous gene-editing efforts have often used Crispr, which can cut out parts of the DNA sequence, but the technology can also cause damage if the wrong DNA is targeted or cut out. In 2018, Chinese scientist He Jianku said he used Crispr to tweak DNA in human embryos and was imprisoned for the work. The technology Egli's group used, called base editing, allows them to target individual DNA letters in sequences more precisely with fewer adverse effects... Egli's group focused on altering two genes, one that can raise the risk of heart disease and one that is tied to blood disorders like sickle cell disease, and the research showed they were sometimes able to do so successfully, in the same embryo, without damage. "I am generally supportive of the concept of embryo editing to prevent genetic disease," said Dr. Paula Amato, a fertility expert at Oregon Health & Science University who wasn't involved in the research... Base editing has been used in human embryos before, according to peer-reviewed studies. The technology was used to correct a disease-causing mutation and an Alzheimer's disease-risk gene variant, said Alexis Komor, associate professor of biochemistry and molecular biophysics at the University of California, San Diego, who wasn't involved in the work. "There really is not any unmet medical or clinical need for this, especially from an in vitro fertilization perspective," Komor said. "Usually what you'll hear is that they're doing it just so that you know we can prevent genetic diseases, but there are so many other better ways to do that." Using embryo editing to create babies is illegal in the U.S. and many other countries. Scientists have long worried that it is a slippery slope and that the technology could ultimately be used to promote eugenics. Her worry is that "they're basically building a blueprint" for more ethically problematic forms of embryo editing. "In my opinion, I think this is a huge no-no," Komor said. "There's just no ethical way to use this...." Nucleus Genomics Chief Executive Kian Sadeghi said his company plans to fund Egli's further research, building on the new findings. His company sells a polygenic embryo-screening product, which screens prospective parents' embryos and produces risk scores for their likelihood of developing disease, as well as factors like height, IQ and eye color. The company has said the IQ predictions are limited in accuracy. The research was published online Monday on a preprint server.

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Scientists "have made a discovery that may help prevent some people from developing lung cancer," reports the New York Times, noting that lung cancer "kills more people worldwide than any other cancer." A team of more than 80 researchers working across four continents have identified a set of proteins in the blood that accurately predict lung cancers more than five years before diagnosis. The scientists also found early evidence that an existing anti-inflammatory drug could significantly reduce lung cancer risk in people with elevated concentrations of these proteins, which they linked to inflammation. More research is needed before a test based on these proteins could be ready for use in patients. And scientists would still need to run a randomized trial to determine whether the drug prevents lung cancers. Still, outside experts said the findings, which were published on Thursday in the journal Cell, offer a promising starting point toward a long-held public health goal... Led by Dr. Swanton, Dr. Tej Pandya, a Ph.D. student, and other researchers took a set of 48,000 blood samples from the UK Biobank and used machine learning to identify 14 proteins associated with the development of lung cancer. When the researchers looked at the presence of those proteins and also took into account a patient's age, smoking status and history of lung disease, they were able to predict who would develop lung cancer more accurately than the best risk assessment models currently in use... Using mouse and cell models, the scientists showed that these proteins increased when a specific inflammatory pathway was activated. Smoking and air pollution can activate that pathway. This adds to the evidence that it isn't just genetic mutations caused by smoking, pollution or other factors that are driving lung cancers. Rather, Dr. Swanton said, the findings suggest that "smoke causes mutations and inflammation, which together cause cancer." They also found that the signature was increased in people who later developed chronic obstructive pulmonary disease and pulmonary fibrosis, pointing to a common inflammatory environment upstream of all three diseases.

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