The Algorithm Age

I'd be happy if by the time I retire, we have [ artificial intelligence ] systems that are as smart as a cat," Yann LeCun , Meta 's chief AI scientist, Turing Award winner and one of the founding fathers of deep learning, tells as part of an ongoing series of conversations about the future of AI , "and that retirement is coming fast, by the way, so I don't have much time." LeCun sees the extraordinary promise of AI on the horizon. But so far we haven't seen this degree of success. While venture capital and corporate investment pours billions of dollars into AI dream factories promising revolutionary transformations—whether it's curing cancer or finally taming the email inbox—a stark reality persists: Most artificial intelligence initiatives collapse under their own ambitions. The gulf between technological marvel and practical utility resembles a paradise island ringed by shipwrecks—the quest for supreme omniscience has left th...

The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications—from autonomous driving to robotics. Researchers at the Technical University of Munich (TUM) have now discovered that artificial neural networks can perform this task better when trained with biological data from early visual system development. The study is published in PLOS Computational Biology . Whether in mice, cats, or humans: Even before vertebrates open their eyes, a built-in training program begins in the retina—entirely independent of external stimuli. Spontaneous activity patterns spread in wave-like motions across the eye's neural tissue. This neural activity, known as "retinal waves," coordinates the early wiring between the retina and the brain's visual system. In a way, the eye starts practicing vision before encountering the real world. Researchers at TUM have now shown that artificial neural networks—which m...