Babbage from The Economist (subscriber edition)

Alzheimer’s disease affects more than 30 million people around the world and there is no cure. For decades, research on the neurological condition has been focused on proteins known as amyloid and tau, which build up in the brains of people and prevent neurons from functioning properly. But treatments that focus on flushing those proteins out of the brain have so far proved underwhelming. A growing number of scientists, however, have a radical alternative theory. What if a virus is to blame? What if infections are the triggers that cause the build-up of amyloid and tau in the first place? Host: Alok Jha, The Economist’s science and technology editor, with data and science correspondent Ainslie Johnstone. Contributors: Ruth Itzhaki of the University of Oxford; Pascal Geldsetzer of Stanford University; and John Hardy of University College London.Transcripts of our podcasts are available via economist.com/podcasts.Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+.For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.

Geoffrey Hinton, one of the godfathers of artificial intelligence and a Nobel laureate in Physics, discusses the stunning evolution of AI, likening its cognitive abilities to those of the human brain. He reflects on his early work in deep learning and neural networks while contemplating the swift advancements in AI technology. Hinton emphasizes the balance between AI's potential benefits in healthcare and education against its existential risks. With insights on language models and the significance of memory, he paints a vivid picture of an AI-driven future.

In 2012 scientists at the Large Hadron Collider (LHC) at CERN in Geneva found the Higgs boson. Things have been quiet since then on the “epic discovery” front—but that doesn’t mean the thousands of physicists working there have been idle. The collider is undergoing a years-long upgrade to make it even more powerful, so that it can probe even deeper into the fabric of our reality. When the LHC is eventually reborn as the “High-Luminosity LHC” by the end of the decade, it will begin a new chapter of discovery. We speak to the incoming boss of CERN to find out if the machine will finally lift the veil on the “new physics” that scientists have been searching for for decades.Alok Jha, The Economist’s science and technology editor, travels to the LHC at CERN in Geneva, where he meets the next director-general Mark Thomson, plus many of the scientists and engineers who are working on the LHC’s big upgrade. Transcripts of our podcasts are available via economist.com/podcasts.Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+.For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.

The world was shocked in 2018 when He Jiankui, a Chinese biophysicist, announced that he had helped to produce two girls whose genetic code he had edited when they had been embryos. His aim had been to tweak a gene that sometimes confers protection against HIV infections. No one had ever used the CRISPR gene-editing tool in reproduction before and it was completely untested in embryos. Scientists around the world condemned the work as wildly premature and possibly dangerous—the Chinese authorities agreed and Dr He was imprisoned for three years. Now, more than six years later, Dr He is back. And he still wants to prevent medical conditions by editing human embryos. But will the world ever be ready for this use of gene editing? Or will newer methods of editing human genes prove more promising?Host: Alok Jha, The Economist’s science and technology editor. Contributors: Emilie Steinmark, science correspondent at The Economist; Chinese researcher He Jiankui; Henry (Hank) Greely of the Stanford Centre for Biomedical Ethics; Panicos Shangaris of King's College Hospital.Transcripts of our podcasts are available via economist.com/podcasts.Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+.For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.

Translation is tricky business—not least when your subject belongs to a different species. But as evidence mounts that many animals are capable of rich, complex communication, scientists are trying to bridge the inter-species gap. Already, artificial intelligence has proved a valuable tool. But one ambitious technologist is trying to take these models even further. Could his new initiative one day allow humans to speak to their fellow animals? And what else might people learn in the process?Host: Kenneth Cukier, The Economist’s deputy executive editor. Contributors: Denise Herzing, founder of the Wild Dolphin Project; Aza Raskin, co-founder of the Earth Species Project, and The Economist’s Abby Bertics.Transcripts of our podcasts are available via economist.com/podcasts.Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+.For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.

Join Robert Berwick, a computational linguist from MIT, Federico Rossano, a cognitive science expert at UC San Diego, and Abby Bertics, a researcher specializing in non-human intelligence. They dive into the fascinating world of animal communication, comparing it to human language. The conversation explores whether animals possess their own languages and challenges our understanding of communication across species. Discover how AI could help decode these complex signals, reshaping our view of intelligence in the animal kingdom.

A sophisticated, predatory, multi-billion dollar industry is emerging from the shadows. It already rivals the size of the illicit drug trade. And it’s about to get bigger and much more powerful. The Economist’s Sue-Lin Wong follows a trail that starts with the collapse of a bank in rural Kansas to uncover a global, underground scam economy built around human trafficking, corruption and money laundering. Can it be stopped?Available now.To listen to the full series subscribe to Economist Podcasts+.

Yann LeCun, Chief AI Scientist at Meta and a professor at NYU, is a luminary in machine learning. He discusses the groundbreaking R1 AI model by DeepSeek and its role in reshaping technology. LeCun advocates for rethinking AI beyond conventional language models, emphasizing the need for architectures that enhance reasoning and memory. He highlights the critical nature of open-source projects in fostering innovation, while also contemplating the balance of AI's potential benefits against its inherent risks and limitations.

In this engaging discussion, former professional volleyball player Abby Bertics, sports data analyst James Tozer, and Google DeepMind's Petar Veličković delve into the transformative impact of AI on sports. They explore how AI is revolutionizing strategies in basketball and soccer, enhancing player recruitment and game tactics. The guests share insights on predicting injuries, analyzing player interactions using graph neural networks, and the challenges AI faces in capturing the complexities of human performance on the field.

In this engaging discussion, Kate Olmstead, a woman with Down syndrome, shares her firsthand experience with the emotional complexities of living with Alzheimer's disease. Joining her is John Hardy, a renowned neuroscientist who sheds light on the amyloid hypothesis and its connection to chromosome 21. They tackle the urgent need for inclusive clinical trials and improved treatment access for individuals with Down syndrome. The conversation explores the intertwined futures of these two conditions and highlights the potential for scientific breakthroughs through better representation in research.