Every year, more than 2 million people in the United States are diagnosed with treatment-resistant depression.
Desperate for solutions, some brave patients are now volunteering to undergo surgery to place experimental ‘pacemakers’ into their brains.
These implanted electrodes are part of a treatment known as deep brain stimulation, which is currently used to address some cases of Parkinson’s disease and epilepsy.
Looking at my reflection in the rearview mirror with morning sunlight streaming through the windows, it’s now hard to ignore the shimmering strands of silver that seem to be multiplying on my head. You may have seen this happen to your parents, friends, pets, and perhaps even yourself?
Is hair greying linked to life stress?
What if this was reversible?
Taken far enough, and given enough compute, that trend points to an AI system capable of fully autonomously designing and developing its own successor. This is called recursive self-improvement. We are not there yet, and recursive self-improvement is not inevitable. But it could come sooner than most institutions are prepared for.
Using public benchmarks and previously unreported data from within Anthropic, The Anthropic Institute is showing that AI is already accelerating the development of AI systems. To take just one example: today, Anthropic engineers on average ship 8x as much code per quarter as they did from 2021–2025.
The technical trends discussed in this piece suggest that AI systems are going to become much more capable in coming years. These trends have huge implications. AI that can build itself would be a major development in the history of technology—one that could bring enormous good for the world in science, healthcare, and beyond. But full recursive self-improvement also might increase the risks of humans losing control over AI systems. If systems are capable of fully building their own successors, the ways we secure them, monitor them, and shape their behavior all grow much more important.
Blurry light from lens imperfections is a problem everywhere, from microscopes to telescopes to smartphone cameras. Using a tiny yet carefully engineered optical element and artificial intelligence, University of California San Diego engineers have built a way to spot and correct those distortions from a single image—a step that could make advanced optical systems faster, smaller and easier to use.
“We used a combination of fundamental physics, nanofabrication and machine learning to make hidden distortions easier to detect and correct,” said senior author Abdoulaye Ndao, an electrical and computer engineering faculty member in the Jacobs School of Engineering and an affiliate of the Qualcomm Institute at UC San Diego.
“Our fast, robust solution is tiny and easy to integrate into different optical systems,” he continued. “The weight is almost nothing, because the size of the sample can be one by one centimeter and half a millimeter thick.”
On April 21, the Munk Debates convened a special debate about gene editing in Deerfield, Massachusetts for 650 students at Deerfield Academy.
Motion: Be it Resolved, let’s engineer better human beings.
About the Debate:
New powerful engineering technology is already being used to edit human embryos, curing diseases and repairing defective genes before a child is even born. Some welcome this new science as a powerful tool to enhance human intelligence, memory, appearance and physical health. Why wouldn’t we embrace a science that allows people to live longer, healthier, and happier lives? Others warn that this new technology will be used to create designer babies and a new class of genetically “enhanced” elites. It will undermine human dignity and autonomy, and risk unleashing new diseases into the human gene pool. Playing G-d with human nature, critics argue, will result in a dystopian nightmare of our own making.
About the Debaters:
Arguing in favour of the motion was the biophysicist, best-selling author, biotechnology entrepreneur, and the former director of the Program on Medicine, Technology and Society at UCLA School of Medicine, Gregory Stock. His debate partner was the internationally acclaimed strategic philosopher and pioneering transhumanist Max More. Arguing against the motion was the prominent American bioethicist Ezekiel Emanuel, Special Advisor to the Director General of the WHO and a former founding chair of the Department of Bioethics at the NIH. His debate partner was the award-winning educator, author, and Professor of Reproductive Science at University College London, Joyce Harper.
Short-term memories are thought to be formed deep within the brain in structures such as the hippocampus, but little is known about how and where memory-related information is kept in the brain or the process of drawing on this information. A good example is the sound of a car horn—most of us recognize it as a warning and know how to respond, even though not all horns sound the same and the circumstances in which we might hear a horn are different each time.
New research led by Professor Lucy Palmer from The Florey’s Neural Network Group has uncovered new insights into how and where memory-related information is stored and how these memory banks are used. These findings improve our fundamental understanding of how the brain works, providing a springboard for other scientists to make further, disease-specific discoveries. The paper is published in the journal Science Advances.
“Using mice that we trained to respond to similar, but slightly altered sounds, we identified a long-range cortical circuit that links memory and sensory systems,” Professor Palmer said. “Our findings provide valuable insights into the cellular and network mechanisms that support learning and memory-guided sensory behavior.
I’ve spent years watching finance and technology slowly adapt to one another, but the shift we’re looking at right now is going to change the entire landscape overnight. We need to stop thinking of AI as just a software tool or a cool shortcut for writing emails. We are officially entering an era where computational power is a foundational global commodity—and the standard unit of that commodity is the AI token.
Think of it like digital energy. Just as factories consume kilowatt-hours of electricity, modern enterprises now have to “burn” tokens to power their workflows. In my latest piece, I break down the massive hidden risk of letting a few Big Tech hyperscalers control both the production of this raw material and the infrastructure of exchange. This is where the banking sector has to step in, not just to cut their own costs, but to act as the ultimate market makers for artificial thought.
I dive deep into how banks will soon offer token futures markets—allowing companies to hedge their computing costs the exact same way airlines hedge aviation fuel—and how autonomous AI agents will soon be transacting with each other using tokenized value. The institutions that build these financial rails now will own the next century of commerce, while the rest risk being left behind in an aging system.
Click through to read the full breakdown on how the machine-to-machine economy is actually going to work!
(https://www.linkedin.com/pulse/new-gold-standard-when-ai-tok…Resilience over Political Influence: History shows that attempting to lobby a system to be “less exploitative” rarely works because the system is designed for extraction. True survival in this model might mean finding “off-grid” pockets where the resource demand is low enough to fly under the AI’s radar, or where the land is unsuitable for massive data centers.
I have spent a significant portion of my career watching the tectonic plates of finance and technology grind against each other. Usually, it is a slow, methodical process—a gradual shifting of legacy systems adapting to new digital realities. But every so often, a shift occurs that is so profound, it completely redefines the landscape overnight. We are standing on the precipice of one of those shifts right now.
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Eric Schmidt is the former CEO of Google.
Dave Blundin is the founder of Link Ventures.
Chapters.
00:00 — The Rise of Digital Superintelligence.
09:26 — AI and Energy: The Power Behind Progress.
18:34 — The Future of Work: AI’s Impact on Jobs.
28:02 — Navigating the AI Landscape: Opportunities and Risks.
37:13 — The Role of Education in an AI-Driven World.
46:41 — The Ethics of AI: Balancing Innovation and Responsibility.
56:12 — The Future of Creativity: AI in Arts and Media.
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