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Nina Schick
@NinaDSchick
Documenting how we’re manufacturing Intelligence | AGI & Geopolitics
6.3K Following    59.6K Followers
“ I see the problems as a sign of the engineering work that is ahead, rather than insurmountable barriers or the sky falling.” Quite.
The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field. I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so. First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world. The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability. Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended. I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent. Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.) Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration. Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building. [Original text (with links): ]
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The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field. I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so. First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world. The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability. Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended. I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent. Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.) Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration. Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building. [Original text (with links): ]
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There are two; and they don’t include France and Canada. Fixed it.
Canadian PM Mark Carney: There are only four countries at the forefront of AI: France, Canada, China and the United States. We must join forces to ensure an appropriate framework so that AI is safe and effective.
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Very good. The labs can built safety into their product, and must. Even more bullish on compute.
.@SecScottBessent: "It is humans who are responsible, not the AI. The Hugging Face incident — that is the responsibility of the OpenAI management, not a bunch of agents... These labs need to take responsibility for themselves."
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Having sense of purpose cuts your risk of dying by more than half. "Purpose does not mean ambition. It means feeling that your daily actions matter to something beyond yourself."
Having a reason to get up in the morning cuts your risk of dying by more than half. A 2019 JAMA study of nearly 7,000 adults found that people with the strongest sense of purpose had the lowest mortality, and the effect was independent of wealth, health, exercise, and depression. Purpose does not mean ambition. It means feeling that your daily actions matter to something beyond yourself. A grandparent raising a garden. A retired teacher who tutors. A caregiver who shows up every morning. The research does not measure achievement. It measures the feeling that what you do connects to something. The biological pathway runs through every system the body uses to stay alive. People with a sense of purpose sleep better, have lower inflammatory markers, take their medications, show up for screenings, and maintain social ties. Each of those individually lowers mortality. Together, they compound into a survival advantage that is larger than the sum of its parts. The opposite is also in the data. People who lose purpose, through retirement without a replacement, the death of a spouse, or the end of a career they defined themselves by, show a rapid decline in health that cannot be explained by aging alone. The body seems to treat purposelessness as a signal that the organism is no longer needed. Nobody writes "sense of purpose" on a prescription pad. The research says it belongs there.
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JUST IN: Meta is investing $115 million to train blue collar workers for guaranteed data center jobs.
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Mao killed so many people that it literally dipped the global life expectancy
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Merkel's legacy for Germany and the EU is devastating. Many leaders of the 2010s whom we once heralded as liberal defenders of Western democracies have proven to be the exact opposite. From shuttering nuclear power and building dependence on Russian gas to acceding to Putin's weaponisation of migration to test European resolve, her legacy is catastrophic. At the height of the 2015 migrant crisis, more than 10,000 people were entering Germany's southern border daily. Over 90% of arrivals were not checked !The political consequences are evident now. At the time, I was close to the Brexit negotiations. The migrant crisis was decisive in the British public's vote for Brexit, alongside the unwillingness of European leaders to offer David Cameron something substantial he could present as evidence of 'EU reform'. Of course, the greatest irony of all is that everything we thought these leaders stood for is undermined by an actual assessment of their legacy. We are at a similar turning point with AI. The decisions we make now about energy, sovereignty and growth will shape the balance of power for decades and determine whether Western democracies remain strong enough to defend their ideals. Amid the public hysteria about AI wiping out humanity, we should remember how much damage can be done when moral certainty takes the place of political judgment. "Stop AI" is the new "Stop nuclear," "Go green,” or “Wir Schaffen Dass.” Each promises a simple answer while avoiding the harder questions: How do we sustain innovation, generate prosperity and retain control over our own future? And we need to be honest about trade-offs. What does it mean for the United States (as Europe is no longer in contention), if it cedes its technology advantage in the age of Intelligence production? Europe's experience over the last decade shows us that the road to hell is paved with good intentions. We cannot afford to learn that lesson all over again with AI. The US is the standard-bearer now. IMHO, the existential risk is not that AI ends humanity: it is that the West (and US) stops leading it.
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Merkel left office five years ago to huge acclaim. Why? She ripped off Nato, cultivated gas dependency on Putin, cosied up to China and opened the door to a million migrants in 2015 alone. She, not the populist right, was the true extremist of our age
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Knowledge, bah! Who needs more knowledge? It is well known for having <gasp> Side-Effects. Whereas ignorance never hurt anyone!
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Amazing. But also testament to how it’s the older generation we need to worry about when it comes to AI-generated content.
Los vídeos que me manda mi mamá preguntando si es IA
Guy who pushed boulders down mountain complains about avalanche.
The U.S. economy will be pulling away from the rest of the world, AI investment already accounting for ~40% of U.S. GDP. This is a function of its utter dominance of compute - over 75% of global total - and the fact that AI at the frontier is American.
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My guess is that AI roughly doubles US GDP growth next year from ~2% to ~4%. Maybe even more.
The US–China competition to become the world’s first AI superpower is the defining geopolitical contest of the 21st century. But it is not primarily a contest between models. It is a contest over the industrial capacity required to manufacture and deploy Intelligence: energy, critical materials, factories, semiconductors, hardware and compute infrastructure. The country that leads will be the one that can secure and scale these foundations reliably. Model capability matters, but it is downstream of them. Without a sufficient industrial base, even the most advanced models cannot be trained, deployed or integrated into systems that create strategic power. The ambitions for AI are extraordinary. Their realization will depend on whether the infrastructure beneath them can keep pace with demand. AI leadership will therefore belong not to the country with the most impressive models alone, but to the country that can sustain the industrial base required to power and scale Intelligence. You cannot lead from the apex if you are hollow at the base.
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Data centres: the creator of community investment, wealth, jobs, cheaper utilities - and Intelligence.
JUST IN: Data centers now provide roughly 45% of all local tax revenue in Loudoun County, Virginia.
What AI has done so far: MEDICINE • Helped paralysed people speak again. (Brain implants turn intended speech into words, even recreating their own voice.) • Helped a paralysed man stand and walk again. (A brain–spine interface let him control his legs by thinking.) • Helped blind people read and understand the world around them. (Describing surroundings, reading labels and identifying objects through a phone camera.) • Uncovered cancers doctors would otherwise have missed. (29% higher breast cancer detection in a major study.) • Identified antibiotic candidates that kill drug-resistant bacteria. (Abaucin targeted a dangerous superbug in lab and animal tests.) LEARNING • Made personalised learning available on demand. (An ‘Einstein’ as your personal tutor whenever you want to learn.) • Helped students learn twice as much in less time. (A custom AI tutor outperformed an active-learning Harvard physics class.) • Helped people write, code, design and build without years of specialist training. SCIENTIFIC DISCOVERY • Predicted the structures of over 200 million proteins. (Opening new paths to understanding disease and developing medicines.) • Discovered planets hidden in telescope data. (Including Kepler-90i, the eighth planet in a distant solar system.) • Recovered ancient writing buried by Vesuvius nearly 2,000 years ago. (Reading inside carbonised scrolls too fragile to unroll.) • Begun unlocking how animals communicate. (Patterns in whale calls. Evidence that elephants use individual, name-like calls.) • Produced a proposed solution to one of mathematics’ hardest problems. (Navier–Stokes: 10,000 AI agents, 88 hours, according to OpenAI.) ENVIRONMENT • Predicted where a hurricane would strike nine days before landfall. (GraphCast forecast Hurricane Lee’s Nova Scotia landfall about three days ahead of conventional forecasts.) • Engineered enzymes that break down plastic in hours rather than centuries. • Detected wildfires before the first emergency call. (Spotting smoke and alerting firefighters earlier.) • Slashed the weedkiller farmers need by targeting weeds individually. (35% less herbicide in sugarcane trials, with nearly the same weed control.) ENERGY • Advanced the science of clean fusion energy. (Controlling and shaping superheated plasma inside an experimental fusion machine.) • Driven a generational wave of investment in carbon-free energy, from nuclear power to solar and wind. (Microsoft’s Brookfield deal alone targets over 10.5 GW of new renewable capacity by 2030.) TRANSPORT • Delivered dramatically safer driverless journeys. (Waymo: 81% fewer injury crashes per mile than human drivers in the areas studied.) • Given people who cannot drive a new way to travel independently. (Including blind passengers and older people who cannot drive.) JOBS AND GROWTH • Fuelled an investment boom. (AI-related investment categories accounted for an estimated 37% of U.S. growth in the first nine months of 2025.) • Driven demand for the skilled trades building AI infrastructure. (Electricians, welders, construction crews and cooling specialists.) WHAT AI HAS NOT DONE • Replaced all the radiologists. Guess what? We still need more of them. • Used a community’s water. Golf courses use more. (U.S. golf irrigation: roughly 550bn gallons in 2020. Data centres’ direct consumption: 17bn in 2023. Microsoft’s next-generation designs consume zero water for cooling.) • Raised everyone’s household electricity bills. (Oregon’s PGE: residential bills cut 1.3% after shifting costs to data centres. Indiana’s I&M: proposed household savings of roughly $100 a year, supported by large-customer growth.) • Demonstrated that it wants to kill us all.
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The polling on AI is dire. AI is now less popular than ICE. In China, 87% of the public trusts AI. In America, it is 32%. The country that owns the lion's share of global AI compute is also the country that trusts it less than immigration enforcement.
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