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Lawrence Krauss welcomes Scott Aaronson to the Origins podcast, praising his remarkable intellect and contributions to quantum computing and AI safety. Aaronson, a leader in theoretical computer science, discusses his journey from winning the Waterman Prize to exploring the complexities of quantum computing and AI. He emphasizes the importance of understanding computational complexity and its implications for both fields. The conversation delves into the nature of quantum computing, highlighting its potential to solve problems that classical computers struggle with, such as factoring large numbers through Shor's algorithm. Aaronson explains that quantum computers operate on qubits, which can exist in superpositions, allowing them to perform calculations in ways that classical computers cannot. He also discusses the challenges of achieving fault-tolerant quantum computing and the significance of quantum error correction. As the discussion shifts to AI safety, Aaronson distinguishes between AI ethics, which focuses on the immediate societal impacts of AI, and AI alignment, which concerns ensuring that advanced AI systems act in accordance with human values. He notes the tension between these two perspectives and the need for a scientific approach to address the complexities of AI. Aaronson shares insights from his work at OpenAI, particularly on watermarking AI outputs to combat misinformation and misuse. He emphasizes the importance of developing methods to identify AI-generated content while acknowledging the limitations of current approaches. The conversation concludes with a reflection on the transformative potential of AI, likening it to past technological advancements while recognizing the unique challenges it presents. Throughout the podcast, Aaronson expresses a mix of optimism and caution regarding the future of AI, advocating for proactive measures to ensure its benefits while mitigating risks. He highlights the need for ongoing dialogue and research in AI safety and the importance of understanding the implications of these technologies for society.

In this a16z podcast, Ilyas Khan, founder and CEO of Cambridge Quantum Computing, discusses the promise and current state of quantum computing. He highlights its potential to revolutionize technology, likening its impact to that of the Industrial Revolution. Khan notes that corporate investment in quantum computing has surpassed academic efforts, with major players like Microsoft and Google leading the charge. He emphasizes that while the specific applications of quantum computing remain uncertain, possibilities include secure communications and advanced optimization problems, such as genome analysis and predictive behavioral analysis in finance. Khan also addresses the distinction between hardware and software development in quantum computing, asserting that startups will play a crucial role in creating quantum algorithms. He expresses optimism about the future of quantum technology, suggesting that it will unlock solutions to complex problems that classical computers cannot address. Lastly, Khan advocates for a strong emphasis on STEM education to prepare society for the advancements brought by quantum computing.

In this episode of the Into the Impossible podcast, host Brian Keating interviews John Preskill, a prominent physicist known for his contributions to quantum computing. They discuss the essence of quantum computers, which utilize quantum mechanics to solve specific problems more efficiently than classical computers, particularly in understanding complex quantum systems. Preskill emphasizes the importance of entanglement in quantum computing, describing it as a frontier for scientific exploration. The conversation touches on the Church-Turing thesis, which suggests that a universal computer can simulate any physical process. Preskill argues that quantum computers could update this thesis, allowing for efficient simulations of nature's processes. He acknowledges the current limitations of quantum computing, noting that while they excel in certain areas like cryptography and simulating quantum systems, their full potential remains to be discovered. Preskill also addresses misconceptions about quantum computing, asserting that it is not limited to cryptography and that its applications could extend far beyond current understanding. He highlights the need for more powerful quantum computers to unlock new discoveries in materials science and chemistry, although he cautions that significant advancements may still be decades away. The discussion shifts to the concept of quantum supremacy, which Preskill defines as a quantum device performing tasks beyond the capabilities of classical computers. He recounts Google's 2019 announcement of achieving quantum supremacy, where their quantum computer completed a specific task much faster than classical supercomputers. As the conversation progresses, they explore the relationship between quantum mechanics and cosmology, touching on topics like black holes and the nature of reality. Preskill shares insights from his experiences with Stephen Hawking and the ongoing debates about information loss in black holes, suggesting that quantum mechanics may provide answers to these profound questions. The episode concludes with Preskill offering advice on maintaining a sense of humor and humility in science, emphasizing the importance of being open to new ideas and experimental evidence. He reflects on the value of understanding both theoretical and experimental aspects of physics, encouraging future scientists to bridge the gap between the two.

Deep Prasad, a 26-year-old founder of Quantum Generative Materials, reverse engineers UFOs using quantum computers and has raised 15 million dollars for the startup. He cites Pentagon sightings with five observable properties—instant acceleration, hypersonic speed with no signatures—and argues these point to macroscopic quantum behavior rather than ordinary physics. He believes advanced materials underlie UAPs and that quantum modeling could identify them. To achieve this, the team uses quantum computing simulations to model complex materials, since the Schrödinger many-body equation scales badly on classical machines. They describe qubits, superposition, and entanglement as essential to representing atomic systems. They also discuss quantum sensing and potential impacts on AI, encryption, and cryptocurrency.

Hartmut Neven, leading Google Quantum AI, explains that quantum computers utilize quantum physics instead of binary logic, allowing for more powerful computations. He describes superposition and parallel universes as key concepts. Current advancements include algorithms for signal processing and potential applications in health monitoring. Neven emphasizes the importance of error correction and predicts significant future capabilities in medicine, energy, and understanding consciousness. Progress continues toward building a practical quantum computer.

Cryptographers safeguard secrets in a long-standing war between code makers and code breakers, particularly in the digital realm. Modern encryption, once thought unbreakable, faces a new threat from quantum computers, which can easily factor large numbers and break current encryption methods. Quantum mechanics allows qubits to exist in multiple states, vastly increasing computational power. While quantum computers promise solutions to global challenges, they also pose risks, as they could retroactively decrypt sensitive data. Cryptographers are urgently seeking new mathematical problems to create quantum-resistant encryption, exploring complex geometric problems to secure our digital future.

At the frontier where physics meets artificial intelligence, Guillaume Verdon argues that the path to truly powerful AI runs through the laws of nature themselves. Trained as a theoretical physicist, he describes a pivot from chasing a single unifying equation to building machines that mimic nature’s complexity. He helped pioneer Quantum Deep Learning, exploring how quantum information theory could guide neural networks, and he worked on early quantum algorithms and TensorFlow Quantum as the field formed. The aim, he says, is to understand the universe by compressing its data into useful representations. That scientific thread informs his current ventures: Extropy, the ambition to create physics-based AI processors; IAK and the Beff Jos persona used to explore ideas openly; and the broader EAK movement advocating rapid acceleration of AI. He describes a dual mission: embed AI inside the physics of the world, and embed the world’s physics inside AI. In this worldview, civilization’s growth depends on self-organization, adaptability, and increasingly intelligent systems that use energy more efficiently. Kardashev-scale thinking anchors the long-term goal: more intelligence per watt across the cosmos. Technically, Verdon describes Theramic computing—an approach that uses stochastic electron dynamics in superconductors and silicon to run learning algorithms at high speed with far lower energy cost than today’s GPUs. The project treats information theory, thermodynamics, and machine learning as a single framework, where Monte Carlo-style sampling can be realized physically. Early hardware will be silicon and room-temperature, with superconducting platforms for research. The promise is to accelerate problem-specific tasks, then scale to foundational models that adapt to many applications. On regulation and societal impact, he argues against heavy-handed AI restrictions and for policy that remains flexible as technology evolves. He frames AI as an augmenting partner—an ongoing, iterative process rather than a fixed upgrade—and notes that fear can undermine progress. The strategy includes open collaboration, openness about algorithmic tradeoffs, and a belief that distributed competition will align AI with human values. He also reflects on his Twitter-era Beff persona as a way to seed optimistic, future-facing memes that keep the pace of change constructive.

Brian Keating welcomes John Preskill, a significant figure in his career, to discuss quantum computing and its implications for fundamental physics. Preskill defines a quantum computer as a device leveraging quantum mechanics to outperform classical computers in specific problem-solving scenarios, particularly in understanding quantum systems. He emphasizes the importance of exploring the "entanglement frontier," where quantum states become highly correlated, presenting opportunities for scientific discovery. The conversation touches on the Church-Turing thesis, which suggests that a universal computer can simulate any physical process. Preskill argues for a "quantum Church-Turing thesis," positing that quantum computers can efficiently simulate natural processes that classical computers cannot. He acknowledges the current limitations of quantum computing, stating that while it excels in certain areas like cryptography and simulating quantum physics, its full potential remains largely unexplored. Preskill addresses skepticism regarding quantum computers, asserting that they are not universally superior but can dramatically speed up solutions for specific structured problems. He highlights the potential for quantum computing to revolutionize fields such as material science and chemistry, although practical applications may still be decades away. The discussion also covers the concept of quantum supremacy, which Preskill describes as the ability of quantum computers to perform tasks that classical computers cannot do efficiently. He recounts Google's 2019 announcement of achieving quantum supremacy, where their quantum device completed a complex task faster than the best classical supercomputers could. Preskill reflects on the technological advancements that have enabled the manipulation of single quantum systems, which are crucial for quantum computing. He notes that while significant progress has been made, challenges remain, particularly in error correction and scaling up quantum systems. The conversation shifts to the philosophical implications of quantum mechanics and artificial intelligence. Preskill expresses optimism about AI's potential to contribute creatively to scientific discovery, suggesting that human cognition is not inherently magical and can be replicated in machines. As the discussion concludes, Preskill shares wisdom about maintaining a sense of humor, being open to learning from experiments, and the importance of objectivity in scientific inquiry. He emphasizes the need for collaboration between theorists and experimentalists to advance the field of quantum computing and physics as a whole.

PsiQuantum’s interview centers on the company’s audacious plan to scale quantum computing into a commercially impactful, million-qubit machine, financed by a near $2 billion round and guided by a philosophy of building a transformational, rather than incremental, technology. The guest emphasizes that typical progress in quantum research has been slow, and PsiQuantum chose to invest in the full stack required for a very large system—specializing in semiconductor manufacturing, networking, cooling, and related infrastructure—rather than staging a sequence of smaller, market-ready demos. The conversation situates this choice within a broader tech landscape where frontier companies like TSMC, ASML, SpaceX, Nvidia, and OpenAI succeed by pushing the limits of science and engineering on the frontier, often with government backing. A central theme is that value will come not from selling a single device but from delivering access to a machine that can generate fundamental knowledge about chemistry, materials, and processes that currently elude conventional computation. To realize this, PsiQuantum has pursued a manufacturing-centric roadmap, partnering with a Tier 1 foundry in the United States, GlobalFoundries, and building out large-scale sites in Australia and Chicago to house the core capabilities and helium-based cryogenics needed for their architecture. The interview also delves into governance and validation: government-backed diligence, DARPA’s red-team approach, and the scrutiny of major investors like BlackRock, Baillie Gifford, Temasek, and others who have backed the venture as it tiptoes toward a stage where practical commercial deployments might emerge. The host pressing a hard question about a trillion-dollar valuation prompts a clarifying point that the business model centers on delivering time on the machine to enterprise customers, while exploring deeper vertical integration and R&D ecosystems to turn breakthrough findings into scalable revenue streams. The dialogue also covers the nuanced relationship with industry peers, the evolving perception of quantum as an instrument rather than a conventional computer, and the ethical and geopolitical realities of pursuing such a transformative technology. In closing, the guest reflects on the pace of site construction, the scale of the South Bay facility, and the aspiration to turn a foundational scientific leap into a generational business that redefines how industries innovate at the molecular and atomic levels.

Lawrence Krauss welcomes John Preskill, a prominent physicist and director of the Institute for Quantum Information and Matter at Caltech, to the Origins Podcast. They discuss Preskill's journey from fundamental particle physics and cosmology to quantum computing, a field he has significantly influenced. Preskill recalls his early interest in physics sparked by the space program and influential teachers at Princeton, including Val Fitch and John Wheeler. The conversation shifts to the hype surrounding quantum computing, with Krauss emphasizing the need to distinguish between reality and exaggeration. Preskill explains that quantum computers leverage the principles of quantum mechanics, particularly superposition and entanglement, to perform calculations that classical computers struggle with. He highlights the challenges of decoherence, where quantum systems interact with their environment, leading to errors in computations. They discuss various hardware approaches for quantum computing, including trapped ions and superconducting circuits. Trapped ions use electromagnetic fields to manipulate individual atoms, while superconducting circuits operate at low temperatures and utilize Josephson junctions to create qubits. Both technologies face challenges related to error rates in quantum gates, which must be minimized for reliable computations. Preskill introduces the concept of NISQ (noisy intermediate-scale quantum) devices, which are currently available but not yet capable of solving complex problems without significant error correction. He emphasizes the importance of quantum error correction, which encodes information in a way that protects it from environmental noise, allowing for more reliable computations. The discussion touches on the potential applications of quantum computing in fields like chemistry and materials science, as well as the need for new cryptographic systems to protect against future quantum threats. Preskill expresses excitement about the future of quantum computing, particularly its potential to deepen our understanding of quantum gravity and the nature of space itself. In closing, Krauss and Preskill reflect on the poetic nature of their discussions, highlighting the profound questions that quantum computing may help answer about the universe. Preskill's insights and experiences as a physicist underscore the ongoing journey of discovery in this rapidly evolving field.

A new bio-computer developed at Lund University could rival quantum computers by using myosin proteins to perform parallel computations with significantly less energy. This system, which is easier and cheaper to build than quantum computers, may be ready for practical use within a decade, potentially revolutionizing computing power in everyday devices.

In this a16z podcast, Chad Rigetti, CEO of Rigetti Computing, discusses the evolution and potential of quantum computing with Chris Dixon. They explore the limitations of classical computing, particularly as Moore's Law approaches its physical limits, leading to challenges in energy efficiency and manufacturing costs. Quantum computing, rooted in quantum mechanics, offers a new paradigm by encoding information in quantum states, allowing for exponential growth in computational power with each additional qubit. Rigetti highlights two primary applications for quantum computing: simulating quantum systems in computational chemistry and solving complex optimization problems relevant to machine learning. The conversation emphasizes the need for sophisticated classical computers to complement quantum systems, enabling hybrid algorithms that leverage both technologies effectively. The quantum computing field has grown significantly, with thousands of researchers globally, including efforts from major companies like IBM and Google. Rigetti aims to build a full-stack quantum computing platform, integrating hardware and software to facilitate access to quantum capabilities. While concerns exist about quantum computers potentially breaking current cryptographic systems, Rigetti believes the most exciting applications lie in advancing artificial intelligence and revolutionizing healthcare and energy solutions.

Joe Rogan welcomes physicist Michio Kaku back to discuss his latest book on quantum computing. Kaku explains that there is a race between the U.S. and China to dominate quantum computing, which could render current digital computers obsolete. Quantum computers operate on atoms, making them potentially millions of times more powerful than traditional supercomputers for specific tasks. However, Kaku believes it will take another decade to refine this technology for everyday use. Kaku outlines the historical progression of computing, from analog devices to digital computers, and now to quantum computers, which represent the final evolution of computing technology. He emphasizes the transformative potential of quantum computing in fields like medicine, where it could revolutionize drug testing and possibly lead to breakthroughs in aging and even immortality. The conversation shifts to the implications of AI and quantum computing working together. Kaku warns that while AI can produce impressive results, it lacks the ability to discern truth from falsehood, which could lead to misinformation. Quantum computers could serve as a fact-checking tool, helping to filter out inaccuracies in AI-generated content. Rogan and Kaku discuss the societal changes that quantum computing could bring, including the potential for a more interconnected world without language barriers. Kaku believes that as technology advances, it could lead to a type one civilization, where humanity harnesses the planet's resources and collaborates globally. Kaku reflects on his childhood fascination with science, sparked by the legacy of Einstein, and shares anecdotes about building a particle accelerator in his garage as a teenager. He expresses excitement about the current era of scientific discovery, particularly in quantum physics and the potential for understanding the universe. The discussion touches on the ethical implications of advanced technologies, including the possibility of creating new forms of life or consciousness through genetic manipulation or AI. Kaku emphasizes the need for responsible governance of these technologies to prevent misuse. Finally, Kaku reiterates the importance of quantum computing in shaping the future, highlighting its potential to empower the powerless and improve global living standards. He concludes by encouraging a collaborative approach to technology that prioritizes the well-being of humanity.

Peter Diamandis and Jack Hidary discuss the transformative potential of quantum technologies, emphasizing that we are the first generation capable of harnessing quantum information science (QIS) to manipulate the atomic and quantum world. They highlight the significance of quantum computers, sensors, and security, noting that these technologies can drive substantial improvements in various fields, including healthcare and climate science. Jack shares insights on his recent $500 million seed round and reflects on his journey with Peter, recalling their early involvement with XPRIZE and the private space industry. He emphasizes the importance of using advanced technologies to improve the world and mentions a recent expedition to Antarctica, where they explored the intersection of AI, quantum science, and climate change. During this expedition, they utilized quantum sensors to study marine life and potentially discover new species, aiming to enhance our understanding of climate dynamics. The conversation shifts to the differences between quantum computers and quantum technologies. Jack explains that while quantum computers are still developing, quantum sensing and simulation technologies are already available and can provide immediate benefits without the need for error correction. He elaborates on quantum sensors that can detect magnetic fields, including those generated by the human heart, and their potential applications in medical diagnostics. Jack also discusses the challenges of developing new drugs, highlighting the high failure rates in clinical trials. He advocates for integrating AI and quantum technologies to streamline drug discovery processes, reduce costs, and improve success rates. The duo emphasizes the need for collaboration and innovation to tackle significant health challenges, including neurodegenerative diseases. They address the growing quantum divide, where only a few countries have robust quantum programs, while many lack access to these technologies. Jack expresses a commitment to democratizing quantum knowledge and ensuring that it benefits all nations, not just the privileged few. Finally, they touch on the role of quantum technologies in addressing climate change, particularly through advancements in battery chemistry and renewable energy solutions. Jack stresses the urgency of utilizing quantum simulations to explore new materials and improve energy storage systems, ultimately aiming for a sustainable future.

Quantum computers can solve problems that classical computers cannot, such as modeling complex molecules and breaking encryption. They use quantum bits (qubits) that exist in superposition, allowing simultaneous computations. Qubits can be made from particles like electrons or atoms, and their states are linked through quantum entanglement. However, challenges remain, including maintaining qubits in a stable quantum state. Current designs include superconductors and quantum dots. While progress is being made, meaningful quantum computers are still decades away, with expectations likely to fluctuate during this period.

In this conversation, Lex Fridman speaks with Scott Aaronson, a professor at UT Austin and director of its quantum information center, focusing on quantum computing and its philosophical implications. Aaronson emphasizes the importance of philosophy in technical fields, arguing that it helps frame and understand complex questions, such as the nature of consciousness and free will. He discusses the historical context of computer science and philosophy, referencing Alan Turing's engagement with philosophical questions and the relevance of formal systems in practical applications. Aaronson introduces quantum computing as a new computational paradigm based on quantum mechanics principles, explaining concepts like qubits, superposition, and interference. He clarifies that quantum computers exploit these phenomena to solve problems faster than classical computers, although they do not operate in a magical realm outside traditional computation. The discussion touches on quantum supremacy, a milestone achieved by Google, which demonstrates a quantum computer performing a task faster than classical computers, though not necessarily useful yet. The conversation also addresses the challenges of building scalable quantum computers, particularly noise and decoherence, and the need for error correction. Aaronson highlights the potential applications of quantum computing in simulating quantum systems, which could revolutionize fields like chemistry and materials science. He cautions against overhyped claims in the quantum computing space, emphasizing the need for rigorous evidence of speed-ups over classical algorithms. Ultimately, the dialogue reflects on the intersection of science, philosophy, and the future of technology.

In this a16z podcast, Jeff Cordova and Vijay Pande discuss the evolution and potential of quantum computing. They emphasize the need to rethink algorithms for different architectures, such as GPUs and quantum computers, highlighting that quantum computing operates on probabilistic principles rather than deterministic logic. The conversation touches on the significance of hybrid computing, where classical and quantum systems interact, and the necessity of cloud access for quantum resources due to their complex operational requirements. They note that while quantum computing is still developing, it has the potential to solve problems beyond the reach of classical computers, particularly in fields like computational chemistry. The discussion concludes with the idea that the true capabilities of quantum computers remain largely unexplored, presenting both challenges and opportunities for future innovation.

In a coin game played on a quantum computer, the quantum system won almost every time due to its ability to harness superposition and uncertainty. Quantum computers operate differently from regular computers, allowing for potential applications in secure encryption, drug development, and information teleportation. These advancements could significantly impact security, healthcare, and communication in the future.

AI plans collide with hardware bets as Possible explores a future where wearables and AI converge. Humane, the AI pen, shut down and was acquired by HP for 116 million after funding. The discussion moves to wearables in professional settings: glasses that parse the world, assist with tasks, or help blind users locate doors. Initial adoption may be in nursing, medicine, firefighting, and public service, where augmented perception improves outcomes. Investors favor software, but some teams pursue quantum-powered acceleration for atom-scale problems, suggesting consumer gains will follow deeper, context-aware use rather than flashy hardware. Majira One, a Microsoft-backed quantum chip, signals a shift: quantum computing could accelerate drug discovery and materials research when enough logical cubits exist. Opinions differ on immediacy; 2,000 to 5,000 logical cubits are cited for meaningful security breakthroughs, and consumer benefits may still be years away. The UK is probing copyright rules for AI training, while Ishiguro frames the debate as a fork in the road for creators, balancing protection with innovation. Deep research tools promise speed but require verification, and Parth Patil says their best use is exploratory synthesis rather than definitive facts. Vibe coding and co-pilots suggest a future where software is built by describing needs, with natural languages becoming the interface while humans review results. The episode closes by highlighting AI's potential to enable faster, more collaborative creativity, despite pains.