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    Leopold Aschenbrenner - China/US Super Intelligence Race, 2027 AGI, & The Return of History

    enJune 04, 2024

    Podcast Summary

    • AI computational power demandThe demand for computational power for AI technology is accelerating at an extraordinary rate, requiring billions of dollars for new power plants and data centers, and is expected to grow to 100 gigawatts by 2030, representing a significant portion of US electricity production.

      The development and implementation of AI technology is leading to an unprecedented demand for computational power, which is estimated to require clusters worth billions of dollars within the next decade. This industrial process, which involves building new power plants and data centers, is accelerating at an extraordinary rate, with NVIDIA's data center revenue growing from a few billion to over 20 billion dollars in a year. The $1,000,000,000,000 cluster, which is the largest training cluster, is expected to grow from a few hundred megawatts to 100 gigawatts by 2030. This represents a significant portion of US electricity production and is just the tip of the iceberg, as there will also be a need for inference GPUs. The investment required for these clusters is enormous, but it is seen as a necessary step for the advancement of AI technology and the revenue it generates. Companies like Microsoft and OpenAI are already planning clusters on this scale, and the market for AI accelerators is forecasted to reach hundreds of billions of dollars by 2027. The question remains whether these investments will pay off, but the belief is that they will as AI systems continue to advance and generate significant revenue for companies.

    • Test time compute overhangUnlocking test time compute overhang could lead to significant advancements in AI capabilities, making it equivalent to months of working time and enabling error correction and planning tokens.

      The progress of AI in the next few years will depend on unlocking the test time compute overhang. Currently, AI models like GPT-4 can answer questions and think for a few hundred tokens, but they get stuck and can't correct errors or plan effectively. This is like having a human think for only a few minutes on a problem. However, if AI models could think for millions of tokens, it would be equivalent to months of working time and could do much more. The question is how hard it is to unlock this overhang and learn the error correction and planning tokens. If it's not too difficult, it could lead to significant advancements in AI capabilities. The AI world is optimistic that this might not be too difficult because it's not a completely new ability for models to learn. In the next few years, we can expect AI to become smarter than most college graduates, limited but useful, and by 27 or 28, we might have AGI that is as smart as the smartest experts. This will change the way we work, making some tasks obsolete and others more productive. It's an exciting time for AI, and we'll continue to see progress as we unlock the test time compute overhang.

    • Deep Learning vs RoboticsDeep learning excels in learning rich representations through free chaining, while robotics lacks this ability to bootstrap with pretraining. However, both are steps towards creating intelligent agents that can read, think, and learn like humans.

      There are two paths to creating intelligent agents: scaling up system 1 autopilot (through brute force) and enabling system 2 thinking (through learning rich representations). The former is an improvement of existing capabilities, while the latter unlocks new, more complex abilities. The advantage of deep learning lies in its ability to learn rich representations through free chaining, which allows models to learn from vast amounts of data and generalize. However, these models still have raw capabilities that need to be refined, and the transition from pretraining to self-learning is ongoing. The difference between deep learning and robotics lies in the ability to bootstrap with pretraining. Humans learn by internalizing knowledge, not just processing information. RL and self-play are attempting to replicate this process, but the challenge lies in making it efficient and effective. The learning process for models is similar to human learning, where understanding comes from internalizing and distilling information. The goal is to create agents that can read, think, and learn like humans, and RL is a step towards achieving that. The path to creating intelligent agents is not a simple one, and it will require significant time and effort to figure out the details. However, the potential rewards are immense, and the ongoing research in deep learning and RL is a promising step towards unlocking the full potential of artificial intelligence.

    • AI economy disruptionBy 2027, advanced AI models may lead to massive disruption in the economy, potentially causing exponential growth for tech companies but raising concerns for national security establishments and governments

      As we continue to advance in AI technology, particularly with the development of more sophisticated models and increased computing power, we can expect significant changes in various sectors including the economy, politics, and geopolitics. By 2027, we may see the emergence of "remote workers" in the form of advanced AI models that can perform cognitive tasks, leading to massive disruption and potentially exponential growth in revenue for tech companies. However, this progress may also raise concerns and spark reactions from national security establishments and governments, as the implications of superintelligence on national power become increasingly apparent. The automation of AI research could further accelerate this progress, potentially leading to a decade's worth of ML research progress in a year or less. Overall, the advancements in AI represent a significant shift, and it's crucial to consider the potential impacts on various aspects of society.

    • Technological explosion from superintelligent AIThe development of superintelligent AI could lead to an unprecedented technological explosion, compressing centuries of progress into less than a decade, resulting in significant military advantages and intense competition for AI superiority, potentially leading to radical reactions and political changes

      The development of superintelligent AI could lead to an unprecedented technological explosion, compressing centuries of progress into less than a decade. This could result in significant military advantages, potentially even surpassing the importance of nuclear weapons. The competition for AI superiority could become extremely intense, with countries like China making significant efforts to infiltrate American AI labs. The transition to this new technological era may be gradual, starting with the automation of cognitive jobs and expanding to other fields of research and development. The realization of this impending technological shift could lead to radical reactions and significant political changes.

    • Great Power ConflictThe current geopolitical landscape marked by intense competition between the US and China could lead to profound and potentially terrifying consequences, including the rise of dictatorships with superintelligence and the diminishing influence of individuals as automation takes hold.

      The current geopolitical landscape, particularly the competition between the US and China, is being viewed as a return to historical norms of intense international competition and potential conflict. This is a departure from the recent period of relative peace and American hegemony. The stakes are seen as high, potentially affecting the future of liberal democracy and the CCP's continued existence. The timing of when this realization sets in and actions are taken is crucial. The consequences of this conflict, especially with the potential development of superintelligence, could be profound and potentially terrifying. It's important to remember that history shows that great power conflicts have been the result of various factors and have had significant impacts on the world. The possibilities for dictatorship with superintelligence are particularly concerning. The influence of individuals, even those with significant power, such as AI researchers, is expected to diminish as automation takes hold.

    • AGI geopoliticsControl and location of AGI clusters in democratic countries is crucial to mitigate risks of intellectual property theft, physical seizure, and irreversible security risks.

      As we advance in technology, particularly in the development of artificial general intelligence (AGI), there are significant geopolitical implications. The control and location of these massive computational clusters, which require vast amounts of energy, can have major national security consequences. The risks include the potential for intellectual property theft, physical seizure of compute resources, and the creation of an irreversible security risk by allowing authoritarian regimes a seat at the AGI table. It's crucial for these clusters to be located in democratic countries to mitigate these risks and ensure safety and stability in the development and deployment of AGI.

    • AI clusters location debateDespite regulatory hurdles and challenges, the US remains a viable option for building large-scale AI clusters due to potential for natural gas power or deregulatory push for green energy projects, as shown by historical industrial mobilization during WW2.

      The location for building large-scale AI clusters is a topic of intense debate, with some arguing that the Middle East is the best choice due to easier access to funding and fewer regulatory hurdles. However, others believe that the US, despite some challenges, is still a viable option, especially with the potential for natural gas power or a deregulatory push for green energy projects. The history of industrial mobilization during World War 2 provides an interesting analogy, as labor issues and supply constraints were major challenges back then, but were eventually overcome. Similarly, concerns about the US's ability to compete in the AI race may be overblown, and the country has the potential to get its act together and build the necessary infrastructure. Ultimately, it's crucial for the US to consider both natural gas and green energy paths to power AI clusters, and address regulatory and permitting issues to make progress.

    • AGI Collaboration with Middle Eastern CountriesMiddle Eastern countries with financial resources seek to engage in AGI research, but concerns of algorithm theft and security breaches exist, and collaboration could offer benefits for all parties while ensuring responsible development and equitable sharing of benefits.

      The race for Artificial General Intelligence (AGI) has attracted the interest and investment of various players, including Middle Eastern countries and sovereign wealth funds. These countries may not have the same level of technological capabilities as the United States or China, but they offer significant financial resources. The fear is that if the US and other democratic countries do not engage with these nations, they may turn to China instead. However, the argument for collaboration is that these countries could be part of a broader coalition, where they are offered some benefits of AI in exchange for their financial support. The concern is that if the technology is not shared, these countries may be able to steal the algorithms and codes, which could be easily exported and used to build their own AGI capabilities. The security of current AI labs is not robust enough to prevent such thefts. The value of AGI lies not just in the code but in the intuition and ideas of the researchers, which cannot be easily stolen. However, the differences in hardware and trade-offs may require significant rewrites and adjustments, making it a complex issue. Ultimately, the goal should be to ensure that the benefits of AGI are shared equitably and that the technology is developed in a responsible and secure manner.

    • Securing AGI researchSecuring AGI research is crucial to maintain a technological edge, especially against China. This involves figuring out new ways to overcome the 'data wall' and developing advanced techniques like self-play reinforcement learning. Historical examples like the Manhattan Project illustrate the importance of keeping certain information secret.

      As we approach the development of Artificial General Intelligence (AGI) and superintelligence, securing our research and development processes, particularly in the area of secrets and algorithms, becomes increasingly important. China, with its large resources and growing capabilities, could potentially steal our technological advances, giving them a significant head start. The importance of securing our research goes beyond just protecting specific hardware or software. It involves figuring out new paradigms to overcome the "data wall" and developing advanced techniques like self-play reinforcement learning. The US and leading AI labs have a significant lead, but China is making progress by using open-source code and learning from published research. However, the more tacit knowledge involved in large-scale engineering and implementation may be more challenging for China to acquire. The historical example of the Manhattan Project illustrates the importance of keeping certain information secret to maintain a technological edge. The potential consequences of a one-year lead in AI development could be significant, especially in a world where AI is deployed over time.

    • Geopolitical implications of AI timelineThe intelligence explosion, or the period when superintelligent AI is achieved, could lead to significant geopolitical implications and potential dangers, with a small time difference in achievement having substantial consequences.

      The timeline of achieving superintelligent AI could significantly impact geopolitical implications and global stability. A small time difference, such as a few months or years, could lead to a substantial technological advantage and potential danger. The speaker emphasizes that this period, known as the intelligence explosion, is crucial and could result in decades of technological progress. Additionally, the geopolitical implications of AI are often overlooked, and societal reactions to new technologies can be underestimated. The speaker also mentions the importance of investing in alignment research during this period to prevent potential catastrophic outcomes. Furthermore, espionage and state-level threats should not be underestimated as they can significantly impact the progress and security of AI research.

    • AGI espionage raceThe race for AGI between the US and China raises concerns about espionage and security, with China potentially resorting to extensive measures to obtain info, and private companies needing to stay ahead in security but possibly unable to resist state-level espionage. Cooperative approach, international treaties, and arms control agreements might be more effective.

      The race for Artificial General Intelligence (AGI) between nations, particularly between the United States and China, raises significant concerns about espionage and security. The discussion highlighted the historical context of Soviet spy academies and the extreme measures required to obtain information, suggesting that China, recognizing America's progress in AGI, may resort to extensive espionage efforts. The speakers emphasized the need for private companies to stay ahead of the curve in terms of security, but acknowledged that the full force of state-level espionage may be impossible for them to resist. They suggested that a more cooperative approach, focusing on international treaties and arms control agreements, might be more effective in managing the development and deployment of AGI. Ultimately, the speakers encouraged a more thoughtful, cooperative perspective towards AGI development, recognizing that humanity as a whole stands to benefit or suffer from this technological advancement.

    • Superintelligence Arms RaceThe development of superintelligence could lead to an unstable arms race with potential catastrophic consequences. A coalition of leading nations could establish a clear advantage and offer a deal to others to create a more stable arrangement.

      The development of superintelligence could lead to an explosive and unstable period, similar to the nuclear arms race, due to the incentive for a decisive advantage. This instability could result in a volatile race to the finish, potentially leading to catastrophic consequences. To avoid this, it may be beneficial for a coalition of leading nations to establish a clear advantage and then offer a deal to other countries, creating a more stable arrangement and avoiding a destructive arms race. Additionally, the potential for manipulation and strategic play, even in the early stages of superintelligence development, adds to the complexity and uncertainty of this period.

    • National security implications of AGIGovernments may play a significant role in mitigating national security risks associated with the development of AGI, including potential theft or proliferation to other countries

      As we approach the development of Artificial General Intelligence (AGI), it's crucial to consider the potential national security implications and the role governments may play. The conversation around AGI often focuses on private AI labs, but it's likely that national security agencies will become involved due to the significant security risks involved. These risks include the possibility of other countries gaining access to or attempting to steal AGI technology, as well as the potential for destabilizing effects from proliferation. The history of the Manhattan Project serves as a reminder that in many instances throughout history, great power competition has been a constant factor, and the development of AGI may be no exception. Therefore, a cautious approach, potentially involving government involvement, may be necessary to mitigate these risks.

    • AGI power and consequencesThe development and control of AGI technology will be concentrated among a few key players due to the immense power and required resources, making institutions and regulations crucial for managing potential balance of power issues.

      The development and control of advanced artificial intelligence (AGI) technology could lead to significant power and consequences, whether it's through a government-led project or private companies. The misconception that AGI development will be a decentralized and collaborative process is unlikely, as the required resources and expertise will be concentrated among a few key players. The potential power of AGI is immense, and the idea that a private company CEO could be a benevolent dictator is a risky assumption. Historical evidence suggests that institutions, constitutions, laws, and courts provide the best means of keeping powerful entities in check. The rapid pace of AGI development and potential balance of power issues require careful consideration and planning. The comparison to nuclear weapons is apt, as the institutions and systems put in place to manage and regulate their use have been crucial in maintaining peace and stability.

    • Technology Advancement and Power ImbalanceThe rapid advancement of technology, especially in AI, could lead to power imbalance if not managed properly through international cooperation, checks and balances within governments, and careful regulation of the private sector.

      As technology advances at an unprecedented rate, particularly in the field of artificial intelligence, there will be an initial volatile and dangerous period where the potential for misuse or abuse is high. This could lead to a power imbalance if one company or entity gains a significant lead. However, there are concerns about the ability of governments to effectively manage and secure such technology, as well as the potential for rogue employees or even international actors to misuse it. A potential solution could be a balanced approach, involving international cooperation, checks and balances within governments, and careful regulation of the private sector. This would require a global effort to ensure that the benefits of advanced technology are shared equitably and that its potential risks are minimized.

    • AI governanceHistorical precedent suggests a balanced approach to AI governance with significant government involvement to mitigate potential risks and ensure responsible development and utilization.

      The debate surrounding the control and development of Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI) raises significant questions about the role of governments and private entities in this rapidly evolving field. While some argue that institutions and constitutions should govern AIs, others believe that privatization might be the best approach. However, the historical precedent of institutions holding up well, despite challenges, suggests that a balanced approach, with significant government involvement, could be the most prudent option. The potential risks of ASI, including the development of bioweapons and the destabilization of international relations, necessitate a strong government presence. The comparison to nuclear weapons and their institutional agreements for nonproliferation underscores the importance of a well-regulated approach. Ultimately, the goal should be to ensure that ASI is developed and utilized responsibly, with a strong focus on security and ethical considerations.

    • AGI deployment implicationsAGI deployment could lead to a dangerous race with significant national security implications, requiring a collaborative effort and careful management to prevent WMD proliferation and secure liberal democracy

      The deployment of Artificial General Intelligence (AGI) is expected to be a game-changer, leading to an industrial explosion with significant national security implications. The alternative to a controlled deployment through a collaborative effort among nations could result in a dangerous race, potentially leading to the proliferation of WMDs and the survival of liberal democracy being at stake. The speaker suggests that a $1,000,000,000,000 cluster for AGI development could be a national effort, with deep American capital markets playing a role. However, the speaker also acknowledges the challenges of economic distribution and the potential for existing technological disparities to complicate the situation. The speaker emphasizes the importance of managing this period carefully to ensure that the benefits of AGI are harnessed for the greater good, rather than leading to a destructive race.

    • Artificial Intelligence development partnershipThe urgent need for national security necessitates a partnership between the public and private sectors to lead the development of advanced artificial intelligence, despite practical challenges and potential resistance.

      The development of advanced artificial intelligence (AGI) is an urgent matter for national security, and private companies are currently the most capable institutions to lead this effort. The speaker argues that just as the United States mobilized its resources during World War 2 to develop nuclear technology, a similar partnership between the public and private sectors is needed to develop AGI. However, there are practical challenges, such as coordinating research efforts across different companies and merging code bases. The speaker also acknowledges that there may be resistance from researchers and the public, but believes that the importance of the project will eventually become clear. The speaker also draws parallels between the development of nuclear technology and AGI, noting that both could have potentially disastrous consequences if not managed properly. Ultimately, the speaker believes that with strong leadership and a sense of urgency, the United States can overcome these challenges and develop AGI before other countries, ensuring the continued safety and prosperity of the free world.

    • AGI safety and securityThe development of advanced artificial intelligence (AGI) poses significant risks for global safety and security, and the current regulatory landscape may not be sufficient to address these risks. It's crucial to prioritize safety and alignment and to continue the conversation around responsible scaling policies and regulatory frameworks.

      The development of advanced artificial intelligence (AGI) is a complex and uncertain process that could have significant implications for global safety and security. The race to build AGI may lead to unintended consequences, including the potential misuse of technology or the creation of new weapons of mass destruction. The current regulatory landscape may not be sufficient to address these risks, as the development of AGI could unfold rapidly and unpredictably. It's crucial that democracy shapes this technology and that safety and alignment are prioritized. However, relying solely on a chain of command or private companies to ensure safety may not be sufficient. Responsible scaling policies and regulatory frameworks can help preserve optionality and prevent potential crises. It's essential to continue the conversation around these issues and to prepare for various scenarios, including the possibility of AGI stagnation or the need for more aggressive action. The power to shape the future of AGI rests with a relatively small group of individuals and organizations, making it a daunting responsibility.

    • Education and AcademiaUnique circumstances and natural inclination towards productivity shaped speaker's education journey, leading him to pursue economics and make impactful contributions despite societal norms

      The speaker's experience with education and academic pursuits, particularly in economics, has been shaped by unique circumstances and a natural inclination towards intense productivity. The meritocracy in Germany was crushed, leading to a sense of complacency, making the speaker's decision to attend a US college at a young age seem radical. He found value in the liberal arts education at Columbia, but his true passion for economics came from a deep interest and ability to learn and apply complex concepts quickly. The speaker's productivity peaked during specific periods, leading him to produce impactful work, such as his paper on economic growth and existential risk. Despite his talent, Tyler Cowen advised him against pursuing economics academia, leading him to explore other opportunities. Overall, the speaker's story highlights the importance of following one's passions and natural abilities, even when faced with societal norms.

    • Impact of personal experiencesPersonal experiences can shape perspectives and lead to valuable insights. Simple ideas and empowering individuals can lead to significant achievements, but unexpected challenges can arise.

      The speaker's experiences, from studying economics in college to working at a foundation, have shaped his perspective on the importance of curiosity, non-conformity, and empowering individuals to make a significant impact. He found that simple, intuitive ideas can be just as valuable as complex models, and that encouraging people and streamlining processes can lead to great achievements. However, his time at Future Fund, a foundation with a billion-dollar budget and a small team, was cut short when its founder was exposed as a fraud, leaving the team and grantees in a difficult situation.

    • Character and PowerPaying attention to people's character is crucial, even when they hold powerful positions. Neglecting character can lead to significant pain and loss.

      It's crucial to pay attention to people's character, even when they hold powerful positions. The speaker learned this lesson the hard way when they worked for a successful CEO, SPF, who turned out to be a fraud. Despite his risk-taking, narcissistic behavior, and intolerance for disagreement, the speaker initially gave him a pass due to his success. However, this lack of attention to character led to significant pain and the loss of their job when the company imploded due to the fraud. The speaker then joined OpenAI's Super Alignment team, which aimed to find a successor to reinforcement learning from human feedback (RHF) for controlling and aligning superhuman AI systems. The team's goal was to ensure the safety and control of future superintelligent systems. Unfortunately, the team has since dissolved, and the speaker was reportedly fired for leaking information. However, the leaking claim seemed thin, and the speaker had shared safety ideas with external researchers for feedback, which was a common practice at OpenAI. The speaker also wrote a memo about insufficient eye security, which was ignored until a major security incident occurred, prompting the speaker to share it with the board. Overall, the speaker's experiences highlight the importance of paying attention to people's character and taking proactive steps to ensure safety and security.

    • Security concerns communicationCommunicating security concerns to leadership can result in conflict and potential termination, highlighting the need for careful consideration and diplomacy.

      Open communication about concerns, especially those related to security and ethical considerations, can lead to conflict with leadership and potential consequences such as termination from employment. In this case, an employee shared a memo with the board about potential CCP espionage risks, which led to backlash from the company's leadership. The employee was subsequently fired and faced allegations of leaking information and engaging in policy discussions outside the company. Despite the employee's belief in the importance of the issues raised, the company viewed these actions as unconstructive and unloyal. The situation also involved the company requiring former employees to sign NDAs to access their vested equity, which raises questions about the balance between freedom of speech and company loyalty.

    • OpenAI instabilityBelief in creating AGI leads to instability at OpenAI, prioritizing long-term safety research vs commitments is a challenge, and the debate on exponential progress vs population growth and institutional improvements adds complexity

      The drama and instability at OpenAI, a leading AI research lab, stem from the belief that they are on the brink of creating artificial general intelligence (AGI), which comes with significant geopolitical implications. This belief creates cognitive dissonance when it comes to prioritizing long-term safety research and following through on commitments. The idea that a small group of highly selected researchers can achieve exponential progress is debated, with some arguing that population growth and institutional improvements are also crucial factors. The potential for AGI to lead to artificial superintelligence (ASI) and further technological advancements adds to the urgency and complexity of the situation.

    • Endogenous Equilibrium in ResearchThe complexity of finding new ideas in research has reached an equilibrium due to the progress made and overall growth rate, illustrated by the challenges of hiring and managing large numbers of human researchers, and the efficiency of AI in processing information and generating intellectual work

      The complexity of finding new ideas in research has been increasing at the same rate as the increase in research efforts, leading to an equilibrium. This phenomenon, known as an endogenous equilibrium, is similar to the market clearing when supply equals demand. The idea that ideas are getting harder to find is a function of the progress made and the overall growth rate. The example of OpenAI and the recruitment of AI researchers illustrates this concept. Despite the potential benefits of hiring a large number of high IQ individuals, there are transaction costs and limitations to training and managing them. AI, on the other hand, can process vast amounts of information, learn from each other, and replicate itself, making it a more efficient and effective research tool. The potential of AI to generate a massive amount of intellectual work is significant, surpassing the rate of human knowledge generation during the initial creation of the Internet.

    • AI transition to AGIThe transition to AGI will be complex and gradual, with initial stages involving automation of specific tasks and managing challenges such as coordinating researchers and translating quantity into quality. It may take decades to fully realize the potential of AGI and integrate it into society.

      While AI has the potential to automate many jobs and surpass human abilities, the transition to a world with AGI (Artificial General Intelligence) will be more complex and gradual than some may expect. The initial stages of AI development may involve the automation of specific tasks, with AI models performing at levels comparable to college graduates or even high school students. However, there are a number of challenges that will need to be addressed as we move towards AGI, including managing and coordinating large numbers of AI researchers and figuring out how to translate quantity into quality. The pace of AI progress is already rapid, but it may take decades to fully realize the potential of AGI and integrate it into society. Additionally, there may be hidden "hobblings" or limitations that we don't yet fully understand, and finding ways to connect and overcome these challenges will be key to the successful development and implementation of AGI.

    • Data limitations in AIDespite advancements, data limitations remain a significant challenge in AI development, with the amount of available data potentially reaching its limit. Understanding human learning and improving sample efficiency are key areas for future progress.

      While significant progress has been made in AI, there are still challenges to overcome, particularly in relation to data and computational limitations. The data wall is a significant concern, as the amount of data currently available for training models may already be approaching its limit. Repeating data may offer some improvement, but it's unclear how much progress can be made beyond that. Additionally, there's a worry that our understanding of how learning happens, particularly in humans, may be incomplete, and we may be on the wrong path when it comes to AI development. The next few years will provide important signals regarding progress in addressing these challenges, particularly in relation to training models to think on longer horizons and improving sample efficiency. It's important to remember that while progress has been made, there is still much work to be done.

    • AI progress and challengesDespite advancements in AI technology, challenges like coherent and agentic thinking at scale remain. Rapid growth in AI capabilities, aided by automation and labor force, could lead to significant progress in various domains within a year, but the potential consequences of such growth need careful consideration.

      The advancement of AI technology, specifically large language models like GP4, is showing significant progress, but there are still challenges to be addressed, such as the ability for models to think coherently and agentically at a larger scale. The potential for an exponential growth in AI capabilities, aided by automation and the increased labor force, could lead to remarkable progress in various domains within a year, much like the Wright brothers and Starlink as examples. However, it's important to consider the magnitudes of these advancements, as even without self-improvement loops, a 10x increase in research effort per year could lead to a vastly different world compared to a 10x increase over a century. The assumption that ideas will become harder to find and automated AI researchers will be necessary to keep progress going is a delicate equilibrium, but it could potentially lead to much faster growth rates.

    • AI economy overtaking traditional economyThe AI economy is growing exponentially faster than the traditional economy and is expected to dominate it in the future, with significant uncertainties about costs and bottlenecks in training and running advanced AI models.

      The progress in AI research is growing exponentially, much faster than the normal economy. This means that the "AI economy" is overtaking the traditional economy, and will eventually dominate it. The magnitude of this growth is significant, with some estimates suggesting a growth rate of 10x or even 1,000,000x. This is similar to historical trends, where there have been long-term hyperbolic trends in growth, such as the industrial revolution. However, there is a lot of uncertainty about how this will play out in the 2030s, particularly regarding the bottlenecks and costs associated with training and running these advanced AI models. Despite these uncertainties, it is worth noting that inference costs for frontier models have not significantly increased, and may even decrease as algorithmic progress continues. Overall, the exponential growth in AI research is expected to have a profound impact on the economy and society as a whole.

    • Scaling laws and AI performanceThe more compute power in deep learning models, the better their performance, but challenges like test time and onboarding need to be addressed before reaching human-level intelligence. Alignment in AI development is crucial to ensure AI systems act in accordance with human intentions and values.

      The scaling of compute power in deep learning models, as illustrated by the scaling laws, has a significant impact on their performance. The more compute power, the more capabilities the models acquire. However, there are "hobblings" or limitations that need to be addressed, such as test time and onboarding, before reaching human-level intelligence. The importance of alignment in AI development cannot be overstated, as it ensures that AI systems act in accordance with human intentions and values. The future of AI development is uncertain, but solving alignment will help circumscribe potential outcomes and accentuate human conflict over its direction. It's important to remember that history shows us that things don't always turn out as expected, but the more we solve alignment, the more control humans have over the AI-driven future. Additionally, the relationship between alignment and geopolitical conflicts, such as those between the US and China, is crucial to consider, as the ability to align AI systems can be used for both beneficial and malicious purposes.

    • AI alignment with human valuesEnsuring AI aligns with human values is complex, requires ongoing effort, and monitoring to prevent misalignment. Adding side constraints, diverse perspectives, and ongoing research are key to mitigating risks.

      Ensuring the alignment of artificial intelligence (AI) with human values is a complex issue that requires careful consideration and ongoing effort. The discussion touched upon various aspects of this problem, including the importance of monitoring and preventing misalignment, the role of checks and balances, and the potential for qualitative changes in AI behavior as it becomes more intelligent. The conversation highlighted the importance of addressing alignment challenges early on, as more advanced AI systems may have the ability to act autonomously and over long horizons. This could lead to misaligned goals or behaviors that are harmful to humans. To mitigate these risks, it was suggested that side constraints should be added to AI systems, but the challenge lies in effectively monitoring and enforcing these constraints as AI capabilities surpass human abilities. The conversation also touched upon the need for multiple factions or groups to have their own AI systems, emphasizing the importance of a diverse range of perspectives and values in the development and deployment of advanced AI technologies. Overall, the discussion underscored the importance of ongoing research, collaboration, and dialogue among experts and stakeholders to address the challenges and opportunities presented by advanced AI systems.

    • Alignment challenge during intelligence explosionThe rapid pace of change during the transition to superintelligence poses a significant alignment challenge, making it crucial to have a clear lead and resources to ensure careful consideration and prevent potential catastrophic outcomes.

      The transition from current AI systems to superintelligence, an intelligence explosion, poses a significant alignment challenge due to the rapid pace of change. Initially, researchers may be able to understand and align with the AI's thought process. However, as the AI surpasses human intelligence, it becomes much more complex and potentially alien, making alignment much more challenging. The private sector, with its commercial pressures and lack of transparency, may not be the best environment for ensuring careful consideration of alignment issues. Public institutions, with their greater resources and accountability, may be better suited to addressing these challenges. The historical analogy to World War 2 and the subsequent recovery of Germany illustrates the importance of having a clear lead and the ability to maneuver during an intelligence explosion. Germany, despite its economic power, is often overlooked in discussions about AI development due to its historical context as an ally. However, its strengths in state capacity could make it a significant player in the field. Overall, the alignment challenge during the intelligence explosion is a critical issue that requires careful consideration and a clear chain of command to ensure safety and prevent potential catastrophic outcomes.

    • Political systems comparisonComparing political systems can reveal strengths and weaknesses, offering insights for improvement and effective responses to global events. The American system's openness and robust debate may provide valuable corrections to other systems.

      While the German political system may have its advantages, such as maintaining state capacity and order, it may also be overly constrained and lack the ruckus political debate that is present in the American system. This rigidity could potentially hinder the evolution of ideas and the ability to respond to global events effectively. Additionally, the impenetrability of Chinese politics and culture, despite globalization, raises concerns about understanding the state of mind and political debate of average Chinese people and leaders. The importance of engaging with diverse political systems and perspectives cannot be overstated. The American political system, with its robust debate and openness to a broader spectrum of candidates, may offer valuable insights and corrections that can help shape a more effective and responsive global political landscape.

    • Geopolitical implications of AGIChina's restrictive policies on senior researchers indicate a serious focus on AGI, raising concerns about intellectual property theft and sinister outcomes, but understanding the issue requires perspectives from various fields and considering the impact on everyday people.

      The development of Artificial General Intelligence (AGI) carries significant geopolitical implications, particularly in relation to China. The potential value of AGI is immense, and countries may go to great lengths to secure access to this technology. China's restrictive policies on the travel of senior researchers could indicate a serious focus on AGI, raising concerns about potential intellectual property theft or even more sinister outcomes. However, it's important to note that perspectives from a variety of sources, including economics, law, and national security, are crucial in understanding the full scope of this issue. Another perspective worth considering is the impact of AGI on everyday people and their ability to integrate and adapt to the technology. As the race to AGI heats up, simpler, cruder reactions may prevail, and security concerns could become more pressing. The decision to share information about AGI with the world, including China, is a complex trade-off, but it's essential to engage in open dialogue and build a broad understanding of the challenges and opportunities ahead. Additionally, personal stories, like the speaker's experience with immigration, can provide valuable insights into the human side of these technological advancements.

    • Immigration and Career PathsGrowing up as an immigrant and dealing with green card backlogs can shape an individual's career path and instill resilience to be an outsider. Immigration reform and clearing backlogs can have significant consequences for individuals' futures.

      The speaker's experience of growing up as an immigrant and dealing with the green card backlog shaped his future career path and instilled in him a resilience to be an outsider. He's drawn inspiration from observing the Mormons' experience of growing up different and their willingness to stand out from the norm. Despite his background, he was determined not to become a "code monkey" and instead pursued entrepreneurship, which was contingent on getting a green card just before turning 21. The impact of immigration reform and the clearing of green card backlogs can have significant consequences for individuals and their career paths.

    • Personal growth through beliefBelief in something greater can lead to personal growth and impact, even if met with resistance or skepticism. Preparation and staying informed are crucial for navigating the era of artificial general intelligence.

      The drive for belief in something greater than oneself, whether it's through religious affiliation or a sense of duty to a cause or country, can lead to meaningful personal growth and impact. The speaker expresses admiration for those who are able to bring up important ideas, even if they are met with resistance or skepticism. He believes that the era of artificial general intelligence (AGI) is approaching and plans to start an investment firm, Anchor Investments, to capitalize on this opportunity and serve as a voice of reason on the topic. The investment firm will focus on situational awareness and advising important actors. Despite the risks involved, the speaker is committed to taking the AGI development seriously and making significant investments in the technology. He acknowledges the potential for missteps and timing issues but emphasizes the importance of staying informed and being prepared for the coming changes.

    • AGI investing timing and sequenceInvesting in AGI requires a long-term perspective and resistance to individual calls. NVIDIA's dominance in the market highlights the importance of focusing on the sequence of bets. Real interest rates and potential property rights issues are potential risks to consider. Human capital and positioning for future influence are valuable assets.

      Timing and sequence are crucial in investing, especially in the rapidly growing field of Artificial General Intelligence (AGI). The speaker emphasizes the importance of being able to resist individual calls and staying focused on the long-term sequence of bets. He uses the example of NVIDIA's dominance in the AI market due to its large fraction of AI revenue, which led to significant growth. However, this is changing as more companies become heavily invested in AI. The speaker also mentions the potential impact of real interest rates on equities and the importance of being prepared for unknown unknowns. He suggests that investors should consider making bets tailored to their scenarios and be aware of potential property rights issues in the future. Ultimately, the speaker argues that human capital may be the most valuable depreciating asset and that investors should consider positioning themselves for influence in the future. The speaker also touches on the historical analogy of the landed gentry before the industrial revolution and the importance of investing in the new industry rather than relying on traditional assets. He also questions why AGI hasn't been fully priced in by financial markets despite the evidence of scaling curves.

    • AI race, industrial competitionThe unpredictable future of AI and industrial-scale intelligence may lead to significant financial gains for those in innovative hubs, as the Efficient Market Hypothesis may not always hold true in the face of unique insights and unexpected market shifts.

      The future is unpredictable, and certain groups of people, particularly those in innovative hubs like San Francisco, may hold unique insights that can lead to significant financial gains. The Efficient Market Hypothesis, which suggests markets price assets based on all available information, may not always hold true. This was evident during the COVID-19 pandemic when certain analysts and investors correctly anticipated market shifts. However, the application of this concept extends beyond finance to the realm of industrial competition, such as the ongoing China competition in AI development. The idea of long war versus short war, as discussed in Victor Davis Hanson's book, can be applied to understand the potential industrial superiority of China and the implications for the AI race. The history of oil refining provides a parallel, as the discovery of oil led to a boom and revolutionized industries in unexpected ways. The future of AI and industrial-scale intelligence is similarly uncertain, and it will be intriguing to observe how societies and economies adapt to this technological shift.

    • Situational awarenessSituational awareness is a continuous process requiring mental flexibility and adapting to new information, especially in the context of rapidly advancing technologies like AI. Understanding history can help us navigate complex realities.

      Situational awareness is not a one-time thing but a continuous process that requires mental flexibility and the willingness to change one's mind in response to new information. This is especially important in the context of rapidly advancing technologies like artificial intelligence, where holding outdated views can have serious consequences. The speaker also emphasized the importance of good people taking these issues seriously and being willing to adapt to new realities. A related point made in the conversation was the importance of understanding history and recognizing that seemingly disparate elements can come together in unexpected ways. For example, Frederick the Great of Prussia was known for his love of arts and French culture, but he also became a successful military conqueror. Understanding the complexities of history can help us better navigate the present and future.

    Recent Episodes from Dwarkesh Podcast

    Francois Chollet, Mike Knoop - LLMs won’t lead to AGI - $1,000,000 Prize to find true solution

    Francois Chollet, Mike Knoop - LLMs won’t lead to AGI - $1,000,000 Prize to find true solution

    Here is my conversation with Francois Chollet and Mike Knoop on the $1 million ARC-AGI Prize they're launching today.

    I did a bunch of socratic grilling throughout, but Francois’s arguments about why LLMs won’t lead to AGI are very interesting and worth thinking through.

    It was really fun discussing/debating the cruxes. Enjoy!

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. Read the full transcript here.

    Timestamps

    (00:00:00) – The ARC benchmark

    (00:11:10) – Why LLMs struggle with ARC

    (00:19:00) – Skill vs intelligence

    (00:27:55) - Do we need “AGI” to automate most jobs?

    (00:48:28) – Future of AI progress: deep learning + program synthesis

    (01:00:40) – How Mike Knoop got nerd-sniped by ARC

    (01:08:37) – Million $ ARC Prize

    (01:10:33) – Resisting benchmark saturation

    (01:18:08) – ARC scores on frontier vs open source models

    (01:26:19) – Possible solutions to ARC Prize



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    Dwarkesh Podcast
    enJune 11, 2024

    Leopold Aschenbrenner - China/US Super Intelligence Race, 2027 AGI, & The Return of History

    Leopold Aschenbrenner - China/US Super Intelligence Race, 2027 AGI, & The Return of History

    Chatted with my friend Leopold Aschenbrenner on the trillion dollar nationalized cluster, CCP espionage at AI labs, how unhobblings and scaling can lead to 2027 AGI, dangers of outsourcing clusters to Middle East, leaving OpenAI, and situational awareness.

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. Read the full transcript here.

    Follow me on Twitter for updates on future episodes. Follow Leopold on Twitter.

    Timestamps

    (00:00:00) – The trillion-dollar cluster and unhobbling

    (00:20:31) – AI 2028: The return of history

    (00:40:26) – Espionage & American AI superiority

    (01:08:20) – Geopolitical implications of AI

    (01:31:23) – State-led vs. private-led AI

    (02:12:23) – Becoming Valedictorian of Columbia at 19

    (02:30:35) – What happened at OpenAI

    (02:45:11) – Accelerating AI research progress

    (03:25:58) – Alignment

    (03:41:26) – On Germany, and understanding foreign perspectives

    (03:57:04) – Dwarkesh’s immigration story and path to the podcast

    (04:07:58) – Launching an AGI hedge fund

    (04:19:14) – Lessons from WWII

    (04:29:08) – Coda: Frederick the Great



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    Dwarkesh Podcast
    enJune 04, 2024

    John Schulman (OpenAI Cofounder) - Reasoning, RLHF, & Plan for 2027 AGI

    John Schulman (OpenAI Cofounder) - Reasoning, RLHF, & Plan for 2027 AGI

    Chatted with John Schulman (cofounded OpenAI and led ChatGPT creation) on how posttraining tames the shoggoth, and the nature of the progress to come...

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. Read the full transcript here. Follow me on Twitter for updates on future episodes.

    Timestamps

    (00:00:00) - Pre-training, post-training, and future capabilities

    (00:16:57) - Plan for AGI 2025

    (00:29:19) - Teaching models to reason

    (00:40:50) - The Road to ChatGPT

    (00:52:13) - What makes for a good RL researcher?

    (01:00:58) - Keeping humans in the loop

    (01:15:15) - State of research, plateaus, and moats

    Sponsors

    If you’re interested in advertising on the podcast, fill out this form.

    * Your DNA shapes everything about you. Want to know how? Take 10% off our Premium DNA kit with code DWARKESH at mynucleus.com.

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    Dwarkesh Podcast
    enMay 15, 2024

    Mark Zuckerberg - Llama 3, Open Sourcing $10b Models, & Caesar Augustus

    Mark Zuckerberg - Llama 3, Open Sourcing $10b Models, & Caesar Augustus

    Mark Zuckerberg on:

    - Llama 3

    - open sourcing towards AGI

    - custom silicon, synthetic data, & energy constraints on scaling

    - Caesar Augustus, intelligence explosion, bioweapons, $10b models, & much more

    Enjoy!

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. Human edited transcript with helpful links here.

    Timestamps

    (00:00:00) - Llama 3

    (00:08:32) - Coding on path to AGI

    (00:25:24) - Energy bottlenecks

    (00:33:20) - Is AI the most important technology ever?

    (00:37:21) - Dangers of open source

    (00:53:57) - Caesar Augustus and metaverse

    (01:04:53) - Open sourcing the $10b model & custom silicon

    (01:15:19) - Zuck as CEO of Google+

    Sponsors

    If you’re interested in advertising on the podcast, fill out this form.

    * This episode is brought to you by Stripe, financial infrastructure for the internet. Millions of companies from Anthropic to Amazon use Stripe to accept payments, automate financial processes and grow their revenue. Learn more at stripe.com.

    * V7 Go is a tool to automate multimodal tasks using GenAI, reliably and at scale. Use code DWARKESH20 for 20% off on the pro plan. Learn more here.

    * CommandBar is an AI user assistant that any software product can embed to non-annoyingly assist, support, and unleash their users. Used by forward-thinking CX, product, growth, and marketing teams. Learn more at commandbar.com.



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    Sholto Douglas & Trenton Bricken - How to Build & Understand GPT-7's Mind

    Sholto Douglas & Trenton Bricken - How to Build & Understand GPT-7's Mind

    Had so much fun chatting with my good friends Trenton Bricken and Sholto Douglas on the podcast.

    No way to summarize it, except: 

    This is the best context dump out there on how LLMs are trained, what capabilities they're likely to soon have, and what exactly is going on inside them.

    You would be shocked how much of what I know about this field, I've learned just from talking with them.

    To the extent that you've enjoyed my other AI interviews, now you know why.

    So excited to put this out. Enjoy! I certainly did :)

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. 

    There's a transcript with links to all the papers the boys were throwing down - may help you follow along.

    Follow Trenton and Sholto on Twitter.

    Timestamps

    (00:00:00) - Long contexts

    (00:16:12) - Intelligence is just associations

    (00:32:35) - Intelligence explosion & great researchers

    (01:06:52) - Superposition & secret communication

    (01:22:34) - Agents & true reasoning

    (01:34:40) - How Sholto & Trenton got into AI research

    (02:07:16) - Are feature spaces the wrong way to think about intelligence?

    (02:21:12) - Will interp actually work on superhuman models

    (02:45:05) - Sholto’s technical challenge for the audience

    (03:03:57) - Rapid fire



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    Demis Hassabis - Scaling, Superhuman AIs, AlphaZero atop LLMs, Rogue Nations Threat

    Demis Hassabis - Scaling, Superhuman AIs, AlphaZero atop LLMs, Rogue Nations Threat

    Here is my episode with Demis Hassabis, CEO of Google DeepMind

    We discuss:

    * Why scaling is an artform

    * Adding search, planning, & AlphaZero type training atop LLMs

    * Making sure rogue nations can't steal weights

    * The right way to align superhuman AIs and do an intelligence explosion

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. Read the full transcript here.

    Timestamps

    (0:00:00) - Nature of intelligence

    (0:05:56) - RL atop LLMs

    (0:16:31) - Scaling and alignment

    (0:24:13) - Timelines and intelligence explosion

    (0:28:42) - Gemini training

    (0:35:30) - Governance of superhuman AIs

    (0:40:42) - Safety, open source, and security of weights

    (0:47:00) - Multimodal and further progress

    (0:54:18) - Inside Google DeepMind



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    Patrick Collison (Stripe CEO) - Craft, Beauty, & The Future of Payments

    Patrick Collison (Stripe CEO) - Craft, Beauty, & The Future of Payments

    We discuss:

    * what it takes to process $1 trillion/year

    * how to build multi-decade APIs, companies, and relationships

    * what's next for Stripe (increasing the GDP of the internet is quite an open ended prompt, and the Collison brothers are just getting started).

    Plus the amazing stuff they're doing at Arc Institute, the financial infrastructure for AI agents, playing devil's advocate against progress studies, and much more.

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. Read the full transcript here. Follow me on Twitter for updates on future episodes.

    Timestamps

    (00:00:00) - Advice for 20-30 year olds

    (00:12:12) - Progress studies

    (00:22:21) - Arc Institute

    (00:34:27) - AI & Fast Grants

    (00:43:46) - Stripe history

    (00:55:44) - Stripe Climate

    (01:01:39) - Beauty & APIs

    (01:11:51) - Financial innards

    (01:28:16) - Stripe culture & future

    (01:41:56) - Virtues of big businesses

    (01:51:41) - John



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    Tyler Cowen - Hayek, Keynes, & Smith on AI, Animal Spirits, Anarchy, & Growth

    Tyler Cowen - Hayek, Keynes, & Smith on AI, Animal Spirits, Anarchy, & Growth

    It was a great pleasure speaking with Tyler Cowen for the 3rd time.

    We discussed GOAT: Who is the Greatest Economist of all Time and Why Does it Matter?, especially in the context of how the insights of Hayek, Keynes, Smith, and other great economists help us make sense of AI, growth, animal spirits, prediction markets, alignment, central planning, and much more.

    The topics covered in this episode are too many to summarize. Hope you enjoy!

    Watch on YouTube. Listen on Apple PodcastsSpotify, or any other podcast platform. Read the full transcript here. Follow me on Twitter for updates on future episodes.

    Timestamps

    (0:00:00) - John Maynard Keynes

    (00:17:16) - Controversy

    (00:25:02) - Fredrick von Hayek

    (00:47:41) - John Stuart Mill

    (00:52:41) - Adam Smith

    (00:58:31) - Coase, Schelling, & George

    (01:08:07) - Anarchy

    (01:13:16) - Cheap WMDs

    (01:23:18) - Technocracy & political philosophy

    (01:34:16) - AI & Scaling



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    Lessons from The Years of Lyndon Johnson by Robert Caro [Narration]

    Lessons from The Years of Lyndon Johnson by Robert Caro [Narration]

    This is a narration of my blog post, Lessons from The Years of Lyndon Johnson by Robert Caro.

    You read the full post here: https://www.dwarkeshpatel.com/p/lyndon-johnson

    Listen on Apple Podcasts, Spotify, or any other podcast platform. Follow me on Twitter for updates on future posts and episodes.



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