"Not Even Wrong" Podcast
Investing in fundamentally new concepts and engineering practices with large impact.
Book impressions ‘The Art of Doing Science and Engineering’ by Richard Hamming. Part 1. Vision matters. Accuracy not as important. But belief is direction to greatness. ‘If you know what you’re doing in science, you shouldn’t be doing science. If you don’t know what you’re doing in engineering, you shouldn’t be doing engineering’. Mindset matters. Match your frequency and wavelength with reality. Must be yours. History matters. You might not be able to extrapolate. But it’s best we have.
Book discussion Crux, a novel by Gabriel Tallent. Purpose of life story. ‘Catcher in the Rye’ meets ‘Into the Wild’. Social activism trickles through story. Unfortunate. Tama character unlikalbe first, then ends up likable. Pivot of character development could be more smooth. Stories are built on characters. Eventually, love is the base of all endeavor. Tama finds purpose in love and care. Dan doesn’t. Adults fail their kids. Ultimate purpose of life is to enable a better future for next generation. It’s not podiums and posters. Even inspiration doesn’t count. It’s when you do things for others that don’t nurture your narcissism that actually make you stronger. Kindness. Fathers don’t matter. Why? Climbing as a metaphor for life is good choice. Social activism trickling through the climbing world, not good.
Book impressions Crux, a novel by Gabriel Tallent. Part 2. Why go to college? What does education actually do? It’s not about getting a job nor about securing a regular, normal life. That’s precisely not what a college eduction is supposed to deliver. Learning how YOU can learn and think. It’s the first step in defining YOUR path. Developing into a real person with a unique path. Climbing is a good metaphor for life and dreams. But it’s not about chasing numbers or podiums. It’s about creating your own path. Start with a college education. Take it seriously. Go in depth and then follow path. Dan should never, ever give up college for climbing. That’s stupid.
Discussing presentation by Mac Schwager. Are foundation robotics models general AI or are they just memorizing? Mostly memorizing. But what does it mean to be general vs. memorizing? Schwager studies tokens and how they appear. General means, they appear in many different, somewhat related scenarios. Memorizing means, they only appear in specific scenarios. How to remedy? Lots of diverse data and general models. Ideally, the robot learns from its own experience. Generality is the ability to solve problems in previously unseen scenarios. Bitter Lesson.
Book impressions 'Crux', a novel by Gabriel Tallent. Novels with political undertone are redundant. Using climbing as a metaphor for life. Good idea. Step by step solutions to problems. We’re not happy about using climbing as a veneer for social activism. Athletes must not engage in political activism. Focus on performance and keep sport out of politics. Character of Tama is unlikable. Risk of stereotyping lesbians as sociopaths like Tama.
Discussing presentation by Daniela Rus about energy efficiency inference models. Liquid networks. A network of neurons each defined by a differential equation. More information per neuron. Less I/O and math per matrix. More inference per Watt. Strong models. Sequential. Good for robotics or real world AI. Drawback; context. Is this just repacked ODEs? No. Neureal nets defined by ODEs with learned coefficients. What about continuous learning?
Buchdiskussion ‘Unterleuten’ von Juli Zeh. Postmodernes Theaterstück auf der Bühne eines Romans. Wie im Theater, so muss der Leser auch hier im Spiel der übertriebenen Simulation eines Soziotops mitmachen. Don Quixote trifft Godot, trifft den Besuch der Alten Dame. 1/3 Realität vs. Illusion. Es gibt keine Wahrheit, nur Geschichten. Kein Sinn, nur spielen, Gewinnen. Entschleunigung der Gesellschaft. Emotionen passen nicht mehr. Menschen ohne Zweck und Berufung. Wo bleibt die Tugend? Wo ist die Frau und wo der Mann? 2/3 Godot. Kein Sinn. Sogar die Rossfrau hat nur Gewinnen im Kopf. Es fehlt an Humanität und Liebe. Vor-apokalyptische Gesellschaft, die im Sumpf der Postmoderne versunken ist und sich am Leichengift moralischer Überlegenheit vergriffen hat. 3/3 Besuch der alten Dame. Wenn plötzlich Geld fliesst, spielen die Dorfbewohner verrückt. Verlockung durch Reichtum verändert Gemüter und beeinflusst das Verhalten. Deutschlandbild einer fahlen Gesellschaft, die in sich selbst zerfällt. Spiegelt nicht nur Deutschland, sondern Westen.
To generate wealth you must concentrate. Invest in maximum epistemic uncertainty with large upside. Only constraint; survive. Christopher Columbus style of investing. Legacy investment theory has it all wrong. It’s not about diversification. It’s about maximizing concentration on positions where epistemic uncertainty and potential returns are high. Legacy investment managers measure uncertainty as standard deviation of stock prices. Useless measure of risk and wealth creation. Wealth is predicated on solving difficult technological problems. Such problems contain high epistemic uncertainty, that is knowledge that is not available right now but can be obtained through iteration and error correction. Engineering is another word for reducing epistemic uncertainty. Concentrate on deep tech with high epistemic uncertainty and entrepreneurs tackle such problems at scale. Constraint is; survive. Darwin. Niche. Develop knowledge to occupy new niche. Large, profitable and scales with customer adoption.
Productivity Technology usually benefits the few and leads to increased inequality. But technology as a whole benefits all. That’s why we tolerate engineering. Only about 5% of top developers are getting better with AI. The rest falls prey to mediocrity. The same dynamics played out when calculus was invented in the 18th century or software in the 20th. Technology is a divider when it comes to productivity because some people figure out how to out perform others. The gap exponentially wides. But technology in general is an equalizer. The internet, self driving electric cars, penicillin, low cost transport and most other engineering marvels benefit all. But productivity tools don’t. Society has to deal with this to stifle the rise.of Socialism driven by feelings of jealousy and envy.
Eindrücke ‘Unterleuten’, ein Roman von Juli Zeh. Teil 3. Charakter von Linda Franzen ist unerträglich. Egoistisch, obsessive Narzisstin. Rossfrauen Dasein ist bloss ein Vorwand, um ihren narzisstischen Trieb voll auszuleben. Doch sie erinnert mich an Elon Musk und andere Unternehmer, die ich mag. Wie kommt das? Der Unterschied ist, dass Musk und andere (Jeff Bezos, Larry Page, Palmer Lucky u.a) eben Unternehmer sind, deren Drang nach Schaffen zu enormen gesellschaftlichen Fortschritten führt (Elektroautos, Internet, Energie, Verteidigung). Allen gemeinsam ist, dass sie durch Technologie Kosten senken und so den Zugang für viel mehr Menschen ermöglichen. Linda’s Drang dient nur der Ablenkungen ihrer tiefgründigen Unsicherheit gegenüber dem Leben. Nutzt niemandem, nicht einmal ihr selbst.
Tesla investors waiting for Goal or Godot? Holding on to Tesla has not been rewarding in the past five years. Patience or stupidity? Today’s delivery numbers are disappointing. Why are people not buying more Teslas when there is FSD and best in class product? Not knowing why things aren’t working is unnerving. Why are we holding on to Tesla? Fully integrated robotics company. Transport as a service. Labor as a service. Cybercab is transitioning from technology risk to business risk. Solving tail end with data driven learning takes time. Scalable. Problems Tesla is solving are conducive to data driven learning. Why is Tesla storage business not growing when energy demand is accelerating? What to do now? Stick with fundamentals. For example, we’re going to CVPR this year because vision is key to robotics.
Tesla should buy Physical intelligence. Sergey Levine interview and his take on Moravec’s paradox. 1/7 Moravec paradox applies to all AI. It’s not the difficulty which matters but how conducive a job is to learning from data. 2/7 Robotics an AI problem, not sensors. For example, haptics can be solved with vision. Robots have different constraints than humans. Don’t anthropomorphize. 3/7 Neurons fire based on tip of tool, not tip of hand. 4/7 Generality is best achieved if a system improves while doing it’s job and pursuing its goal. Tesla is solving tail end of FSD through AI, not explicit interventions. Scalable. 5/7 What’s the kindest thing somebody has ever done to you? 6/7 Create systems that get better at the thing the more they do the thing. 7/7 Physical Intelligence could be for Tesla what Deep Mind is for Google.
Eindrücke ‘Unterleuten’, ein Roman von Juli Zeh. Teil 2. Zitat von Gerhard: ‘Wir leben in einer Welt, in der Ärzte das Gesundheitssystem zerstören, Akademiker das Wissen zerstören und Politiker die Freiheit vernichten.’ Obschon ich politisch mit Gerhard nicht übereinstimme, bin ich mit diesem Zitat einverstanden. Zeh zeigt wie politische Meinung verwickelt ist und die vermeintlich klaren politischen Demarkationslinien falsch sind.
Robotaxi competition is about cost, comfort and scaling. Demand for transport grows exponentially. Three levels of competitive dynamics between Tesla and others. 1/3 Short term, Due to inferior tech, Google pumps billions into Waymo in hope to suffocate Tesla. How can Tesla respond? Much lower cost, lower wait times, more comfort, network effects and scaling anywhere globally. Every company is ultimately defined by their cost structure. 2/3 Mid term. Rapid iteration across Robotaxi value chain. Automate tail end. Waymo is self driving car on digital rails. Cannot scale due to human labor and explicit code growing exponentially with tail end. Risk; Waymo fights with regulatory capture. Incumbents haven’t been able to lower price. 3/3 Tesla is launching a service which is designed from the ground up to be fully automated for scale, low cost, high comfort and reach. Customers can turn their robots into the network. Cybercab. Optimus (maintenance, logistics). Grok, network management. Digital Optimus, agentic logistics.
Energy, Defence and Transport. Invest your money and career in those areas. Pascal’s wager. Believe in God even if you don’t. It’s a better bet. Same applies to career and money. Define areas of belief and and train yourself to become passionate about them. Then focus, learn and iterate. Deliver lower cost, safer, cleaner and scalable energy, transport and/or defense. Purpose. Through history humans mostly cared about energy, transport and defense. It’s where real wealth is created. No Ponzi needed.
Eindrücke ‘Unterleuten’, ein Roman von Juli Zeh. Teil 1. Beschreibt Charaktere mit spitzer Genauigkeit ohne der Pedanterie zu verfallen. Satirisch übertrieben und unterhaltsam. Fortsetzung von Middle England - die Deutsche Version. Zeh zeigt die Wurzeln der gegenwärtigertigen Frustration in Deutschland von beiden Seiten, Links und Rechts. Fehlender Bezug zum Leben, ohne Zweck und mit viel Lärm und teurer Unterwerfung in der Stadt und gleichzeitig fehlende Relevanz auf dem Land. EU als Bürokratiekorsett mit dem Ziel, den Fortschritt zu stoppen. Die Progressiven von heute sind an Erhaltung des Bestehenden interessiert und sehen alles Neue als Gefahr. Aufschwung von Rechts, weil sich die Rechte zumindest verbal um die Leute kümmert, während die Mitte und Links in einem zwecklosen Idealismus von Europa, Ökologie und falscher Toleranz versinkt.
Diffusion models are the future of AI because most bit streams will be video. Stefano Ermon introduces diffusion for text. But that’s just a side show. Elon’s X post ‘The vast majority of AI workload will be video understanding and generation, so good chance diffusion is the biggest winner overall.' And Stefano’s response: ‘For video and world models, diffusion is simply the right tool: more parallelism and better scaling.’Diffusion finds signal by symmetry breaking. Much better for video. Robotics based on vision is driven by diffusion. Tesla FSD using diffusion for video generation in training. Diffusion also utilizes compute more efficiently thanks to parallelism. Elon’s comment: ‘ratio of compute to memory bandwidth will increase.’
Negar Mehr. Multi-agent collaboration. Robots and digital agents. What is an entity? One robot, a system of robots? Game theory. Multi agent collaboration through control theory. Or RL? Using LLM for high level semantic decision making. LLM guides step by step. Good at predicting next step. Like an operating system for multi agents. (Optimus managing Cybercab network). Collaboration is a big deal. Even human intelligence is not fully understood when it comes to collaboration. Coase theorem. Why do people work together. Collaboration? LLM, maximum likelihood method. Modeling reward functions. Drawback in robotics is LLMs lack spacial understanding.
Trump let us down. He started an unwindable war. What to do as an investor? Trump’s and Israel’s war against Iran is unwindable because there is no purpose, no clear definition of what a win means and no plan of what to do after. Like Vietnam, Iraq 2 and Soviet vs. Afghanistan. What to do as an investor? Make sure your daily agenda is aligned with your mission. In our case, we attempt to generate wealth by investing in fundamentally new concepts and engineering practices with large impact. Focus on deep tech such as robotics, energy, new concepts for AI infrastructure, agentic real world systems (such as Cybercab network). Deep tech is best achieved by fully integrated goal oriented companies optimized for iteration. Tesla. Nvidia. Space X. Anduril. Monitor leverage and cost structure of fund.
Book impression ‘Middle England’ by Jonathan Coe. Part 7. Immense antagonism of pro EU people after Brexit vote. Elites were relaxed about the debate because they thought they will win. After loss, bitter anger. Seeds sown for Covid and Wokeism. Similar developments in US after first Trump election. Urban aristocrats suddenly woke up to a world where 'real people' fight back. That’s when they chose to impose Covid and the radical censorship on us. They masked us and looked us up. Trump 2 gave the US a breather. Now he’s making a huge Iran mistake. Iran could become his Covid 2.0 with dire consequences for future elections. Europe still strangled by the Woke crowd. US cities lost to Woke crowd.
Book discussion ‘Middle England’ by Jonathan Coe. Great portrait of social and political climate in Britain prior to Brexit vote. Described through well built characters. 1/3 Modern Madame. Bovary. Decline of contemporary British aristocracy. Sophie and Benjamin are modern aristocrats. Privileged, multicultural grifters. They want advantage through convoluted culture of tolerance and acceptance whilst refusing their own. Sophie is a fruitcake. Good intentions. despicable actions. 2/3 Bifurcation of society in people with purpose and without. All pro EU characters in this book have shallow jobs, careers and lives. Devoid of purpose and love. The pro Brexit crowd has real jobs, with real purpose, but not fancy (forklifts, driving school). 3/3 Everybody is attached to an idea. People live in their heads. Idealism is ok as long as you have a real life. Otherwise it becomes a dangerous drug. What is the path forward. It’s purpose or not. It’s love or not. Deep-tech. Do something real that you understand. Avoid EU and US East Coast phantasy life devoid of purpose and wealth creation. Learn how to love your work and the people around you. Coe keeps characters raw
Book impression ‘Middle England’ by Jonathan Coe. Part 6. Sophie is the epitome of what’s wrong with urban, multicultural society. Suicidal empathy. No bad intentions, But her actions are despicable. Tolerance with everybody but her own. She excuses people who almost destroyed her and despises the ones who love her. Sophie lives in her head and acts like s fruitcake and closet racist. Coriander doesn’t just happen. You can stop this. Inaction is destructive. Coe does a great job is depicting Sophie’s character.
X is falling behind Anthropic. Is this a problem for Tesla? No, because Tesla is working on a different problem. Yes, because Woke AI must not garner resources. Tesla and X are pursuing real world AI. Problem solving in the real world with digital and physical robots. Tesla near term catalysts are energy, Semi, Robotaxi and unsupervised FSD. Longterm Terafab, energy and compute from space, digital and physical Optimus. Tesla is building a fully integrated supply chain. Important to iterate and solve problems for real customers in real world with robots. Nvidia risk is to the upside. Competitive risk weighing on stock.
Book impression ‘Middle England’ by Jonathan Coe. Part 5. Fruitcakes, Loners and closet racists. The trifecta of Woke mind virus. Fruitcakes. Idealists and utopists who think you can engineer a fair society. By doing so they create an even more unfair society. Loners, isolated hermits. Lack of feeling and empathy. Closet racists, social justice warriors who tolerate everything but Western society. They are racist, sexist and nationalist. Exhibiting suicidal empathy. Multicultural closet racists are often self depreciating. The hypocrite version of closet racists is those who want Wokeism for all but their own.
Book impression ‘Middle England’ by Jonathan Coe. Part 4. Sequence when Sophie gets harassed by social justice warriors shows in subtle way how bad Wokesim is spread in academia. Very Orwellian. It just happens and nobody is to blame. Well, no. There is a culprit. It’s Coriander and she must be reigned in. The problem is not her aggression, the problem is the passive aggressive inability of everybody else to fight back and put her in her place. Coe writes very skillfully. His character build up and social context is subtle, but clear. Trump freed us from this tyrannic the US.
Book impression ‘Middle England’ by Jonathan Coe. Part 3. The irony is that when there was less diversity of writers in English literature, when they were mostly men, they wrote about lots of progressive issues. Today we have more diversity but pretty much one option. The message which is convoluted, Woke infested. Soviet style, Orwellian. Art cannot flourish under the tyranny of political correctness and Wokeism. Art doesn’t just require freedom, it is freedom. Today’s Western art culture is not free. Just look at Hollywood and American literature. Coe is refreshingly Habermasian.
Book impression ‘Middle England’ by Jonathan Coe. Part 2. The opening of the 2012 London Olympics shows the beginnings of Woke virus. Britain is not a multicultural society. It’s a culture of tolerance at risk of being undermined by those who were shown tolerance. Ironic and sad. One of the characters writes a PhD on how painters show black ancestry in European writers. That’s something Nazis would do. Disgraceful. Quote ‘for the privileged equality is a step down’. Wrong! It was the privileged who enabled the idea of equality. All those asking for equality today either came from places that never had it or feel bad about who they are. Only wealth and industry enables opportunities for all. Complacency, riots and anger don’t.
Book impression ‘Middle England’ by Jonathan Coe. Part 1. 1/2 Political. Approachable. Beginning of end of Britain as we know. Common sense of injustice amongst British society. Always been the case, but until 2008, people thought they have chance. (Difference between Communism and Capitalism is that latter gives you a chance). Not anymore. 2/2 One party system. Political parties are for show. Politics used to be about catering to your constituency. Today it’s about catering to own privileges. London is center of privileged society, detached from rest. London, New York, more in common than London and Birmingham. Problem of Western society. Radical indecision. Todays politics in nutshell.
Book discussion ‘The God of the Woods’ a novel by Liz Moore. 1/3 Disappointing. Thriller made to thrill. Bad execution. Suspense driven to the absurd. Insults readers intelligence. Like B-TV show. 2/3 Woke, feminist message. Boring, obsolete. Rich, white men are evil, everybody else cannot do wrong even if they do. 3/3 Good character build up. But strong characters are not enough for a good story. You’d expect literature to be immune to Woke group think. It’s not.
More energy enables more power and more intelligence. Space AI is the quest for orders of magnitude more intelligence. Energy is the ability to do stuff. Dot product is the mechanics of intelligence. The more energy, the more dot products, the more intelligence. Space AI removes constraints of space and power.
Space X is trailing in the AI race. What is the race? 1/3 Performance and quality of foundation models 2/3 Data centers 3/3 Market share. Space X trails in market share, not in performance and quality of models nor in data centers. By going to space, Space X removes two constraints, space and energy. New compute architecture with abundance of space and energy. Intelligence is compute and demand is infinite. Space X is building a truth seeking AI, which will prevail over Woke AI. Also, iterating along real world AI with Cybercab and Optimus are scalable use cases. Iteration along real customers is best way to develop AI. The more usage, the better it gets.
Highest value is when intelligence solves human problems.
Tesla’s FSD is being stalled by regulators on behalf of the legacy auto industry. Movie Longitude shows how watchmaker in the 18th century solved the longitude problem for British Navy. It took decades for the technology to be adopted and the movie shows why. The establishment was stalling by continuously asking for detailed explanations and overwhelming the watchmaker with scientific pedantries. Similar situation with Tesla FSD. Regulators are stalling to gain time for their constituency, legacy OEMs, not the public. FSD would save lives and give disabled, older and younger people more mobility if the regulators were more honest about the technology.
Knowledge and Truth and the job of the future. Inspired by Jessica Moss talk about knowing what is what. Discrimination as driver of knowledge, the ability to distinguish this from that. But how do we avoid a Wittgensteinian word salad arms race? Explanation. Epistemic uncertainty and aleatoric uncertainty. Concepts converge. By reducing aleatoric uncertainty (increase knowledge domain) we increase epistemic uncertainty (there are many more problems to be solved, and solvable with more data and compute. The job of the future is to reduce epistemic uncertainty in specific domains (aerospace engineering will work on AI models to increase knowledge about how to solve problems). Foundation models must follow truth seeking explanations. Most value. Demand for intelligence is infinite.
Quantum for AI and AI for quantum. Two presentations that both tackle quantum physics but from different angles. Researcher 1: Jiaqi Leng uses quantum computation to accelerate finding optimal point with lots of local optima. Interference, superposition and hamiltonian evolution offer a faster look at the landscape and accelerate optimal solutions. His PhD thesis is about setting the foundation for quantum computation to solve highly non-convex problems with lots of local optima. Researcher 2: Liang Fu. Use a neural net and transformer architecture to guess and approximate many electron interaction. A “first-principles AI” framework is introduced in which neural networks as universal and systematically improvable variational wavefunctions (guessing Hamiltonians of fermions when interacting) for many-electron quantum states. Crucially, these neural wavefunctions are optimized entirely by energy minimization, without training data or input physics knowledge. Input Hamiltonian and optimize with physics constraints.
AI will reduce bigotry because returns of collaboration go up with higher productivity. Complex societies with advanced economies have high return of collaboration. People choose diversity because collaboration is profitable and the opportunity cost of bigotry higher (focusing on kinship, ethnicity) The big question is, what will happen if AI reduced returns on collaboration (Coasean Singularity) and everybody becomes the CEO of a one man company? AI will actually increase returns of collaboration because higher productivity drives returns of collaboration. The more productive people are (they make more with same input of time, energy), the more they benefit from collaboration.
Discussing our essay ‘CRISPR: Much Ado About Very Little’. Gene editing started the same year as AI. Today AI is a trillion dollar industry while Crispr is still not much more than a science project. Why? Because the government has turned life sciences into a trust fund. Science must serve the public and not the other way around. Two things we want to see to invest in gene editing again; 1/2 Image net style data for life sciences to capture complex relationships (similar to LLMs and language) and 2/2 Real entrepreneurs enter the field, not academics with side jobs.
Book discussion “Buckeye” by Patrick Ryan. Coming of age novel about US between 1940 and 1980. Showing critical social and political developments through stories of human characters. Powerful. 1/3 The best history books are novels. Transcend time and location with human narratives. 2/3 Role of women evolves. Some things don’t change. Responsibility, accountability, trust and love. Women post WWII went through transition from tradition to liberation. Challenging. 3/3 Betrayal and lies. Even if you are lied to, forgiveness is best way forward. Actions in the book are not as crucial. It’s the way characters feel about what’s happening. Interesting literary technique.
Humanoid supply chain waiting for Tesla to deliver form factor and intelligence. Forcing function for scalable technology requires large, credible player to commit to size. In the case of humanoids it’s new supply chain. Component supplies must wait for the right mix of components, chips, networking solution and intelligence. Intelligence dictates sensor suite and sensor suite determines intelligence. Tesla best positioned because they can iterate around use cases like factory, space AI data centers and Cybercab maintenance.
Waymo is competing with Tesla the same way Yahoo competed with Google. Driverless taxi on digital rails versus Tesla’s general intelligence. Short-term gain, longterm pain. Tesla scaling will dwarf competitors. Waymo and Uber are competing with price in markets where Tesla is present. Waymo advertising legroom and other perks. Predictable competitive reaction towards Tesla's lower cost and higher value offering. Tesla is disrupting transportation form both sides, lower cost and higher comfort. Incumbents like Waymo and Uber will suffer psychological breakdown since they can’t react. Only way to compete is to replicate supply chain.Chinese OEMs are real competitors because they are replicating Tesla supply chain. We expect 130 Billion Dollar revenue by 2030 for Tesla.
We live in a tech bubble and the money is being made elsewhere. That’s exhausting. Lots of wealth has been generated in the past nine months. And it’s not in tech. AI is driving everything but the money is being made elsewhere. Copper mining stocks have tripled in the past nine months. Memory makers, steel makers, turbine blades makers and many other basic industries are thriving while we are talking about Space AI and Cybercabs. It’s exhausting. What do we do? Stick with our mission. Use Elon’s way; stay on path and aggressively error correct.
The purpose of science is technological deterrence and survival of species. In war and in morals. We are the sorcerer and we must control the brooms. Give AI good goals so it can do science for us. Three questions. 1/3 What is the purpose of science? 2/3 How can we make sure AI follows human states purpose of science? 3/3 How do we actually implement that? What is the best way to organize society in light of this massive industrial revolution? Organic. Error correct. The purpose of science is to enable strong technological deterrence and morals. Survival of society. Protect against external and internal enemies. Moral infrastructure to handle technological power. Goal driven AI is the most promising architecture. ‘Era of experience’. Preserve fragile equilibrium of liberty and stability. Ownership of science important. Responsibility to pursue overarching goals. What is a good outcome? What is success in science? Today, science goals are not well defined. Leads to inefficiency and corruption. Good goals (technological deterrence). Bad goals (climate change). Goals must have measurable verification and accounatibclty. Open models vs. closed models. There is no such thing as independent, open model. All AI is biased. Pursue truth and error correct.
Space AI will lower cost of intelligence by 100x or more. Today AI is power constrained. Not just power, but also political. Nimby and geopolitics are making terrestrial energy production ever more expensive. Space AI will shift focus from token/Watt to token/kg. New industry will arise and lower cost of intelligence by more than 100x. Demand for intelligence is infinite and with massively lower prices it will grow exponentially. Space X is space AI company. Tesla is chip and terrestrial intelligence company. Engineering problems to be solved; Starship reusability and lower cost per kg to orbit. Lower weight chips and optimizing for compute/kg. Lower weight solar cells with higher efficiency. Low cost and low weight radiation. Optical networks for compute and communication.