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Jacque Fresco: Apply the Methods of Science to the Social System!

I have to confess something about this interview.

I really liked Jacque Fresco. Not as a thinker I was supposed to admire, but as a person: the humor, the humility, the scientific curiosity still burning at 97.

That made the disagreements harder, not easier.

Fresco spent almost a century arguing one idea. We apply the methods of #science to engineering, to medicine, to flight. Then we run our economies and our politics on opinion, tradition, and the preferences of the financial elite.

He thought we had it exactly inverted. Rigor for the machines, guesswork for the humans.

“Technology was never the hard part. The harder question is what kind of society we want it to serve.”

John Nash (1928−2015)

John Nash was born on June 13, 1928, in Bluefield, West Virginia, a former coal town nestled deep in the Appalachian Mountains. As a young boy, Nash was solitary, bookish, and introverted. His father, John Sr., was a quiet engineer with an incisive mind. His mother, Virginia, also intelligent, was a former teacher who had large dreams for her son, pushing him to read at four, learn Latin, and skip a grade at school.

The first hint of John Nash’s math talent came in fourth grade, when a teacher told Virginia that the boy couldn’t do the math. Virginia laughed, well aware that her son was going down his own path to solve the simple problems. In high school, John solved his teachers’ clunky proofs in just a few elegant steps. He was one of ten nationally awarded winners of the George Westinghose Award, which provided him with a full scholarship to the Carnegie Institute of Technology. He hopped from engineering to chemistry before discovering his passion: mathematics.

He was accepted into Princeton University, which at the time was to mathematicians what Detroit was, and still is, to cars. Nash first wowed his peers with an elegantly playable board game, which his peers dubbed “Nash,” but later reached the market as Hex. He then absorbed himself in one of the sexiest math fields of the day, game theory, which described strategies in competition, whether in card games or business. His deceptively simple doctoral thesis would later re-orient the field of economics, although no one, not even Nash, predicted its potential.

Anthropic CEO Dario Amodei Talks Scaling Laws, AI Arms Races, and Radical Abundance

This video features a conversation with Dario Amadei, CEO of Anthropic, discussing the intersection of AI and economics. Viewers will gain insights into how technological innovation impacts business processes and models, the future landscape of AI companies, and the potential societal ramifications of advancements in AI technology. The main theme emphasizes the evolving dynamics between innovation and established business strategies in the AI sector, as well as the importance of understanding how these changes affect both markets and society.

⚠️ The X-Ray We Keep Refusing to Read

The fractures aren’t in our biology. They’re in our agreements, our economic systems, and our willingness to extend the definition of “us” to include the health minister in a lower-middle-income country holding a terrifying lab result and staring at a phone they are afraid to pick up.


A world on the edge global pandemic preparedness

A world on the edge – Priorities for a pandemic-resilient world, 2026 GPMB report

GHS Index: Homepage

Ex-OpenAI Scientist WARNS: You Have No Idea What’s Coming In 5 Years

Ilya Sutskever, co-founder of OpenAI and founder of Safe Superintelligence, says the scaling era from 2020 to 2025 is over, that pre-training will run out of data, and that the industry is back to pure research with more companies than ideas. He argues that AGI is the wrong target what is actually coming is a learning algorithm that can take any job, learn it on the fly, and merge that knowledge across millions of simultaneous instances in a way humans cannot, producing rapid economic growth that regulation is unlikely to stop.

He predicts that once AI becomes visibly powerful, frontier companies will become paranoid overnight and governments will scramble, and says the only thing worth building is an AI aligned to sentient life broadly — not human life alone — because the AI itself will be sentient and will vastly outnumber humans within 5 to 20 years.

📚 Sources cited in this video:

Safe Superintelligence Inc. – Company Overview https://ssi.inc.

OpenAI, Founding Charter and Mission https://openai.com/charter.

Ilya Sutskever, Google Scholar – Research Publications https://scholar.google.com/citations?

⚠️ DISCLAIMER: This channel provides AI commentary and analysis for educational and informational purposes only. Views expressed by guests are their own and do not represent the positions of any company or institution. We encourage viewers to consult multiple sources and form their own conclusions. #ai #agi #artificialintelligence.

Peter Joseph: We Are All Subjected To The Same Natural Law System

13 years ago, I sat down with Peter Joseph, musician, filmmaker, and founder of the Zeitgeist Movement.

His argument was simple, and uncomfortable: the system we live under (debt-based money, work-for-survival economics, infinite growth on a finite planet) isn’t broken. It’s working exactly as designed. And it’s running out of runway.

In 2013, this sounded radical. In 2026, it sounds like a weather report.

We covered a lot of ground in 75 minutes: the Resource-Based Economy, the role of Artificial Intelligence in managing scarcity, the schism between Zeitgeist and the Venus Project, sustainability, central planning, and the technological singularity itself.

You don’t have to agree with Peter to take the conversation seriously. I don’t agree with all of it. But the questions he was asking back then are the questions we’re being forced to ask now, except we’re asking them in an era when AI systems can actually do things he could only theorize about.

The technology has caught up with the critique. The philosophy hasn’t caught up with the technology.

AI-Based Cancer Models in Oncology: From Diagnosis to ADC Drug Prediction

Introduction Artificial intelligence (AI) has been influencing the way oncology has been practiced. Major issues constituting a bottleneck are the lack of data for training purposes, confidentiality preventing development, or the absence of transparency in clarifying how models operate to generate decisions. Novel Models With explainable AI, trust and utilization barriers among clinicians, researchers, and patients can be removed. With the implementation of federated learning, multiple institutions could contribute to crucial dataset’s learning information. Precise diagnosis and prescription of the right drug are essential in preventing unnecessary life losses, and economic burden to the underling system.

The Growing Cybersecurity Risks To The Supply Chain In The AI Era

#cybersecurity #suppychains #ai #tech


Supply chains are a primary target for cybercriminals and provide the foundation of global commerce in the hyper-connected digital ecosystem of today. Artificial intelligence (AI) simultaneously exacerbates vulnerabilities as it revolutionizes operations through predictive analytics, automation, and real-time visibility. Sophisticated threat actors, ransomware groups, and nation-state actors employ AI to exploit the vulnerable links in intricate, multi-tiered supply networks.

Artificial intelligence can create dual-use dynamics. It promotes efficiency by facilitating real-time data transfers and hyper-connected operations, while simultaneously significantly expanding the attack surface. Compromises of a single vendor or update have been shown to have a cascading effect on economies, governments, and critical infrastructure through supply chain attacks.

In The AI Era, Supply Chains Are Prime Targets.

The complexity of supply chains is inherent, as they encompass continents, jurisdictions, and a multitude of third-party vendors, contractors, and software components. Each link—whether it be legacy systems, unvetted code, IoT devices, or 5G-enabled connections—provides potential entry points. AI exacerbates these risks by allowing attackers to automate reconnaissance, create polymorphic malware that evades detection, create personalized phishing campaigns, and identify vulnerabilities quicker than defenders can apply patches.

Commercial Space Economy: Space Stations, Space Data Centers, and NASA

Matthew Weinzierl and Brendan Rosseau, authors of Space to Grow, explain the commercial space economy and the role of NASA, Artemis, commercial space stations, space-based data centers, Starlink, GPS, China’s space program, national security, and space governance.

The conversation covers how governments, private companies, and investors build, fund, regulate, and compete in space, from microgravity research and launch markets to lunar exploration, space resources, and the economics of commercial space.

We also try and re-write the Space Treaty and look at the politics of the space race.

Please enjoy the show.

Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping the future.

🏠 Buy us a beer on Substack: https://thinkingonpaperpodcast.substa… Take us with you on Spotify: https://open.spotify.com/show/00volKq… 🎧 Remember steve jobs on APPLE: https://podcasts.apple.com/us/podcast… 📺 Get the clips and outtakes on Instagram / thinkingonpaperpodcast — Links & Resources Matthew: https://www.hbs.edu/faculty/Pages/pro… Brendan: linkedin.com/in/brendan-rosseau Buy Space To Grow: https://www.hbs.edu/faculty/Pages/ite… — Chapters 00:00 Setting The Scene 03:35 Microgravity 07:43 Economic Incentives 12:14 Political Cycles 17:09 International Collaboration 18:45 National Security in Space 21:36 Space Exploration 24:27 A Day Without Space 28:49 Space Investment 30:37 Space-Based Data Centers 33:40 Space Resources 38:26 Governance in Space 40:55 A New Space Treaty.

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