Could cultivated meat replace industrial farming without asking billions of people to change what they eat? And save all the cows on the way?

Bruce Friedrich, founder of the Good Food Institute and author of Meat, explains why the future of food may depend less on changing human behaviour and more on changing how meat is produced.

For more than 12,000 years, humans have relied on animal agriculture to produce meat. Bruce argues that this system is reaching its limits.

We explore how cultivated meat is made, why it is attracting support from governments and major food companies, and why some of the biggest meat eaters are also the most open to the technology.

Along the way, we discuss the environmental cost of livestock, antibiotic resistance, food security, infrastructure, consumer psychology, regulation, and whether this technology could become as transformative as renewable energy or electric vehicles.

We also examine what happens to farmers, why culture may be harder to change than technology, and whether cultivated meat can ever reach price parity with conventional meat.

If the next agricultural revolution is already underway, it may not begin on a farm.

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

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Chapters

(00:00) Who Eats Cultivated Meat?

(02:37) Cultural Significance of Meat

(06:09) What Is Cultivated Meat?

(08:25) The Science Behind Cultivated Meat

(10:48) How Much Does Cultivated Meat Cost?

(14:46) What does cultivated meat taste like?

(17:10) Emerging Companies in the Lab Meat Industry

(19:08) Industry Support for Alternative Meats

(21:06) Government Role in Innovation

(24:40) The Future of Animal Agriculture

(28:25) Agricultural Policies for Sustainability

(31:41) What Are Fermented Meats?

(35:48) Meat And Antibiotic Resistance

(39:32) The Invisible Costs of Meat Production

(42:26) The Future of Cultivated Meat

Asteroid mining sounds insane until you speak to AstroForge CEO Matthew Gialich. Then it makes perfect sense.

Matthew’s team at AstroForge builds spacecraft to mine metallic M-type asteroids for platinum group metals, the unglamorous but essential metals inside phones, cars, chips, electronics and much more.

AstroForge is one of the few companies trying to make space mining real, targeting metal-rich asteroids that could contain platinum, palladium, iridium and other PGMs.

Why? Earth’s resources are getting harder, deeper and more expensive to reach. The good stuff is not sitting neatly on the surface. A lot of it is buried, depleted, regulated or uneconomic.

In this episode, Matthew explains why asteroid mining may now be technically and economically possible, why Planetary Resources may have been too early, how SpaceX changed the capital story for space startups, and why AstroForge’s first deep-space spacecraft failed after travelling nearly a million miles from Earth.

Please enjoy the show.

--

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

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Chapters

(00:00) Asteroid Mining Trailer

(02:51) The Economic Necessity of Asteroid Mining

(08:37) Lessons from Planetary Resources

(10:43) Risk and Innovation

(15:26) Deep Space Two

(19:05) The Quest for Asteroid Exploration

(22:20) Aliens & Life Beyond Earth

(24:17) Ownership and Ethics in Space Mining

(26:21) The Next Challenges in Asteroid Mining

(27:56) Changing Earth's Economy

(30:13) The Role of Capital

(32:32) Matt's Vision for Space Exploration

(35:06) The Drive to Explore the Universe

(36:55) NASA's Evolution

(39:17) Inside Astroforge

(42:53) The Complexity of Space Engineering

(44:25) Data Centers in Space

(47:30) The Limitations of AI in Space Engineering

Quantum computers could change medicine, material science and AI. Unfortunately, it's impossible to know how because the industry is buried under hype.

In today’s show, Dr. Bob Sutor takes us on a masterclass through the hype and conflicting headlines to the reality of quantum technology today. 

By the end of the show you’ll know what’s fact and fiction, where the industry is heading and how to protect yourself from AI slop masquerading as insight.

We also learn about:

• Why “quantum supremacy” and “quantum advantage” claims should be treated carefully

• Why quantum computing is still in its prehistory

• How engineering discipline is changing the field

• What IBM and Cleveland Clinic’s protein simulation work shows about quantum chemistry

• Why money, sovereignty and technology are driving the quantum industry

• How governments are funding quantum computing in the United States, France, the UK, Finland and elsewhere

• What China may be doing in quantum computing

• Which industries are doing serious quantum research

• Why there are many quantum hardware approaches and no clear winner yet

• Whether helium-3 supply matters for quantum computing

Bob also explains why quantum computers will be useful for specific classes of difficult problems where classical computers struggle, especially once systems become larger, more reliable and fault tolerant.

The conversation ends with practical advice on separating the quantum noise from the Thinking On Paper signal.

Please enjoy the show.

--

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

🏠 Buy us a beer on Substack

🫵 Choose your own technology adventure

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📺 Get clips and exclusive videos on Instagram

(00:00) AI Quantum Slop

(00:40) Welcome To The Show

(06:04) When Quantum Computers Finally Become Useful

(10:13) Why Governments Are Throwing Money at Quantum

(15:53) Is China Ahead in Quantum?

(18:48) Where Quantum Might Actually Matter

(27:11) Can Quantum Help Fix Climate Change?

(28:35) Why Battery Companies Care About Quantum

(30:31) Why Quantum Doesn’t Belong in the IT Department

(31:53) Who’s Doing the Real Work in Quantum?

(32:40) Why Quantum Companies Need Real Customers

(38:19) The Funding Problem Behind Quantum Progress

(45:22) Does Quantum Computing Need Helium-3?

(48:01) Will We Need a Quantum Computer Matchmaker?

(50:38) How to Spot Quantum Hype Before You Share It

Have you used Google Search recently? Exactly. Most companies, and most people, still think about Google when they think about search. They’re still spending heavily to rank there and paying for the ads around it.

But more people are asking ChatGPT, Claude and Gemini what to buy, read, use or trust.

SEO isn’t disappearing. It’s evolving into GEO.

Awad Sayeed, co-founder and CTO of Parsnipp AI, joins Thinking on Paper to explain generative engine optimisation, or GEO, and how companies can become more visible inside ChatGPT, Claude, Gemini and other AI answer engines.

Traditional SEO focuses on keywords, backlinks and rankings. GEO is more dependent on context: who the user is, what they’ve already asked, what they’re trying to achieve and how an AI system retrieves and combines information.

In this episode, we discuss:

• How generative engine optimisation differs from SEO

• Why context matters more than keywords in AI search

• How ChatGPT, Claude and Gemini use information differently

• What persona-based agents reveal about brand visibility

• How structured data helps AI systems understand websites

• Why comparison pages and clear product information matter

• What black-hat GEO could look like

• How AI-generated content could pollute the internet

• Whether brands should create separate experiences for humans and AI agents

• How advertising may develop inside AI assistants

Awad argues that GEO doesn’t replace SEO. Strong websites, useful content and clear structure still matter. But companies now need to think about whether AI systems can retrieve, interpret and recommend their information in the right context.

And as this is Thinking On Paper, we ask about the human impact, the wider change in the structure of the internet, trust, data and consumerism. 

Please enjoy the show.

--

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Chapters

(00:00) Introduction to Generative Engine Optimization

(03:36) Understanding Persona-Based Agents

(06:23) The Transition from SEO to GEO

(09:06) Context in LLMs and GEO

(11:41) Black Hat Strategies in GEO

(14:22) The Future of the Internet

(16:58) Advertising in the Age of GEO

(19:37) The Impact of GEO

(28:22) The Evolution of AI Models

(29:03) Integrating AI into Business Strategies

(29:52) Agents vs. Humans

(32:10) The Future of SEO and GEO

(34:08) Tools for Visibility and Analytics in AI

(36:00) Customer-Driven Development

(39:23) The Role of Storytelling in GEO

(42:04) Model Transparency and the Future of AI

The UK produces world-class technology and is home to exceptional tech entrepreneurs. All too often it watches them scale in America.

Rory Daniels, Head of Emerging Technology and Innovation at techUK, joins Thinking on Paper to discuss whether the United Kingdom can remain competitive as quantum computing, robotics, photonics, AI and advanced computing begin to converge.

The UK has strong research institutions, deep technical talent and globally significant companies. Its recurring problem is scale. Promising technologies are often developed in British universities and laboratories, then commercialised or funded elsewhere.

In this episode, we discuss:

• What makes the UK robotics industry different from the US and China

• Why British companies often focus on specialised robots for nuclear sites, wind turbines and industrial environments

• How autonomous driving companies such as Wayve combine AI, sensors and connectivity

• Whether robotaxis can coexist with London’s black-cab industry

• Why UK technology companies struggle to scale after the startup stage

• How access to long-term capital affects quantum, robotics and semiconductor companies

• The role of universities, technology-transfer offices and regional innovation clusters

• What is happening in Coventry, Edinburgh, Milton Keynes, Barnsley and other UK technology centres

• How digital twins and simulation are used to train robots and autonomous vehicles

• Why photonics matters for quantum computing

• How quantum, photonic, neuromorphic and biological computing could converge

• Whether AI can develop the judgement and wisdom required to solve complex technical problems

• How techUK connects companies, researchers and policymakers

• Why public trust and adoption matter as much as technical performance

Rory argues that the UK’s advantage may not lie in dominating a single technology. It may come from combining existing strengths in AI, chip design, robotics, quantum computing, photonics and connectivity.

The conversation examines what government, industry, universities and investors must do if the UK is to convert strong research into companies that can scale globally without leaving the country.

Please enjoy the show.

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

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Chapters

(00:00) The UK Technology Landscape

(03:14) Robotics: A UK Perspective

(05:54) Autonomous Vehicles in the UK

(08:39) The UK's Innovation Ecosystem

(11:05) Challenges and Opportunities for UK Tech Entrepreneurs

(13:27) Regional Innovation and Government Initiatives

(16:33) The Role of Universities in Tech Development

(19:15) Barnsley: A Blueprint for Tech Towns

(21:53) Government Initiatives in Robotics

(24:20) Digital Twins and the Future of Robotics

(27:12) Quantum Computing and Photonics in the UK

(29:24) The Role of Education in Emerging Technologies

(30:55) AI and Human Wisdom: A Complex Relationship

(38:02) Neuromorphic Computing: The Future of AI

(38:23) Convergence of Technologies: Opportunities for the UK

(42:42) The Human Element in Technology Adoption

The Vij brothers join Thinking on Paper to discuss Neo, an autonomous machine learning engineer designed to automate parts of the AI development process.

As demand for AI systems grows, companies and governments are competing for a limited pool of experienced machine learning engineers. The challenge isn’t only access to data or computing power. Many organisations also lack the technical expertise required to build, test and deploy effective models.

Neo uses a multi-agent system to perform tasks normally handled by machine learning engineers, including analysing datasets, selecting modelling approaches, running experiments and evaluating results. The aim is to automate repetitive technical work while allowing human engineers to concentrate on higher-level decisions and more creative problems.

In this episode, we discuss:

• What an autonomous machine learning engineer is

• How Neo’s multi-agent AI system works

• Why skilled machine learning engineers are in such high demand

• Which parts of AI development can be automated

• How autonomous agents compare with traditional machine learning workflows

• Why Kaggle Grandmasters are considered leading practitioners in applied machine learning

• Whether AI agents can match expert human performance

• How automation could affect machine learning jobs and salaries

• The evolution of GPUs from graphics hardware to AI infrastructure

• What the Vij brothers learned from working at CERN

• How autonomous AI systems could change business, creativity and technical work

  
  

Neo is intended to expand access to machine learning expertise rather than simply generate code. Its development raises a wider question: what happens when AI systems can perform the specialised work required to build other AI systems?

This conversation examines the technical capabilities of autonomous machine learning agents, the shortage of experienced AI talent and how automation could reshape the role of engineers

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Timestamps

(00:00) Why Are There So Few Machine Learning Engineers?(01:54) Meet Gaurav Vij and Saurabh Vij(02:57) Lessons Learned from Working at CERN(04:45) How to Explain The Importance Of A.I. to Your Parents(07:24) The World’s First Autonomous Machine Learning Engineer: What AI Problem Does NEO Solve?(08:17) AI Competitions and Kaggle Grandmasters(11:06) How Many A.I./ML Engineers Do We Need?(17:30) Fixing The A.I. Hallucination Problem(18:09) Hot Buttons: 5 AI Questions In 30 Seconds(18:46) Hollywood: Doomed by A.I, or Reborn?(20:26) AI News: Nvidia Digits Explained(21:51) Moore's Law And Could AI Models Be Motivated by Rewards?(25:42) AI And Quantum Computing(29:45) The Thinking on Paper Carry-Over Question(30:16) After Hours: Backstage Extra

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Check out NEO: https://heyneo.so/Learn more about the show: www.thinkingonpaper.xyzFollow Thinking On Paper On Instagram: https://www.instagram.com/thinkingonpaperpodcast/

We read NASA’s Moon Base User’s Guide and ask what it would take to establish a sustained human presence on the Moon.

A permanent lunar base requires far more than rockets, landers and astronauts. NASA and its partners would need to build an integrated infrastructure system covering power generation, communications, navigation, habitats, transportation, logistics, robotics and resource extraction.

In this episode, we discuss:

• How NASA plans to build a permanent Moon base

• Why reliable power is essential for long-term lunar operations

• Whether nuclear power will be required on the Moon

• How astronauts, vehicles and robots would communicate and navigate

• What lunar habitats need to protect crews from radiation and extreme temperatures

• How autonomous robots could prepare sites and maintain infrastructure

• Why lunar dust creates serious engineering problems

• How equipment from different companies and countries could work together

• Whether water, oxygen and construction materials can be extracted from lunar resources

• What infrastructure must exist before humans can live and work on the Moon continuously

  
  

The discussion also examines the gap between NASA’s long-term ambitions and the systems currently available. Many of the technologies exist individually, but they haven’t yet been combined into a reliable, scalable lunar operating environment.

This episode asks whether a permanent Moon base is a realistic extension of human spaceflight or a programme whose infrastructure requirements remain badly underestimated.

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Chapters

00:00 Executive Summary and Vision

01:17 Phased Approach to Moon Base Development

07:21 Challenges of Lunar Environment

09:06 Interoperability and Coordination in Space

15:13 Economic Incentives and Future of Space Development

17:03 Identifying Gaps in Space Technology

20:23 Functional Gaps and Their Implications

24:01 Dust Challenges and Solutions

29:10 The Moon as a Launchpad for Mars

31:08 Human Factors in Lunar Missions

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

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Sanjay Vijendran of TerraSpark joins Thinking on Paper to explain how space-based solar power could become a practical source of clean energy.

TerraSpark is developing wireless power-transmission systems that could eventually collect solar energy in orbit and beam it to receivers on Earth. The company plans to demonstrate the concept by powering a live music event in Portugal and by testing radio-frequency power transfer aboard Dcube’s Arrakis mission.

In this episode, we discuss:

• How space-based solar power works

• How energy can be transmitted wirelessly

• TerraSpark’s plan to power a concert in Portugal

• What its in-orbit power-beaming experiment will test

• The differences between radio-frequency and laser power transmission

• How near-infrared power beaming works

• How much energy is lost during wireless transmission

• Whether orbital data centres could use the same infrastructure

• How space-based solar could improve energy security

• Why spectrum regulation and interference testing matter

• What investors and regulators need to see before the technology can scale

  
  

Sanjay explains the engineering, regulatory and commercial challenges behind power beaming, including transmission efficiency, safety, spectrum allocation and the cost of placing energy infrastructure in orbit.

This conversation examines whether space-based solar power can move beyond demonstration projects and become a credible alternative to terrestrial energy generation and fossil fuels.

--

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

🎧Be With Us On YouTube

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📺 Get the clips and outtakes on Instagram

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Chapters

(00:00) Introduction to Space-Based Solar Power

(01:37) Market Trends and Projections

(03:52) Energy Crisis and Global Dependencies

(06:26) The Threat to Power Structures

(07:39) Innovative Demonstrations of Wireless Power

(10:31) Future Plans and Space Missions

(20:41) Scaling Power Transmission from Space

(22:35) Technologies for Space-Based Solar Power

(31:22) Governance and Regulation of Space-Based Solar Power

(49:57) The Future of Space-Based Solar Power

Jennifer Dunn, professor of chemical engineering at Northwestern University, joins Thinking on Paper to explain how lithium and copper mining affect water, ecosystems, local communities and the wider energy transition.

Lithium and copper are essential to electric vehicles, grid storage, renewable energy, drones and data centres. But the environmental consequences of extracting these minerals vary sharply depending on the mine, location, technology and supply chain.

Life cycle assessment offers a way to compare those impacts across different forms of production, from lithium brines and hard-rock mining to copper extraction, refining and recycling.

In this episode, we discuss:

• The environmental impact of lithium mining

• How lithium brine mining compares with hard-rock lithium mining

• Why copper demand is rising

• How mining affects water use and local water stress

• The risks of pollution, biodiversity loss and mining waste

• How life cycle assessment compares mines and supply chains

• Why local conditions matter more than global averages

• The role of mine permitting in the energy transition

• Whether recycling can reduce demand for new mining

• How battery supply chains shift environmental costs between regions

• What responsible critical-mineral production should look like

Jennifer explains why no single measure can capture the full impact of a mine. Carbon emissions matter, but so do water availability, land use, waste, local ecology and the distribution of costs and benefits.

This conversation examines whether clean energy can scale without transferring environmental harm from fossil-fuel systems to the communities that supply lithium, copper and other critical minerals.

--

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

🎧 Take us with you on Spotify

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Chapters

(00:00) Disruptors & Curious Minds

(02:10) The Demand for Copper and Lithium

(02:57) Environmental Impact of Mining

(05:59) Water Consumption and Mining Methods

(08:30) Community Concerns and Local Impact

(11:29) Recycling and Wastewater Mining

(14:04) Life Cycle Assessments in Mining

(27:06) Understanding Emissions in Mining

(29:45) Life Cycle Assessment: A Comparative Approach

(34:05) Stakeholder Perspectives on Mining Impacts

(37:42) Technology and Transparency in Mining

(42:42) Consumer Awareness and Ethical Sourcing

(48:55) Challenges in Quantifying Social Impacts

Anders Sandberg examines whether artificial general intelligence could manage the global economy more effectively than human institutions.

A sufficiently capable AI system might coordinate markets, allocate resources, interpret legal rules and respond to complex global problems faster than governments or companies. Greater efficiency, however, wouldn’t necessarily mean greater freedom.

In this short excerpt from a longer Thinking on Paper conversation, Anders discusses:

• Whether AGI could manage the global economy

• How superintelligence might improve global coordination

• Why markets and legal systems are difficult to optimise

• Whether AI could make better decisions than human institutions

• How highly efficient systems could concentrate power

• The challenge of keeping advanced AI under human control

• How evolutionary pressures could shape competing software systems

• Whether humans could become wealthier while losing political agency

• What role people would retain in an AI-managed economy

The central question isn’t simply whether AGI could run economic systems better. It’s whether humans would still control the goals, rules and trade-offs behind those systems.

This is a short from a much longer conversation with Anders Sandberg about superintelligence, governance and the future of human decision-making.

--

Thinking on Paper is a technology podcast about AI, quantum, space and their impacts on society, business and culture. It's very good.

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