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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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.

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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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📺 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.

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🎧 Take us with you on Spotify

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📺 Get the clips and outtakes on Instagram --

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.

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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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NASA scientist Philip Metzger joins Thinking on Paper to explain why Moon dust and rocket exhaust create a major engineering problem for future lunar missions.

When a spacecraft lands on the Moon, its engines can accelerate dust and rocks across the surface at high speed. That material can damage nearby equipment, including solar panels, telescopes, antennas, sensors and thermal-control systems.

The problem becomes more serious as NASA, SpaceX and other organisations plan larger landers, permanent bases and more frequent missions. Every landing could threaten infrastructure already operating on the lunar surface.

In this episode, we discuss:

• Why lunar landers throw dust and debris across the Moon

• How rocket exhaust interacts with lunar soil

• Why larger spacecraft such as Starship increase the risk

• How Moon dust can damage solar panels, antennas and scientific instruments

• What this means for NASA’s Artemis programme

• Why future lunar bases may require dedicated landing pads

• How far spacecraft should land from existing equipment

• Whether lunar infrastructure needs exclusion zones

• How landing rules could affect Moon governance

• What engineers still don’t know about repeated lunar landings

Philip explains why lunar dust isn’t a minor operational inconvenience. It’s a systems-level problem that affects spacecraft design, base planning, scientific equipment and the rules governing activity on the Moon.

This conversation examines one of the least visible challenges facing lunar exploration: how to land safely without damaging the infrastructure needed to remain there.

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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.substack.com/

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