NEXT with John Koetsier

What changes when robots deliver everything?

Starship Technologies has already completed 9 million autonomous deliveries, crossed roads over 200 million times, and operates thousands of sidewalk delivery robots across Europe and the U.S. Now they’re scaling into American cities ... and they say they’re ready to change your world

In this episode of TechFirst, I speak with Ahti Heinla, co-founder and CEO of Starship and co-founder of Skype, about:

- How Starship’s robots navigate without GPS

- What makes sidewalk delivery better than drones

- Solving the last-mile problem in snow, darkness, and dense cities

- How Starship is already profitable and fully autonomous

- What it all means for the future of commerce and city life

Heinla says:

“Ten years ago we had a prototype. Now we have a commercial product that is doing millions of deliveries.”

Watch to learn why the future of delivery might roll ... as well as fly.

🔗 Learn more: https://www.starship.xyz

🎧 Subscribe to TechFirst: https://www.youtube.com/@johnkoetsier

00:00 - Intro: What changes when robots deliver everything?

01:37 - Meet Starship: 9 million robot deliveries and counting

02:45 - Why it took 10 years to go from prototype to product

05:03 - When robot delivery becomes normal (and where it already is)

08:30 - How Starship robots handle cities, traffic, and construction

11:20 - Snow, darkness, and all-weather autonomy

13:19 - Reliability, unit economics, and competing with human couriers

16:23 - Inside the tech: sensors, AI, and why GPS isn’t enough

18:03 - Real-time mapping, climbing curbs, and reaching your door

19:54 - How Starship scales without local depots or chargers

22:04 - How city life and commerce change with robot delivery

25:53 - Do robots increase customer orders? (Short answer: yes)

27:05 - Hot food, Grubhub integration, and thermal insulation

28:26 - Will Starship use drones in the future?

29:38 - What U.S. cities are next for robot delivery?

Imagine a quantum computer with a million physical qubits in a space smaller than a sticky note.

That’s exactly what Quantum Art is building. In this TechFirst episode, I chat with CEO Tal David, who shares his team’s vision to deliver quantum systems with:

• 100x more parallel operations

• 100x more gates per second

• A footprint up to 50x smaller than competitors

We also dive into the four key tech breakthroughs behind this roadmap to scale Quantum Art's computer:

1. Multi-qubit gates capable of 1,000 2-qubit operations in a single step

2. Optical segmentation using laser-defined tweezers

3. Dynamic reconfiguration of ion cores at microsecond speed

4. Modular, ultra-dense 2D architectures scaling to 1M+ qubits

We also cover:

- How Quantum Art plans to reach fault tolerance by 2033

- Early commercial viability with 1,000 physical qubits by 2027

- Why not moving qubits might be the biggest innovation of all

- The quantum computing future of healthcare, logistics, aerospace, and energy

🎧 Chapters

00:00 – Intro: 1M qubits in 50mm²

01:45 – Vision: impact in business, humanity, and national tech

03:07 – Multi-qubit gates (1,000 ops in one step)

05:00 – Optical segmentation with tweezers

06:30 – Rapid reconfiguration: no shuttling, no delay

08:40 – Modular 2D architecture & ultra-density

10:30 – Physical vs logical qubits

13:00 – Quantum advantage by 2027

16:00 – Addressing the quantum computing skeptics

17:30 – Real-world use cases: aerospace, automotive, energy

19:00 – Why it’s called Quantum Art

👉 Subscribe for more deep tech interviews on quantum, robotics, AI, and the future of computing.

Are humanoid robots distracting us from the real unlock in robotics ... hands?

In this TechFirst episode, host John Koetsier digs into the hardest (and most valuable) problem in robotics: dexterous manipulation.

Guest Mike Obolonsky, Partner at Cortical Ventures, argues that about $50 trillion of global economic activity flows through “hands work,” yet manipulation startups have raised only a fraction of what locomotion and autonomy companies have.

We break down why hands are so hard (actuators, tactile sensing, proprioception, control, data) and what gets unlocked when we finally crack them.

What we'll talk through ...

• Why “navigation ≠ manipulation” and why most real-world jobs need hands

• The funding mismatch: billions to autonomy & humanoids vs. comparatively little to hands

• The tech stack for dexterity: actuators, tactile sensors (pressure, vibration, shear), feedback, and AI

• Grasping vs. manipulation: picking, placing, using tools (e.g., dishwashers to scalpels)

• Reliability in the wild: interventions/hour, wet/greasy plates, occlusions, bimanual dexterity

• Practical paths: task-specific grippers, modular end-effectors, and “good enough” today vs. general purpose tomorrow

• The moonshot: what 70–90% human-level hands could do for productivity on Earth ... and off-planet

Chapters

00:00 Intro—are we underinvesting in robotic hands?

01:10 Why hands matter more than legs (economics of manipulation)

04:30 Funding realities: autonomy & humanoids vs. hands

08:40 Locomotion progress vs. manipulation bottlenecks

12:10 Teleop now, autonomy later—how data gets gathered

14:20 What’s missing: actuators, tactile sensing, proprioception

17:10 Perception limits in the real world (wet dishes, occlusions)

22:00 General-purpose dexterity vs. task-specific ROI

26:00 Startup landscape & reliability (interventions/hour)

29:00 Modular end-effectors and upgrade paths

30:10 The moonshot: productivity explosion when hands are solved

Who should watch

Robotics founders, VCs, AI researchers, operators in warehousing & manufacturing, and anyone tracking humanoids beyond the hype.

If you enjoyed this

Subscribe for more deep-tech conversations, drop a comment with your take on the “hands vs. legs” debate, and share with someone building robots.

Keywords

robotic hands, dexterous manipulation, humanoid robots, tactile sensing, actuators, proprioception, warehouse automation, AI robotics, Cortical Ventures, TechFirst, John Koetsier, Mike Obolonsky

#Robotics #AI #Humanoids #RobotHands #Manipulation #Automation #TechFirst

Are humanoid robots the future… or a $100B mistake?

Over 100 companies—from Meta to Amazon—are betting big on humanoids. But are we chasing a sci-fi dream that’s not practical or profitable?

In this TechFirst episode, I chat with Bren Pierce, robotics OG and CEO of Kinisi Robots. We cover:

- Why legs might be overhyped

- How LLMs are transforming robots into agents

- The real cost (and complexity) of robotic hands

- Why warehouse robots work best with wheels

- The geopolitical robot arms race between China, the US, and Europe

- Hot takes, historical context, and a glimpse into the next 10 years of AI + robotics.

Timestamps:

0:00 – Are humanoids a dumb idea?

1:30 – Why legs might not matter (yet)

5:00 – LLMs as the real unlock

12:00 – The hand is 50% of the challenge

17:00 – Speed limits = compute limits

23:00 – Robot geopolitics & supply chains

30:00 – What the next 5 years looks like

Subscribe for more on AI, robotics, and tech megatrends.

The future could be much healthier for both farmers and everyone who eats, thanks to farm robots that kill weeds with lasers. In this episode of TechFirst, we chat with Paul Mikesell, CEO of Carbon Robotics, to discuss groundbreaking advancements in agricultural technology.

Paul shares updates since our last conversation in 2021, including the launch of LaserWeeder G2 and Carbon's autonomous tractor technology: AutoTractor.

LaserWeeder G2 quick facts:

- Modular design: Swappable laser “modules” that adapt to different row sizes (80-inch, 40-inch, etc.)

- Laser hardware: Each module has 2 lasers; a standard 20-foot machine = 12 modules = 24 lasers

- Laser precision: Targets the plant’s meristem (≈3mm on small weeds) with pinpoint accuracy

- Weed kill speed: 20–150 milliseconds per weed (including detection + laser fire)

- Throughput: 8,000–10,000 weeds per minute (Gen 2, up from ~5,000/min on Gen 1)

- Coverage rate: 3–4 acres per hour on the 20-foot G2 model

- ROI timeline: Farmers typically achieve payback in under 3 years

- Yield impact: Up to 50% higher yields in some conventional crops due to eliminating herbicide damage

- Price: Standard 20-foot LaserWeeder G2 = $1.4M, larger models scale from there

- Global usage: Units in the U.S. (Midwest corn & soy, Idaho & Arizona veggies) and Europe (Spain, Italy tunnel farming)

We chat about how these innovations are transforming weed control and farm management with AI, computer vision, and autonomous systems, the precision and efficiency of laser weeding, practical challenges addressed by autonomous tractors, and the significant ROI and yield improvements for farmers.

This is a must-watch for anyone interested in the future of farming and sustainable agriculture.

00:00 Introduction to TechFirst and Carbon Robotics

01:10 The Science Behind Laser Weeding

05:46 Introducing Laser Weeder 2.0

06:39 Modular System and New Laser Technology

09:26 Manufacturing and Cost Efficiency

11:47 ROI and Benefits for Farmers

13:24 Laser Weeder Specifications

14:08 Performance and Efficiency

14:49 Introduction to AutoTractor

17:23 Challenges in Autonomous Farming

18:23 Remote Intervention and Starlink Integration

23:23 Future of Farming Technology

24:50 Health and Environmental Benefits

25:18 Conclusion and Farewell

Can robots reduce herbicide and fertilizer use on farms by up to 90%?

Probably yes.

In this episode of TechFirst we chat with Verdant Robotics' CEO Gabe Sibley about SharpShooter, the company's state-of-the-art farm tech that precisely targets herbicide and fertilizer application, massively reducing chemical use.

That's huge for the environment.

It's also huge for farmer's pocketbooks ... because herbicide and fertilizer are increasingly expensive.

We dive into:

- How Sharpshooter targets plants with pinpoint accuracy — 240 shots per second

- Why this approach can save farmers millions in input costs

- The environmental benefits for soil, water, and food

- How AI and edge computing make split-second farm decisions possible

- The future of robotics in agriculture

If you’re interested in agtech, AI, or sustainable farming, this one’s for you.

00:00 Introduction to Robotic Farming

00:28 Interview with Gabe Sibley, CEO of Verdant Robotics

00:50 How Sharpshooter Technology Works

02:40 Economic and Environmental Benefits

04:59 Technical Specifications and Capabilities

11:11 Future of Agricultural Automation

11:54 Personal Insights and Motivation

16:39 Conclusion and Final Thoughts

Will your next browser be AI-enabled? AI-first? Perhaps even an AI agent?

In this episode of TechFirst, John Koetsier sits down with Henrik Lexow, Senior Product Leader at Opera, to explore Opera Neon, a big step toward agentic browsers that think, act, and create alongside you.

(And buy stuff you want, simply hard problems, and do some of your work for you.)

Opera’s new browser integrates real AI agents capable of executing multi-step tasks, interacting with web apps, summarizing content, and even building playable games or interactive tools, all inside your browser.

We chat about

• What an agentic browser is and why it matters

• How AI agents like Neon Do and Neon Make automate complex workflows

• Opera’s vision for personal, on-device, privacy-aligned AI

• Live demos of shopping, summarizing, and game creation using AI

• Why your browser might replace your operating system

🎮 Watch Henrik demo the Neon agent building a Snake game from scratch

🛍️ See AI navigate Amazon, add items to cart, and act independently

🧠 Learn why context is king and how this changes everything about search, tabs, and multitasking

00:00 Introduction: Should Your Browser Be an AI Agent?

00:52 The Evolution of AI in Browsers

04:53 Introducing Opera's Agentic Browser

11:51 Neon: The Future of Browsing

20:26 Exploring the Cart Functionality

20:53 Future of AI in Shopping

22:39 Trust and Privacy in AI

25:05 Neon Make: Generative AI Capabilities

26:05 Creating a Snake Game with Neon

28:33 Analyzing Car Insurance Policies

31:58 Sharing and Publishing with Neon

35:53 Conclusion and Future Prospects

Can nuclear waste solve the energy crisis caused by AI data centers? Maybe. And maybe much more, including providing rare elements we need like rhodium, palladium, ruthenium, krypto-85, Americium-241, and more.

Amazingly:

- 96% of nuclear fuel’s energy is left after it's "used"

- Recycling can reduce 10,000-year waste storage needs to just 300 years

- Curio’s new process avoids toxic nitric acid and extracts valuable isotopes

- 1 recycling plant could meet a third of America’s nuclear fuel needs

- Nuclear recycling could enable AI, space travel, and medical breakthroughs

In this episode of TechFirst, host John Koetsier talks with Ed McGinnis, CEO of Curio and former Acting Assistant Secretary for Nuclear Energy at the U.S. Department of Energy. McGinnis is on a mission to revolutionize how we think about nuclear waste, turning it into a powerful resource for energy, rare isotopes, and even precious metals like rhodium.

Watch now and subscribe for more deep tech insights.

Neura Robotics officially launched shed 4NE-1 this week. It's the leading European humanoid robot and it's the most powerful humanoid robot in existence right, as far as I'm aware, able to life 100kg or 220 pounds.

Neura also released a plan to build 5 million robots by 2030, a new home service robot named MiPA, a new 'Omnisensor' technology platform for integrating input from multiple types of sensors, and an app store for robot skills that anyone can contribute to ... and profit from.

In this TechFirst, we chat with David Reger, CEO of Neura Robotics, the leading European humanoid robotics company.

We touch on advanced sensors, AI integration, and Neura Robotics' platform that enables extensive customization and scalability. We also chat about significant partnerships with companies like NVIDIA, SAP, and Deutsche Telekom.

00:00 Introduction to Humanoid Robotics

00:22 Interview with Neura Robotics CEO

00:39 Launch of '4NE-1' Humanoid Robot

02:26 Technical Specifications and Capabilities

04:39 Advanced Sensor Technology

09:24 Artificial Skin and Touch Sensory

14:05 AI Integration in Robotics

15:53 Challenges in Embodied AI

17:11 Robot Gyms and Training

19:10 Partnerships and Collaborations

20:56 The App Store for Robot Skills

22:18 AI-Assisted Development Platform

29:15 Introducing Mepa: The Home Robot

31:41 Future Prospects and Closing Remarks

AI is big these days. Massive. More parameters, more memory, more capability. But what if the future is in tiny AI. Neural networks as small at 8 kilobytes on tiny chips, embedded in everything?

Think smart shoes.

Smart doors.

Smart ... everything

In this episode of TechFirst, host John Koetsier discusses the future of smart devices with Yubei Chen, co-founder of AIzip.

The conversation explores how small-scale AI can revolutionize everyday objects like shoes, cameras, and baby monitors. They delve into how edge AI, which operates at the device level rather than in the cloud, can create efficient, reliable, and cost-effective smart solutions. Chen explains the potential and challenges of integrating AI into traditional devices, including the hardware and software requirements, and touches on the implications for product quality, safety, and cost.

This insightful discussion provides a look into the near future of ubiquitous, intelligent technology in our daily lives.

00:00 Introduction to Smart Matter

01:17 Examples of Smart Applications

03:40 Building Efficient AI Models

04:01 The Future of Edge AI

09:32 Hardware for Smart Devices

11:52 Potential Downsides and Challenges

18:14 Conclusion and Final Thoughts