Exclusive: Wayve co-founder Alex Kendall on the autonomous future for cars and robots

UK-based autonomous vehicle startup Wave started life as a software platform loaded into a small electric «car» called Renault Twizy. Adorned with cameras, the company’s co-founders and PhD students, Alex Kendall and Amar Shah, tweaked the deep learning algorithms that power the car’s autonomous systems until they got it to drive around a medieval city unaided.

No fancy Lidar cameras or radars were needed. They suddenly realized that they were on the trail of something.

Fast forward to today and Wayve, now an AI modeling company, raised a $1.05 billion Series C funding round led by SoftBank, NVIDIA and Microsoft. This makes this the largest AI fundraiser to date in the UK and in the top 20 AI fundraisers globally. Even Meta’s head of artificial intelligence, Yann LeCun, invested in the company when it was young.

Wayve now plans to sell its autonomous driving model to various OEMs as well as manufacturers of new autonomous robots.

Image credits: Alex Kendall, CEO, Wayve

In an exclusive interview, I spoke with Alex Kendall, co-founder and CEO of Wayve, about how the company trained the model, new fundraising, licensing plans and the broader self-driving vehicle market.

(Note: The following interview has been edited for length and clarity)

TechCrunch: What tipped the balance to achieve this level of funding?

Kendall: Seven years ago, we started a company to build embodied artificial intelligence. We were dealing with construction technology (…) What happened last year was that everything really started to work (…) All the elements needed to turn this manufacturing dream into reality (gathered), and especially the first opportunity to embodied artificial intelligence has been applied in large numbers.

Production vehicles are now coming out with GPUs, surround cameras, radars and, of course, the appetite to bring in AI now and enable an accelerated journey from assisted to automated driving. Therefore, this fundraising is a validation of our technology approach and gives us the capital to turn this technology into a product and bring it to market.

Very soon you will be able to buy a new car and it will have Wayve’s artificial intelligence (…) Then this goes into enabling all kinds of embodied artificial intelligence, not just cars, but other forms of robotics. I think what we want to achieve here is to go far beyond what AI is today with language models and chatbots. To really enable a future where we can trust intelligent machines to whom we can delegate tasks, and of course, they can improve our lives. Self-driving will be the first example of this.

TC: How have you trained your self-driving model over the past few years?

Kendall: We partnered with Adsa and Ocado to collect data for the Autonomy Trial. It was a great way for us to launch this technology and it continues to be a very important part of our growth story.

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TC: What is the plan around licensing AI to OEMs, car manufacturers? What will be the benefits?

Kendall: We want to enable all car manufacturers around the world to work with our artificial intelligence, of course, from various sources. More importantly, we will get different data from different cars and markets, and this will produce the most intelligent and capable AI embodied.

TC: Which car manufacturers did you sell it to? Who did you land?

Kendall: We cooperate with several of the top 10 car manufacturers in the world. We are not ready to announce who they are today.

TC: What moved the needle for Softbank and other investors in terms of your technology? Is it because you are effectively platform independent and every car will now have cameras around it?

Kendall: That is largely true. SoftBank has publicly commented on their focus on artificial intelligence and robotics, and self-driving (technology) is just a cross-section of that. What we’ve seen so far with AV 1.0 approaches is where they throw all the infrastructure, HD maps, etc., into a very limited environment to prove this technology. But it’s a long journey from that to something that can be applied on a large scale.

We found that – and this is where SoftBank and Wayve are completely aligned in the vision of creating autonomy on a large scale – by introducing this software and a diverse set of vehicles around the world, millions of vehicles, not only can we build a sustainable business, we can also get different data from all over the world how we would train and validate the safety case to be able to implement AV on a large scale through «away, eyes off» driving around the world.

This architecture works with built-in intelligence to make its own decisions. It is trained in video and language, and we also bring general-purpose thinking and knowledge to the system. So it can handle the long, unexpected events you see on the road. This is the path we are on.

TC: Where do you see yourself in the landscape right now in terms of what’s already set out there?

Kendall: There’s been a bunch of really exciting evidence, but self-driving has pretty much stalled for three years and there’s been a lot of consolidation in the AV space. What this technology represents, what AI represents, is a complete game changer. It allows us to drive without Lidar and HD costs. This allows us to have built-in intelligence to work with. It can handle the complexities of unclear lane markings, cyclists and pedestrians, and is intelligent enough to predict how others will move so it can negotiate and operate in very tight spaces. This allows the technology to be implemented in the city without causing anxiety or road rage around you, and to drive in a way that is in keeping with the driving culture.

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TC: You made your first experiments at one time, enriching the Renault Tizzy with cameras. What will happen when car manufacturers put a lot of cameras around their cars?

Kendall: Automakers are already building vehicles that make this possible. I wouldn’t name the brands, but pick your favorite brand, and especially in higher end vehicles, they have surround cameras, surround radar and built-in GPU. It all makes this possible. Also, they are now set Software-defined vehiclesso we can do wireless updates and download data from the vehicle.

TC: What was your «book»?

Kendall: We have built a company that has all the pillars needed to build. Our playbook is AI, Talent, Data and Computing. In terms of talent, we’ve built a brand that is the intersection of artificial intelligence and robotics, and we’ve been lucky enough to bring some of the best minds around the world to work on this problem. Microsoft is a long-standing partner of ours, and the amount of GPU computing they’re giving us in Azure will allow us to train the model at a level we’ve never seen before. A truly massive, embodied AI model that can actually build the safe and intelligent behavior we need for this problem. And then NVIDIA, of course. Their chips are the best in class on the market today and enable the application of this technology.

TC: Will all the training data you get from the brands you work with be mixed into your model?

Kendall: That’s right. This is exactly the model we were able to prove. No car manufacturer will produce a model that is safe enough on its own. Being able to train AI on data from many different car manufacturers will be safer and more efficient than just one. It will come from multiple markets.

TC: So you will actually be the owner of probably the largest amount of driving data in the world?

Kendall: That is certainly our ambition. But we want to make sure that this artificial intelligence goes beyond driving – as real artificial intelligence in person. It is the first visualization-language-action model that can drive a car. It is trained not only on driving data, but also on text from the Internet and other sources. We even train our model on UK government PDF documents that tell you the highway regulations. Let’s go to different data sources.

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TC: So it’s not just cars, but robots too?

Kendall: Exactly. We build an embodied core model of artificial intelligence as a general-purpose system trained on very different data. Consider home robotics. The data (from it) is diverse. It’s not some limited environment like manufacturing.

TC: How do you plan to expand the company?

Kendall: We’re continuing to grow our AI, engineering and product teams both here (in the UK) and in Silicon Valley, and we’ve just launched a small team in Vancouver. We will not ‘blitzscale’ companies, but use disciplined, purposeful growth. The headquarters will remain in Great Britain

TC: Where do you think the centers of AI talent and innovation are in Europe?

Kendall: It’s pretty hard to look for anywhere outside of London. I think London is by far the dominant place in Europe. We’re in London, Silicon Valley and Vancouver—probably in the top five or six of the world’s biggest hubs. London has been a great place for us so far. To begin with, we grew out of academic innovation in Cambridge. Where we are now until the next chapter is a little off the beaten path. But in terms of where we are now, it’s been a brilliant ecosystem (in the UK).

There are many good things to say about corporations, law and tax. On the regulatory front, we have been working with the government for the last five years on new legislation for self-driving in the UK. It’s passed the House of Lords, it’s almost passed the House of Commons, and it’s due to come into effect soon and make all this legal in the UK The ability of the government to rely on this to work with us (…) we’ve really been working in the weeds for it and we had more than 15 visits by ministers. It’s been a very good partnership so far and we’ve certainly felt the government’s support.

TC: Do you have any comments on the EU’s approach to autonomous driving?

Kendall: Autonomous driving is not part of the AI ​​law. It is a separate vertical and should be regulated with subject matter experts as a separate vertical as well. It’s not some mismatched catch-all and I’m glad for that. It’s not the fastest way to innovate in certain verticals. I think we can do this responsibly by working with specific automotive regulatory bodies that understand the problem space. Therefore, sector-specific regulation is really important. I am glad that the EU has taken such an approach to self-driving.

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