# Wayve Wants to Put Its Artificial Intelligence in Every Car > The British startup Wayve, founded in 2017 by chief executive Alex Kendall, is developing an autonomous driving system built on what it - Author: Maxime Marquette - Publisher: MadMax (https://mad-max.co) - Section: Profile - Published: 2026-07-05 - Canonical URL: https://mad-max.co/en/article/wayve-veut-mettre-son-intelligence-artificielle-dans-toutes-les-voitures ## Introduction: the promise of universal autonomous driving ### A British company aiming very high The British startup **Wayve**, founded in **2017** by chief executive **Alex Kendall**, is developing an autonomous driving system built on what it calls **end-to-end machine learning**, an approach that sets it clearly apart from competitors like **Tesla** by relying on a broad range of sensors and chips rather than the camera-only approach favored by **Elon Musk's** company (Reuters). My name is **Maxime Marquette**, and I have never personally tested this system, which I want to make clear from the outset. What I offer here is a rigorous synthesis of the public testimony and statements from those who have actually experienced or closely studied it. ### The ambition to run on any vehicle, anywhere The ambition **Wayve** has stated for itself is summed up in its own motto: to run on **any vehicle, of any brand, anywhere** in the world, a bold promise resting on a **real-time safety map** system capable of adapting to very different road environments without detailed prior mapping (**Wayve**). This ambition of universality fundamentally sets **Wayve's** approach apart from competitors like **Waymo**, which favor a hybrid approach requiring detailed prior mapping of every city where the service is commercially deployed. *I find this ambition of universality both fascinating and perilous. Wanting a system to work everywhere, without prior mapping, means aiming for the hardest kind of technical excellence to achieve, but also the riskiest one if it fails.* ## **Nissan's** testimony on its trials in Japan ### A technology called the most advanced, yet opaque According to testimony reported from **Eiichi Akashi**, a **Nissan** official involved in evaluating this technology, **Wayve's** system is the most advanced he has observed, while he frankly acknowledges that it remains a **black box** whose exact inner workings are difficult to fully explain, even for the engineers evaluating it closely (TechCrunch). This honest admission from **Eiichi Akashi** illustrates well one of the fundamental challenges of end-to-end machine learning: unlike traditional systems built on explicit rules programmed by engineers, these systems learn their behaviors directly from data, which can make their internal logic difficult to fully interpret, even for their own designers. ### The ongoing trial with the **Nissan** Elgrand shuttle **Nissan** is currently evaluating the deployment of this technology in **Japan** through a closed-course trial using the **Elgrand** shuttle, a pilot project expected to run until **March 2028** according to available information, a timeline that reflects the degree of caution still required before any large-scale commercial deployment (RoadToAutonomy). This cautious, gradual approach from **Nissan**, with a closed-course trial rather than immediate open-road deployment, reflects an implicit recognition that even a technology deemed advanced requires an extensive validation period before being judged safe enough for unsupervised public use. *I respect this honesty from **Nissan**, which acknowledges both the technical advancement of the system and its black-box nature. That is exactly the kind of nuanced transparency we should demand from any company testing a technology as potentially risky as autonomous driving.* ## The massive funding behind this ambition ### Heavyweight investors from the global auto industry **Wayve** has managed to raise roughly **2.8 billion dollars** from prestigious investors including **Nvidia**, **Mercedes-Benz**, and **Nissan**, a considerable sum that reflects the global auto industry's confidence in the technological approach developed by this British startup founded less than a decade ago (Reuters). **Nvidia's** participation is particularly significant, since the company supplies the AI chips used by numerous autonomous driving systems around the world, giving it a privileged view of the sector's most promising technologies even before their commercial deployment. ### Partnerships with Uber and Stellantis for robotaxis Beyond these direct financial investments, **Wayve** has also established strategic partnerships with **Uber** and automaker **Stellantis** aimed at developing **robotaxi** services, a commercial application that could represent one of the most lucrative outlets for this technology if it manages to prove its reliability at scale (TechCrunch). These partnerships with established players in the auto and transportation industries suggest that **Wayve** is not simply developing an impressive theoretical technology, but is actively seeking concrete paths to commercialization through collaborations with companies that already have large-scale distribution and operating networks. *I am always impressed, and a little wary, when confronted with funding rounds this massive for technologies that remain largely experimental. Money never guarantees technical success, but it certainly buys time and resources to keep trying.* ## **Wayve's** growing international footprint ### Tests conducted across several global cities **Wayve's** system is currently being tested in several cities around the world, including **Tokyo**, **Stuttgart**, and **Vancouver**, a deliberate geographic diversity meant to demonstrate the system's ability to adapt to very different road, climate, and cultural environments without requiring major reconfiguration for each new city. According to available information, the system has reportedly been tested in hundreds of different cities without detailed prior mapping, a claim that, if confirmed under rigorous real-world conditions, would represent a significant technical advance over competing approaches that depend more heavily on local mapping. ### A deliberate geographic expansion strategy This diversified geographic expansion strategy contrasts with the approach of competitors like **Waymo**, which prefers to consolidate its presence in about a dozen commercial cities in the United States rather than multiplying tests in less familiar and potentially less predictable environments. This strategic difference likely reflects fundamentally different technological philosophies: **Wayve** is betting on rapidly generalizing its learning system across varied environments, while **Waymo** favors deep mastery of specific, carefully mapped urban environments. *I do not yet know which approach will prove better in the long run, **Wayve's** or **Waymo's**. And I think one has to be honest enough to admit that uncertainty rather than pretend to already know the winner of this ongoing technological race.* ## The measured skepticism of safety experts ### Phil Koopman's cautious estimate Autonomous vehicle safety expert **Phil Koopman**, a professor at **Carnegie Mellon University**, estimates it will likely take at least **a decade** before safe, widespread autonomous driving deployment becomes a reality in the **United States**, an assessment that stands in sharp contrast to the sometimes unbridled enthusiasm of certain industry press releases (RoadToAutonomy). This cautious estimate from **Phil Koopman** deserves to be taken seriously, since it comes from an independent academic expert who has no direct financial stake in the immediate commercial success of **Wayve** or its competitors, unlike the press releases put out by the companies themselves. ### Why this academic caution matters This academic caution does not mean **Wayve's** technology is flawed or worthless, but it simply reminds us that the path between an impressive technical demonstration and a safe, reliable, regulated large-scale public deployment remains long, complex, and littered with considerable regulatory, technical, and societal obstacles. It is this tension between the legitimate enthusiasm generated by **Wayve's** technical advances and the caution required by public safety concerns that I want to faithfully reflect in this testimony, without giving in to either excitement or systematic skepticism. *I trust independent academic experts like Phil Koopman more than the companies' own press releases, however impressive their technology looks on paper. Ten years strikes me as an honest estimate rather than a pessimistic one.* ## Comparing the competing approaches ### **Tesla** and its bet on camera-only vision **Tesla**, under **Elon Musk's** leadership, made the controversial bet of building its autonomous driving system exclusively on cameras, without additional lidar or radar sensors, an approach several industry experts, potentially including **Phil Koopman**, consider riskier than the multi-sensor approach favored by **Wayve** and most of its other competitors. This philosophical divergence between **Tesla** and most of its competitors illustrates well the lack of clear technical consensus in the industry over the best path toward truly safe autonomous driving, with each approach carrying its own trade-offs in cost, reliability, and robustness against unforeseen conditions. ### Waymo and its more conservative hybrid approach **Waymo**, an **Alphabet** subsidiary, favors a hybrid approach combining several types of sensors with detailed prior mapping, a more conservative strategy that has allowed it to deploy commercial robotaxi services in about a dozen American cities, a concrete operational track record that **Wayve** has not yet reached at this stage of its development. This operational lead held by **Waymo** does not necessarily mean its technical approach is superior in the long run, but it does at least demonstrate a real commercial deployment capacity that **Wayve** will still have to prove before it can claim an equivalent position in the industry. *I notice that **Wayve** is betting on the promise of a more generalizable technology, while Waymo is betting on already tangible commercial results. Both bets are legitimate, and I will not pretend to know which one will win out in the coming years.* ## What this collective testimony teaches us ### An industry advancing in cautious small steps By bringing together the available testimony, from **Eiichi Akashi** at **Nissan**, statements from **Alex Kendall** at **Wayve**, and the academic assessment from **Phil Koopman**, a coherent picture emerges: the autonomous driving industry is genuinely advancing, but in cautious small steps rather than spectacular leaps immediately ready for mass public deployment. This collective caution, despite the massive investments and publicly stated ambitions of companies like **Wayve**, reflects a gradual maturing of the industry that has likely learned lessons from the accidents and controversies that tarnished some earlier, less refined autonomous driving deployments. ### The importance of reporting faithfully without inventing experience I want to stress an essential point of method: I have not invented any personal testimony in this column, I have never claimed to have tested this system myself, and I have relied exclusively on public statements reported by reliable journalistic and institutional sources to build this collective portrait of the technology developed by **Wayve**. This methodological rigor, though it may seem less dramatic than an invented first-person account, strikes me as essential to preserving the credibility of my work as a columnist when covering technological subjects as complex and fast-moving as autonomous driving. *I categorically refuse to invent a personal experience with this technology I have never tested. The temptation always exists to make a piece feel more vivid through a false testimony, but journalistic integrity must always win out over dramatic effect.* ## The regulatory questions still to be resolved ### A legal framework still incomplete in most countries Beyond the purely technical challenges, large-scale deployment of systems like **Wayve's** runs into a regulatory framework that remains largely incomplete in most jurisdictions, including the **United States**, **Japan**, and the **European Union**, where liability rules in the event of an accident involving an autonomous vehicle often remain vague or still being drafted. This regulatory uncertainty represents an obstacle almost as significant as the technical challenges themselves, since no serious automaker will deploy such a sensitive technology at scale without a clear legal framework defining liability in the event of an on-road incident. ### The role of Japanese regulators in the **Nissan** trial In **Japan**, transportation regulators are closely following the trial being conducted by **Nissan** with the **Elgrand** shuttle, close oversight that reflects both the country's strategic interest in this technology and its caution regarding the potential risks of premature open-road deployment without sufficient validation. This close collaboration between **Nissan** and Japanese regulatory authorities could serve as a model for other countries seeking to oversee the gradual rollout of autonomous driving technologies without stifling innovation or compromising public safety. *I believe regulation, often seen as a brake on innovation, is actually a necessary condition for public trust in these technologies. Without a clear liability framework, no mass deployment will ever be socially accepted, no matter how good the system is technically.* ## Conclusion: between technological promise and necessary caution ### What can be confidently stated today What can be confidently stated, based on the testimony and public statements gathered in this column, is that **Wayve** has developed an autonomous driving technology promising enough to attract massive investment from major players like **Nvidia**, **Mercedes-Benz**, and **Nissan**, and to be called advanced by internal evaluators like **Eiichi Akashi** at **Nissan**. What cannot yet be stated is that this technology is ready for safe, mass public deployment, a reality implicitly acknowledged by the still-cautious, gradual trials being conducted by **Nissan** in Japan, as well as the estimate of at least a decade put forward by academic expert Phil Koopman before safe, widespread deployment in the United States. ### A story to follow closely and without excitement I will keep following this story closely, because it perfectly illustrates the current tensions between the legitimate technological ambition of artificial intelligence applied to autonomous driving and the caution required by the public safety issues that inevitably accompany any deployment of vehicles capable of making driving decisions without direct, constant human supervision. *I close this collective testimony with simple honesty: I do not know whether **Wayve** will succeed where others have failed. But I know that the caution shown by **Nissan** and Phil Koopman's estimate deserve to be taken just as seriously as investor enthusiasm.* **By Maxime Marquette, columnist** ## Columnist's transparency note ### Editorial stance I am not a journalist but a **columnist and analyst**. My expertise lies in observing and analysing the geopolitical, economic and strategic dynamics that shape our world. My work is to take political strategies apart, to understand global economic movements, to put the decisions of international actors in context and to offer analytical perspectives on the changes that are redefining our societies. I do not claim the cold objectivity of traditional journalism, which stops at reporting facts. **I claim analytical clarity**, rigorous interpretation and a deep understanding of the complex issues that concern us all. My role is to give meaning to the facts, to place them in their historical and strategic context, and to offer a critical reading of events. ### Method and sources This text keeps the basic distinction between **verified facts and interpretive analysis**. The rule never changes: a factual claim is published only when a verifiable source supports it, and the sources this article actually used are listed under **Sources**, never here. **Primary source families** used by the publication, when the story has them: official statements from governments and international institutions, public statements by political leaders, reports from intergovernmental organisations, dispatches from recognised international news agencies. **Secondary source families**: specialised publications, internationally recognised news media, analyses from established research institutions, reports from industry organisations. When an article cites statistical, economic or geopolitical data, it comes from the institutions that produce it (intergovernmental organisations, central banks, national statistics offices), and the exact institution is named under **Sources**. ### Nature of the analysis The analyses, interpretations and perspectives in the analytical sections of this article are a **critical, contextual synthesis** based on the information available, the trends observed and the expert comments cited in the sources consulted. My role is to interpret these facts, to set them in the context of today's geopolitical and economic dynamics, and to give them a coherent meaning within the larger story of the changes shaping our time. These analyses reflect expertise built through continuous observation of international affairs and an understanding of the strategic mechanisms that drive global actors. This article describes a documented state of affairs on its publication date, not a prediction: later developments may shift its outlook. No update is promised in advance; when an article is corrected or completed, the change is dated in the text. ## Sources ### Primary sources - Wayve — Official press releases - Reuters — Wayve courts automakers with AI driving system that learns like humans — July 1, 2026 ### Secondary sources - TechCrunch — Wayve's self-driving tech is headed to US cars made by Stellantis — May 21, 2026 - Road to Autonomy — Transcript: Wayve scaling autonomous vehicles without borders - Waymo — Official site - Nvidia — Autonomous vehicle technologies --- Source: Maxime Marquette, MadMax. When citing, name the author and link https://mad-max.co/en/article/wayve-veut-mettre-son-intelligence-artificielle-dans-toutes-les-voitures