Vehicles of The Future: John Hayes Of Ghost Autonomy On The Leading Edge Technologies That Are Making Cars & Trucks Smarter, Safer, and More Sustainable
An Interview With David Leichner
Lots of people would love for faster cycles in car development, but this industry is one you need to get it right the first time — customers will not tolerate a partially built product. Incredible cross-domain engineering is required to make one of the most complex industries work, which can only be achieved through copious meetings (i.e., time).
The automotive industry has been disrupted recently with new exciting technologies that have made cars and trucks much smarter, much safer, and much more sustainable and more environmentally friendly.
What other exciting disruptive technologies will we see in the next few years? How much longer will fossil fuel powered cars be produced? When will we see fully autonomous vehicles? Can we overcome the challenge of getting stuck in traffic? As cars become “moving computers”, do we have to worry about people hacking our cars? How else will our driving experience be different over the next five years? To address these questions, Authority Magazine started a new interview series about “Exciting Leading Edge Technologies That Are Making Cars & Trucks Smarter, Safer, and More Sustainable.” In this series we are talking to leaders of automotive companies, automotive tech companies, EV companies, and other tech leaders who can talk about the vehicles of the future. As a part of this series, I had the pleasure of interviewing John Hayes.
John Hayes is CEO and founder of autonomous vehicle software innovator Ghost Autonomy. Prior to Ghost, John founded Pure Storage, taking the company public (PSTG, $11 billion market cap) in 2015. As Pure’s chief architect, he harnessed the consumer industry’s transition to flash storage (including the iPhone and MacBook Air) to reimagine the enterprise data center inventing blazing fast flash storage solutions now run by the world’s largest cloud and ecommerce providers, financial and healthcare institutions, science and research organizations and governments. Like Pure, Ghost uses software to achieve near-perfect reliability and re-defines simplicity and efficiency with commodity consumer hardware. Ghost is headquartered in Mountain View with additional offices in Detroit, Dallas and Sydney. Investors including Mike Speiser at Sutter Hill Ventures, Keith Rabois at Founders Fund and Vinod Khosla at Khosla Ventures have invested $200 million in the company.
Thank you so much for joining us in this interview series! Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started in the automotive industry?
I was just fifteen when I started my career working at startups as a programmer at a company in Burlington, Ontario. I’d been doing some programming on my own, and to my surprise, they gave me a job. It carried me throughout college and taught me valuable lessons about working in a smaller company.
While in college studying to be an engineer, I also played a lot of online games and decided I wanted to extend one particular game myself. I created a small developer community to make plugins for the game. From that point, I was offered a job working for a company called There, which was an operation on a much larger scale than I was used to. I saw many different engineering disciplines all working towards one product, and that expanded my interests in growing my own company.
Immediately prior to founding Ghost Autonomy, I was co-founder and chief architect at Pure Storage, where we parlayed the consumer industry’s transition to flash to reimagine data center storage. The high-performance data solutions we built are run today by some of the world’s largest cloud providers, financial services institutions, healthcare providers and governments and I’m thrilled that the company has continued to flourish since its IPO in 2017 (NASDAQ:PSTG).
After about 8 years doubling down on my interest in building infrastructure at Pure, I was itching to put my engineering hat on again to create a new product. I was looking for an industry that would allow me to explore my interest in building technically complex things that are well-produced. At that time –2017 — mobile was the driving force in technology and AI was on the cusp of transforming the market. The intersection of these two trends led me to autonomous vehicles, where I’m able to apply my software expertise to the traditionally hardware-centric automotive industry, as I did at Pure in the previously hardware-centric data storage industry. At Ghost we’re bringing software-defined autonomous driving technology to consumer cars on commodity, consumer-grade hardware, giving advanced features like autonomy to the masses. It’s exciting to help propel an industry in a half-century of stagnation to a place of extraordinary innovation.
Can you share the most interesting story that happened to you since you began your career?
When we decided to take Pure Storage public in 2015, we had to delay our IPO by a week, because we found out the Pope was visiting New York on the same day. We were so excited and had worked so hard to go public, but decided “ We just can’t compete with the Pope.”
Ok wonderful. Let’s now shift to the main focus of our interview. Can you tell our readers about the most interesting projects you are working on now?
At Ghost, we are pioneering the use of multi-modal large language models (MLLMs) in autonomous driving. The automotive industry is at the precipice of a revolution dividing innovators and naysayers, and we are working to solve complex scenarios that autonomous cars face — like urban driving and novel or unforeseen scenes — in a scalable way.
MLLMs, which are now capable of processing, understanding and drawing conclusions from diverse inputs like video, images and sounds, are opening up an entirely new set of use cases across industries such as medicine, legal, automotive and more. Ghost is exploring the use of large language models (LLMs), MLLMs, and other large models for automotive use cases, to bring true autonomous driving software to the next generation of consumer cars. We recently announced new funding from the OpenAI Startup Fund, which will allow us to bring large-scale MLLMs to autonomous driving by accelerating our ongoing research and development of LLM-based complex scene understanding required for urban autonomy.
How do you think this might change the world?
LLMs provide a breakthrough that will finally enable everyday consumer vehicles to reason about and navigate through the toughest scenarios that few companies to date have been able to drive, and none have yet mastered. For example, construction zones have unusual components that can be difficult for simpler models to navigate — temporary lanes, flagpersons holding signs that change, and complex negotiation with other road users. LLMs have been shown to be capable of processing all of these variables in concert with human-like levels of reasoning.
Consumers also always want the latest and greatest feature-rich capabilities at their fingertips — we update our devices every time a new OS comes out. As vehicles become more commoditized and competition heats up, cars will increasingly be differentiated based on their software capabilities (e.g., safety, entertainment and autonomy features), not their hardware (e.g., heated seats, rims, sunroofs). A software-defined vehicle can be continually improved with over-the-air software updates that add cool new capabilities and fix issues remotely.
We believe that software is the key to delivering advanced features like consumer autonomy to the mass market and winning market share.
Keeping “Black Mirror” in mind, can you see any potential drawbacks of this technology that people should think more deeply about?
The more pleasant it is to drive, the longer people will be willing to be in their cars, and as a result, the more traffic that may cause. Many people transitioned the past few years into working from home, moving further from their workplaces without commute considerations. This eliminated significant roadway congestion. Making transportation easier with self-driving built into consumer cars will translate into more people on the roads traveling longer distances and potentially putting more demand on our road infrastructure. If self-driving cars prove extremely popular, we will probably need to invest more heavily in our road system to meet consumer demand.
What are a few things that most excite you about the automotive industry as it is today? Why?
AI innovation is exploding in every sector and holds massive potential for transforming the automotive industry. New ways to drive will emerge that combine advanced autonomous capabilities with understanding of driver intent — for example, systems that use voice commands to take the next exit, automatically avoid collisions when a driver is distracted, or recognize when a driver is asleep and safely pull the car to the side of the road.
I’m excited to see how the automotive industry will transform with AI and LLMs, creating new experiences for drivers that are advanced and secure. At Ghost, we understand that safety is the key concern for drivers when looking at autonomous capabilities for themselves, and we see the automotive industry embracing AI to support safety initiatives.
What are a few things that most concern you about the automotive industry as it is today? What must be done to address these challenges?
The automotive industry — like all the other industries embracing AI — is impacted by current regulations on technological advancements. The recent White House executive order on AI poses a material threat to innovation in the U.S., potentially killing America’s next golden goose before it’s even hatched.
AI is the next transformative technology platform — comparable to the introduction of smart phones 15 years ago and the birth of the internet 30 years ago. The executive order threatens to effectively close off the new ‘AI platform,’ restricting development, use and oversight to a handful of incumbents.
Ultimately, it’s consumers who will lose out as a result. All of the potential life-changing and life-saving applications of AI may now never see the light of day — and those that do will be built by companies in other countries like China, who will reap rewards and outpace the U.S. on AI innovation, which they are already doing when it comes to autonomous capabilities.
Based on your vantage point as an insider in the automotive industry, what other exciting disruptive technologies will we see in the next few years? Can you share some of the new developments that will make vehicles smarter, safer, and more sustainable?
Thanks to generative AI, data is no longer the new oil when it comes to autonomy. Let me explain what I mean. Until recently, the ultimate competitive advantage established players (read: Tesla) had was access to enormous data sets, sourced in the real world, for training their advanced AI and autonomous driving models. However, generative AI has erased this advantage by enabling anyone to create vast synthetic data sets at low cost, eliminating the requirement to collect so much real-world data to power models.
LLMs — with their fusion of general intelligence and specialized problem-solving capabilities — will serve as the great equalizer in the AV space. They will empower emerging companies to compete at a comparable level to the incumbents, fostering innovation and competition in the race towards fully autonomous vehicles. Generative AI has changed a critical part of the equation and is dismantling one of Tesla’s biggest moats in the process.
In your opinion, how much longer will fossil fuel powered cars be produced? When do you think EVs will be the majority of vehicles in use? Can you explain?
EVs are much more consumer friendly than internal combustion engine (ICE) vehicles, with significant downstream implications on everything from pricing to model and trim development to manufacturing.
EVs are driving unprecedented levels of price transparency in the automotive business. The old way of building and selling cars (i.e., gas-powered vehicles) thrived on opacity — literally thousands of permutations of trim options stacked on complex financing options (e.g., teaser rates, rebates, trade-ins, etc.) all made price comparisons almost impossible. EVs by contrast are much simpler products, with far fewer options in the powertrain and otherwise. Led by Tesla, we are seeing the number of options and permutations of vehicles shrink dramatically. This uniformity makes it significantly harder for OEMs to play pricing games, benefitting the consumer.
Though today not every aspect of EVs is consumer friendly — range anxiety is still a real issue. Increasing the number of charging stations and reducing the time it takes to charge should dramatically improve this issue in a relatively short amount of time.
When do you think we will see fully autonomous vehicles deployed in a mainstream way? What do you think are the main barriers to reaching that stage?
For autonomous vehicles to go mainstream, mixed mode driving with drivers still in the front seat needs to be a first step to ensure comfort, safety and security. There is persistent skepticism surrounding robotaxis and autonomous vehicles, but mostly by those who either have no experience with self-driving vehicles or don’t fully understand their current capabilities. Everyday advanced driver assistance (ADAS) has fallen behind the state of the art. According to our recent industry research, more than half (57%) of people who bought a new car in the last five years listed autonomous driving or ADAS as an important consideration, and safety was the overwhelming stated benefit.
OEMs must focus on nearer-term applications for advanced safety and driving tech. A few ingredients are essential to pulling these timelines forward in the consumer space — low cost hardware, advanced autonomy capabilities that live in software and can be continually improved via over-the-air updates, and well-defined operational design domains (ODDs), making it obvious to consumers which ADAS or autonomous capabilities are available in each driving environment.
How else will our driving experience be different over the next five years?
As the software-defined car takes shape, it’s clear that, beyond autonomy, the automotive software opportunity is wide open and largely undefined in terms of scope and potential applications. Copying Apple’s open software development model may well be the right way to build the next trillion-dollar car company.
However, to unlock a developer ecosystem, car companies must commit to building and servicing a real, open API and they must make the entire car accessible by software — and by software developers. This requires enabling direct access to core components, like data feeds from sensors. It also requires reducing or eliminating entirely specialized components or modules that are walled off from developer input and innovation. On top of that, an API that can only access the car’s infotainment system misses the point — third-party software isn’t just about media consumption, but about imagining new ways to drive and interact with the whole car.
Software will emerge as the key differentiator in the “future car,” offering consumers autonomous vehicles capabilities that can be continually improved to make the car experience meaningfully better. At Ghost, we are doing just that by bringing the first self-driving software solution built to bring the car of the future to the mainstream consumer automotive market and ultimately transforming driving experiences for everyone.
What are your “5 Things You Need To Create A Highly Successful Career In The Automotive Industry?
Since I am relatively new to the automotive industry, I really only have one key piece of advice to share: patience is the key to making change and success in this industry. You need to not only remind yourself that things take time, but remind your investors as well. Design cycles in the automotive industry often last up to five years and almost every major decision is made three years before being put into action, which can be a long time to go without revenue. Lots of people would love for faster cycles in car development, but this industry is one you need to get it right the first time — customers will not tolerate a partially built product. Incredible cross-domain engineering is required to make one of the most complex industries work, which can only be achieved through copious meetings (i.e., time).
You are a person of great influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)
A lot more research and development can be done in public than is currently being done. Almost all recent AI advancements have been published research — subject to scrutiny and experimentation — but more of this can be done on the engineering side.
In the past, building monuments and institutions has been limited to the very wealthy, opening contributions to technical capital to individuals. What has been missing is corporate contributions. Today, corporations are building and submitting to open source projects, but still trying to keep as much propriety as possible. Corporate teams bring a level of production that makes open source viable for new types of products and, often, it’s not the software itself that’s the value but rather the execution and operation of software. Publishing more software publicly is the modern version of creating monuments as they are constructive and cumulative.
How can our readers further follow your work online?
They can learn more about Ghost Autonomy here or visit my LinkedIn account.
Thank you so much for the time you spent doing this interview. This was very inspirational, and we wish you continued success.
About The Interviewer: David Leichner is a veteran of the Israeli high-tech industry with significant experience in the areas of cyber and security, enterprise software and communications. At Cybellum, a leading provider of Product Security Lifecycle Management, David is responsible for creating and executing the marketing strategy and managing the global marketing team that forms the foundation for Cybellum’s product and market penetration. Prior to Cybellum, David was CMO at SQream and VP Sales and Marketing at endpoint protection vendor, Cynet. David is a member of the Board of Trustees of the Jerusalem Technology College. He holds a BA in Information Systems Management and an MBA in International Business from the City University of New York.
