17 Mar Why Intel Is Buying Mobileye, And What Does It Need To Do To Be Successful?
In a move that Intel hopes can propel it to the forefront of The Next Big Thing, Intel announced it would purchase Mobileye, an Israeli company that makes sensors and cameras for driverless vehicles. Buying a leader to become a leader is never cheap: Intel will pay $13.3B for the firm, a 34% premium over Mobileye’s closing price last Friday. The two companies have a history of collaboration, having announced a partnership with BMW last year to put driverless vehicles on the road by 2021. But until this acquisition, it was hard to take Intel seriously in the automotive market; Intel only has a partial solution in-house. It takes specialized silicon to keep up with the massive data rates generated by a vehicle or a missile, and Mobileye brings that needed capability to Intel. But there are a few potholes along the road to autonomous vehicles Intel will need to steer around to make this expensive acquisition pay off.
Routing and steering a fast-moving vehicle seems to be an easy task to most of us; you just point the car in the right direction, and your eyes and brain just figure it out, sending instructions to your hands and feet. But in fact, humans are tragically bad at the task; the US National Safety Council estimates 38,300 people were killed and 4.4 million injured on U.S. roads in 2015 alone. Let’s face it, we need to be replaced with safer technologies and many companies from Google to General Motors and Intel to intend on making that transition a reality. Yes, there are hurdles that need to be cleared, from the daunting computational task to the regulatory environment. But the economics are compelling and these barriers will be solved.
Why Did Intel Buy Mobileye, And Why Now?
The market for Advanced Driver Assisted Systems (ADAS) and fully autonomous (Level 5) vehicles is widely expected to explode during the decade. In fact, Intel says the market for vehicle systems and data services for autonomous driving will become a $70 billion opportunity by 2030. While the industry is in its infancy, Mobileye is already realizing good growth and revenue $358M in sales in 2016, a 49% increase over the previous year. Mobileye’s CTO and co-founder Amnon Shashua said in a conference call that the company is already working with 27 car manufacturers, including 10 production programs with Audi, BMW and others.
Meanwhile, a large portion of Intel’s revenues today come from powering PCs, networking and servers, and these older markets have become fairly stagnant, leading the company to lay off 12,000 employees last year. Having largely missed the smartphone market, the company now needs to find the next big growth engine, and this announcement shows it believes one of these will be self-driving vehicles, as well as other vision-guided systems such as robots, drones and other applications. And while $13B is not cheap for less than a half billion in revenues, one could argue that buying the leader in such a lucrative market will only get more expensive.
Moreover, Intel does not possess the requisite technologies to become a leader in this market by itself, and a partnering approach can be complex and slow. While Intel has CPUs that can act as the vehicle’s brains, it lacks the state of the art vision silicon and software. It also needs to deliver tightly integrated systems (CPU and accelerators) that can be difficult to design, negotiate and implement across company lines. Intel has already demonstrated this capability by integrating Altera and Xeon chips. Intel’s competitors in this space include NVIDIA, Qualcomm and Xilinx, all of whom are already delivering devices that integrate CPUs tightly coupled with vision with sensor fusion and machine learning. (See my Machine Learning Application Landscape for more information about this type of hybrid processor.) By acquiring Mobileye, Intel hopes that the combination of vision and brains will make it a leader in this fast growing market. And that certainly seems like a sound strategy.
So, What Does Intel Need to Do Now?
First, integrating two organizations, cultures and technologies headquartered half a world apart will be critical but will not be easy. Intel has experience here with integrating Altera, which should help. The combined team will need to create a technology and infrastructure roadmap, aligning and integrating hardware and software to compete in this market. Finally, it will need to build an integrated sales strategy to leverage Mobileye’s strong end-user relationships in the automotive industry.
Meanwhile, the combined company won’t have the market to itself and will face stiff competition from several sources. Strategically, I’d point out that this is the third acquisition, after Altera and Nervana, which are at least partly motivated by Intel’s former weak position in accelerators, especially with respect to NVIDIA. While Mobileye had first mover advantage in advanced vision chips and sensors, focusing on Lidar, some see NVIDIA’s GPUs and SOCs as superior solutions for multiple input modalities. In fact, Tesla, perhaps the leader in driverless car automation, has recently opted for the NVIDIA Drive PX 2 for future Tesla vehicles at the expense of Mobileye, its former supply partner. Mobileye technology is very good, but it delivers a custom platform, whereas NVIDIA’s Drive PX 2 and Jetson TX2 platforms are relatively open in the sense that OEM can program them for solutions tailored to their vehicles. NVIDIA’s platforms are general-purpose solutions that combine sensor fusion with CPUs and GPUs for machine learning. This allows the OEM to customize the platforms to meet their specific design requirements, while the Mobileye solution is a fixed vision-only part, not a programmable Machine Learning accelerator. Therefore it will be important to see whether Intel can leverage Mobileye’s technology and IP in other areas of machine learning inference. If it can, it would have a powerful duo: Nervana for ML training and Mobileye derivatives for inference. But here’s an important caveat: since Mobileye is currently a closed vision system, we don’t know if can deliver the performance for Machine Learning that NVIDIA has already demonstrated.
In addition to NVIDIA, Qualcomm’s purchase of NXP combined with its AI-enabled Snapdragon SOC, is clearly intended to enable it to compete in the automotive market. And Xilinx has recently announced the Xilinx reVISION platform which provides an SOC for vision-guided applications, combining ARM cores FPGAs with a rich software stack to simplify adoption. Xilinx FPGAs are no stranger to the automotive industry and already enjoy wide adoption across scores of models. While Intel theoretically could also compete in this market with its own Altera FPGAs, it would appear that Intel prefers to jump in with a proven leader instead of slowly building out its own FPGA-based solution. (Note that Intel’s Nervana Engine part, due out later this year, will probably target machine learning training in the datacenter, and will not be well suited for the low power automotive market.)
In conclusion, Intel’s acquisition can be seen as an expensive move to pole vault to become a Tier 1 provider of ADAS and fully autonomous vehicle computational solutions, a market that it can’t afford to miss. But it can also be seen as a yet another attempt to catch up in a market Intel was not well positioned to win. And a market expected to be as large as this one is already attracting a lot of healthy competition. Let’s hope they all get it right; we are counting on them to arrive safely at our destinations in the near future!