Vaire Computing, based in London and Seattle, is betting that chips that can do reversible computing are going to be the way forward for the world.
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Second-hand car auction platform Motorway hits Unicorn status after $190M raise with Index, ICONIQ
It was only in June that Motorway – a U.K. platform on which professional car dealers can bid in an auction for privately owned cars for sale – raised $67.7 million in a Series B round. It’s now raised a $190m Series C funding round led by Index Ventures and ICONIQ Growth, a leading Silicon Valley technology growth investment firm. Existing investors Latitude, Unbound, and BMW i Ventures also participated in the round. The startup is now claiming a valuation of over $1bn.
Part of the reason is the impact of the COVID pandemic on supply chains. Second-hand cars have boomed in price because new cars are being made in smaller numbers due to the lack of supply of computer chips and other essential equipment from China.
On Motorway consumers can sell their car via a smartphone app that also uses computer vision to assess the state of the car. The cars are then bid on by professional car dealers in a daily online auction, with the car collected for free by the winning dealer within 24 hours. Given it’s also a “contactless” process, dealers and car owners increasingly seeking to buy and sell cars online.
Motorway says it now has a network of 4,000 professional car dealers using the platform and claims it has booked a 300% uplift in third-quarter sales to $411 million compared with $105 million last year. Some 100,000 used cars have been sold on Motorway since launch, with over 8,000 cars currently being sold a month, with over $2bn projected completed sales over the next year.
Motorway is also announcing the appointment of James Wilson, former Director of Marketplace Fulfillment for Amazon UK, as Chief Operating Officer.
Tom Leathes, CEO of Motorway, said: “8,000 car sales a month is still less than one percent of UK used car sales – so there’s a massive opportunity ahead.”
Danny Rimer, Partner at Index Ventures, said: “Since joining the board, following our initial investment in June, I have experienced first-hand just how fast Motorway is growing and how agile the team is in scaling the business to support this incredible growth.”
Yoonkee Sull, Partner at ICONIQ Growth said: “The used car market’s move online is only accelerating and we believe Motorway is delivering the best consumer experience and the most differentiated supply to dealers in the UK.”
This latest investment brings Motorway’s all-time raise to $273m since it was founded by Leathes, Harry Jones and Alex Buttle in 2017.
In a call with me Leathes added: “There’s no connection with BMW particularly, but they are automotive specialists so they bring quite a lot of knowledge to the white broader market and trends that are happening. They were also part of the B along with Latitude and Unbound.”
“What motorway does differently to a lot of competitors is that we are we’re not a retailer. We don’t own inventory. We’re a marketplace. And so that that allows us to scale much more quickly,” he said.
MIT aims to speed up robot movements to match robot thoughts using custom chips
MIT researchers are looking to address the significant gap between how quickly robots can process information (relatively slowly), and how fast they can move (very quickly thanks to modern hardware advances), and they’re using something called ‘robomorphic computing’ to do it. The method, designed by MIT Computer Science and Artificial Intelligence (CSAIL) graduate Dr. Sabrina Neuman, results in custom computer chips that can offer hardware acceleration as a means to faster response times.
Custom-built chips tailored to a very specific purpose are not new – if you’re using a modern iPhone, you have one in that device right now. But they have become more popular as companies and technologists look to do more local computing on devices with more conservative power and computing constraints, rather than round-tripping data to large data centers via network connections.
In this case, the method involves creating hyper-specific chips that are designed based on a robot’s physical layout and and its intended use. By taking into account the requirements a robot has in terms of its perception of its surroundings, its mapping and understanding of its position within those surroundings, and its motion planning resulting from said mapping and its required actions, researchers can design processing chips that greatly increase the efficiency of that last stage by supplementing software algorithms with hardware acceleration.
The classic example of hardware acceleration that most people encounter on a regular basis is a graphics processing unit, or GPU. A GPU is essentially a processor designed specifically for the task of handling graphical computing operations – like display rendering and video playback. GPUs are popular because almost all modern computers run into graphics-intensive applications, but custom chips for a range of different functions have become much more popular lately thanks to the advent of more customizable and efficient small-run chip fabrication techniques.
Here’s a description of how Neuman’s system works specifically in the case of optimizing a hardware chip design for robot control, per MIT News:
The system creates a customized hardware design to best serve a particular robot’s computing needs. The user inputs the parameters of a robot, like its limb layout and how its various joints can move. Neuman’s system translates these physical properties into mathematical matrices. These matrices are “sparse,” meaning they contain many zero values that roughly correspond to movements that are impossible given a robot’s particular anatomy. (Similarly, your arm’s movements are limited because it can only bend at certain joints — it’s not an infinitely pliable spaghetti noodle.)
The system then designs a hardware architecture specialized to run calculations only on the non-zero values in the matrices. The resulting chip design is therefore tailored to maximize efficiency for the robot’s computing needs. And that customization paid off in testing.
Neuman’s team used an field-programmable gate array (FPGA), which is sort of like a midpoint between a fully custom chip and an off-the-shelf CPU, and it achieved significantly better performance than the latter. That means that were you to actually custom manufacture a chip from scratch, you could expect much more significant performance improvements.
Making robots react faster to their environments isn’t just about increase manufacturing speed and efficiency – though it will do that. It’s also about making robots even safer to work with in situations where people are working directly alongside and in collaboration with them. That remains a significant barrier to more widespread use of robotics in everyday life, meaning this research could help unlock the sci-fi future of humans and robots living in integrated harmony.