In the race to develop self-driving technology, Chinese Internet giant Baidu unveiled its 50+ partners in an open source development program, revised its timeline for introducing autonomous driving capabilities on open city roads, described the Project Apollo consortium and its goals, and declared Apollo to be the ‘Android of the autonomous driving industry’.

At a developer's conference last week in Beijing, Baidu described its plans and timetable for its self-driving car technology. It will start test-driving in restricted environments immediately, before gradually introducing fully autonomous driving capabilities on highways and open city roads by 2020. Baidu's goal is to get those vehicles on the roads in China, the world's biggest auto market, with the hope that the same technology, embedded in exported Chinese vehicles, can then conquer the United States. To do so, Baidu has compiled a list of cooperative partners, a consortium of 50+ public and private entities, and named it Apollo, after NASA's massive Apollo moon-landing program. 

Project Apollo

The program is making its autonomous car software open source in the same way that Google released its Android operating system for smartphones. By encouraging companies to build upon the system and share their results, it hopes to overtake rivals such as Google/Waymo, Tencent, Alibaba and others researching self-driving technology. 

MIT Technology Review provided a description of the open source Apollo project:

The Apollo platform consists of a core software stack, a number of cloud services, and self-driving vehicle hardware such as GPS, cameras, lidar, and radar.

The software currently available to outside developers is relatively simple: it can record the behavior of a car being driven by a person and then play that back in autonomous mode. This November, the company plans to release perception capabilities that will allow Apollo cars to identify objects in their vicinity. This will be followed by planning and localization capabilities, and a driver interface.

The cloud services being developed by Baidu include mapping services, a simulation platform, a security framework, and Baidu’s DuerOS voice-interface technology.

Members of the project include Chinese automakers Chery, Dongfeng Motor, Foton, Nio, Yiqi and FAW Group. Tier 1 members include Continental, Bosch, Intel, Nvidia, Microsoft and Velodyne. Other partners include Chinese universities, governmental agencies, Autonomous Stuff, TomTom, Grab and Ford. The full list of members can be seen here.

Quoting from Bloomberg News regarding the business aspect of Project Apollo:

China has set a goal for 10 to 20 percent of vehicles to be highly autonomous by 2025, and for 10 percent of cars to be fully self-driving in 2030. Didi Chuxing, the ride-sharing app that beat Uber in China, is working on its own product, as are several local automakers. It’s too early to tell which will ultimately succeed though Baidu’s partnership approach is sound, said Marie Sun, an analyst with Morningstar Investment Service.

“This type of technology needs cooperation between software and hardware from auto-manufacturers so it’s not just Baidu that can lead this,” she said. If Baidu spins off the car unit, “in the longer term, Baidu should maintain a major shareholder position so they can lead the growth of the business.”

Baidu and Apollo have a significant advantage over Google's Waymo: Baidu has a presence in the United States, whereas Alphabet has none in China because Google closed down its search site in 2010 rather than give in to China's internet censorship.

Strategic Issue

According to the Financial Times, “autonomous vehicles pose an existential threat [to global car manufacturers]. Instead of owning cars, consumers in the driverless age will simply summon a robotic transportation service to their door. One venture capitalist says auto executives have come to him saying they know they are “screwed”, but just want to know when it will happen.” 

This desperation has prompted a string of big acquisitions and joint ventures amongst competing providers including those in China. Citing just a few:

• Last year GM paid $1bn for Cruise, a self-driving car start-up.
• Uber paid $680m for Otto, an autonomous trucking company that was less than a year old.
• In March, Intel spent $15bn to buy Israel’s Mobileye, which makes self-driving sensors and software.
• Baidu acquired Raven Tech, an Amazon Echo competitor; 8i, an augmented reality hologram startup; Kitt, a conversational language engine; and XPerception, a vision systems developer.
• Tencent invested in mapping provider Here and acquired 5% of Tesla.
• Alibaba announced that it is partnering with Chinese Big 4 carmaker SAIC in their self-driving effort.

China Network

Baidu’s research team in Silicon Valley is pivotal to their goals. Baidu was one of the first of the Chinese companies to set up in Silicon Valley, initially to tap into SV's talent pool. Today it is the center of a “China network” of almost three dozen firms, through investments, acquisitions and partnerships. 

Baidu is rapidly moving forward from the SV center: 

• It formed a self-driving car sub-unit in April which now employs more than 100 researchers and engineers. 
• It partnered with chipmaker Nvidia.
• It acquired vision systems startup XPerception.
• It has begun testing its autonomous vehicles in China and California. 

Regarding XPerception, Gartner research analyst Michael Ramsey said in a CNBC interview:

“XPerception has expertise in processing and identifying images, an important part of the sensing for autonomous vehicles. The purchase may help push Baidu closer to the leaders, but it is just one piece.”

XPerception is just one of many Baidu puzzle pieces intended to bring talent and intellectual property to the Apollo project. It acquired Raven Tech and Kitt AI to gain conversational transaction processing. It acquired 8i, an augmented reality hologram startup, to add AR — which many expect to be crucial in future cars — to the project. And it suggested that the acquisition spree will continue as needed.

Bottom Line

China has set a goal for 10 to 20 percent of vehicles to be highly autonomous by 2025, and for 10 percent of cars to be fully self-driving in 2030 and Baidu wants to provide the technology to get those vehicles on the roads in China with the hope that the same technology, embedded in exported Chinese vehicles, can then conquer the United States. It seems well poised to do so.

In a surprise move which shook Baidu’s stock, Andrew Ng, Baidu’s Chief Scientist and partner with Baidu’s founder Robin Li Yanhong in expanding Baidu’s AI activities into machine learning, driverless vehicles, and to power AI usage in advertising, maps, takeout delivery, and voice-activated search, resigned.

Baidu’s AI group has expanded to over 1,300 people in China and Silicon Valley. Ng, who has been with Baidu since 2014 oversaw most of that change.

Some see Ng’s departure as a setback to their AI efforts, hence the shakeup in the stock price. Others comment that the timing was right both for him and for Baidu.

Ng blogged about his resignation that:

I will be resigning from Baidu, where I have been leading the company’s AI Group. Baidu’s AI is incredibly strong, and the team is stacked up and down with talent; I am confident AI at Baidu will continue to flourish. After Baidu, I am excited to continue working toward the AI transformation of our society and the use of AI to make life better for everyone.

In January, Lu Qi, an AI exec from Microsoft, was hired as COO which included oversight of Baidu’s AI research and business. Today he announced Ng’s replacement as head of AI Group to be Wang Haifeng, also an AI expert, and previous president of the Association for Computational Linguistics, an international scientific and professional society for people working on computational problems involving human language.

One analyst, Kitty Fok, from IDC, a provider of research, consulting and events for the data and telecom industries, said of Ng’s choice to leave Baidu:

He wants to start his own company. Ng saw a golden opportunity to become an entrepreneur. It’s perfect timing for him because he has the expertise, he’s well known in his field, and interest is high for innovative tech start-ups. I wouldn’t be surprised if Baidu, Tencent Holdings and Alibaba Group would be interested in investing in Ng’s potential new AI enterprise.

The MIT Technology Review’s annual list of 35 Innovators Under 35 aims to illustrate the most important emerging technologies of the moment. Released this August, the 2015 list features a number of robotics and AI visionaries. Check them out.

Lars Blackmore, Visionary, 34: SpaceX engineer, working on reusable rockets that could be flown back to Earth in reverse.

Yunji Chen, Inventor, 32: designing dedicated deep-learning processors, optimized “to compute the basic blocks of machine learning.”

Adam Coates, Visionary, 34: designing artificial intelligence for Chinese search company Baidu, to make the Internet more useful to millions.

Canan Dagdeviren, Inventor, 30: working on flexible sensors and batteries for a new class of medical device.

Travis Deyle, Inventor, 32: builder of robots that can be powered wirelessly. Now at Google X working on tech to improve health care.

You may remember our Robots Podcast interview with Travis about his research on Finding objects with RFID.

Rikky Muller, Entrepreneur, 34: designing the implantable hardware intended to interact directly with the brain and help treat mental disorders.

Jaime Shotton, Inventor, 34: computer visionary at Microsoft Research. Giving computers a new way to see the world.

Ilya Sutskever, Visionary, 29: pushing the frontiers of deep-learning for the Google Brain.

You may remember the Talking Machines Podcast interview with Ilya about Machine Learning and magical thinking.

Benjamin Tee, Inventor, 33: developing medical diagnostic and treatment technologies using a synthetic sense of touch.

Conor Walsh, Inventor, 33: working on robots that are soft, lightweight, and flexible so people can wear them to enhance their abilities.

You may remember our Robots Podcast interview with Conor’s colleague Donal Holland about their Soft Robotics Toolkit.

Melonee Wise, Entrepreneur, 33: Fetch Robotics CEO wants affordable robots for the warehouse and beyond.

Check out our coverage of Melonee and Fetch Robotics on Robohub.

Credit: Illustration by Magoz; Color portraits by Matthew Hollister; black-and-white portraits by Ping Zhu. Source: MIT Technology Review.

Earlier this week Baidu announced they will be collaborating with BMW to launch an autonomous vehicle prototype later this year.

Here’s a roundup of news stories in the field of robocars.

Google begins PR campaign and talks about accidents

As the world’s most famous company, Google doesn’t need to seek press and the Chauffeur project has kept fairly quiet, but it just opened a new web site that will feature monthly reports on the status of the project. The first report gives details of all the accidents in the project’s history, which I’ve discussed previously. A new one just took place in the last month, but like the others, it did not involve the self-driving software. Google’s cars continue to not cause any accidents, though they have been at the receiving end of a modestly high number of impacts, perhaps because they are a bit unusual.

The zero at-fault accident number is both impressive, and possibly involves a bit of luck. Perhaps it even raises unrealistic expectations of perfection, because I believe there will be at-fault accidents in the future for both Google and other teams. Most teams, when they were first building their vehicles, had minor accidents where cars hit curbs or obstacles on test tracks, but the track records of almost all teams since then are surprisingly good. One way that’s not luck, of course, is the presence of safety drivers ready to take the controls if something goes wrong. They are trained and experienced, though some day, being human, some of them will make a mistake.

Baidu to build a prototype

In November I gave a “Big Talk” for Baidu in Beijing on cars. Perhaps there is something about search engines because they have made announcements about their own project. Like Google, Baidu has expertise in mapping and various AI techniques, including the advice of Andrew Ng, whose career holds many parallels to that of Sebastian Thrun, who started Google’s project. (Though based on my brief conversations with Andrew I don’t think he’s directly involved.)

Virginia opens test roads

The state of Virginia has designated 70 miles of roads for robocar testing. That’s a good start for testing by those working in that state, but it skirts what to me is a dangerous idea — the thought that there would be “special” roads for robocars designated by states or road authorities. The fantastic lesson of the DARPA Grand Challenges was the idea that the infrastructure remains stupid and the car becomes smart, so that the car can go anywhere once its builders are satisfied it can handle that road. So it’s OK to test on a limited set of roads but it’s also vital to test in as many situations as you can, so you need to get off that set of roads as soon as you can.

Zoox startup un-stealthed

Zoox is probably the first funded startup working on a real, fully automated robocar. They were recently funded by DFJ ventures and set up shop in rented space at the SLAC linear accelerator lab. Zoox was begun by Tim Kentley-Klay, a designer and entrepreneur from Australia, and he later joined forces with Jesse Levinson, a top researcher from Stanford’s self-driving car projects.

I’ve known about Zoox since it begain and had many discussions. They first got some attention a while back with Tim’s designs, which are quite different from typical car designs, and presume a fully functional robocar — the designs feature no controls for the humans, and don’t even have a windshield to see forward in some cases. (Indeed, they don’t have a “forward” since an essential part of the design is to be symmetrical and move equally well in both directions, avoiding the need for some twists and turns.) I like many elements of the Zoox vision, though in fact I think it is even more ambitious than Google’s, at least from a car design standpoint, which is quite audacious in a world where most of the players think Google is going too far.

You can see details in this report on Zoox from IEEE. I haven’t reported on Zoox under FrieNDA courtesy — in fact the early consultations with “Singularity University” described in the article are actually discussions with me.

Zoox is not the first small startup. Kyle Haight’s “Cruise” has been at it a while aiming at a much less ambitious supervised product, and truck platooning company Peleton has even simpler goals, but expect to see more startups enter the fray and fight with the big boys in the year to come.

Mercedes E Class

Speaking of supervised cruising, the report is that the 2016 Mercedes E Class will offer highway speed cruising in the USA. This has been on offer in Europe in the past. As I wrote earlier, I am less enthused about supervised cruising products and think they will not do tremendously well. Tesla’s update to offer the same in their cars will probably get the most attention.

Non-Stories

The press continue to get super excited about things that aren’t real. In spite of many reports, Uber does not yet have a car cruising the streets of Pittsburgh, though there is reality to the report that Uber has “poached” a large fraction of the robotics research crew from CMU.

In addition, many stories reported that Tesla had “solved” the liability problem of robocars through the design of their lane change system. In their system (and in several other discussed designs — they did not come up with this) the car won’t change lanes until the human signals it is OK to do so, usually by something like hitting the turn signal indicator. The Tesla plan is for a supervised car, and in a supervised car all liability is already supposed to go to the human supervisor.

Changing lanes safely is surprisingly challenging, because there is always the chance somebody is zooming up behind you at a rather rapid rate of speed. That’s common merging into a carpool lane, or on German autobahn trips. Most supervised cars have only forward sensing, but to change lanes safely you need to notice a car coming up fast from behind you, and you need to see it quite a distance away. This requires special sensors, such as rear radars, which most cars don’t have. So the solution of having the human check the mirrors works well for now.

More and more stories keep getting excited by “connected car” technology, in particular V2V communications using DSRC. They even write that these technologies are essential for robocars, and it gets scary when people like the transportation secretary say this. I wish the press covering this would take the simple step of asking the top teams who are working on robocars whether they plan to depend on, or even make early use of vehicle to vehicle communications. They will find out the answers will range form “no, not really” to a few vague instances of “yes, someday” from car companies who made corporate support commitments to V2V. The engineers don’t actually think they will find the technology crucial. The fact that the people actually building robocars have only a mild interest, if any, in V2V, while the people who staked their careers on V2V insist it’s essential, should maybe suggest to the press that the truth is not quite what they are told.

This article originally appeared on robocars.com.

Source: Stanford University  

In episode twelve we talk with Andrew Ng, Chief Scientist at Baidu, about how speech recognition is going to explode the way we use mobile devices and his approach to working on the problem.

We also discuss why we need to prepare for the economic impacts of machine learning. We’re introduced to Random Features for Large-Scale Kernel Machines, and talk about how using this twist on the Kernel trick can help you dig into big data. Plus, we take a listener question about the size of computing power in machine learning.