China’s not just a copycat economy anymore; it has turned into a high-speed innovator. So says Ben Joffe, general partner of HAX, a five-year-old hardware accelerator and investor.
And the rest of the world had better watch out.
We call what China is doing “Xiaomization,” because smart-phone giant Xiaomi’s high-speed commoditization of product categories is driving a lot of people out of business. Right now, he says, Xiaomi has invested in 77 companies—and four are unicorns, meaning they have a market capitalization of over $1 billion.
Xiaomization, he says, knocked Fitbit out of the Chinese market when Xiaomi launched a $13 activity tracker. And no product category is safe.
“The advantage of China is not cost,” Joffe says. “It is speed. Everything works at startup speed. You will get a message from the supplier Sunday night telling you that they can ship your component in morning.”
It’s also becoming a research mecca, Joffe said, with top universities and companies from around the world starting research centers in China. And, he says, this year China will overtake Japan in terms of numbers of patents filed, making it second only to the United States.
There’s plenty of startup funding in China as well, Joffe indicated. “Currently, there is an overflow of funding,” he said, “particularly angel funding.” First round funding, he pointed out, tends to be larger than funding for comparable ventures in the United States, because, he said, China believes you have to win a market quickly.
“China today,” says Joffee, “is like Japan in the 1980s: incredibly creative and incredibly fast.”
As for particular technologies, he indicated, voice control is booming—as is virtual reality, with thousands of VR arcades introducing people to the technology. Rental ventures are booming, with, he said, some companies introducing rental bikes that don’t need to be docked at a specific station, others are renting umbrellas, batteries, and even basketballs.
I’m sitting in a rented Ford Transit van driving down El Camino Real in Palo Alto. The driver, Marco Della Torre, suddenly floors the gas pedal. And nothing happens—the car just keeps smoothly rolling along, just under the speed limit.
That’s because, just before we rolled out onto the road, Della Torre set an internal speed limit on the car. He also adjusted idle settings and shift points to make the car’s operation more fuel efficient. All that took him a couple of minutes, sitting in the passenger seat, with a gadget plugged into the van’s on-board diagnostics port. After making the adjustments, he unplugged the gadget and put it away.
Now you wouldn’t normally limit a car’s speed to under 35 miles an hour—that was just for this demo. But you might want to set a more reasonable limit, to prevent speeding on freeways. Or adjust rates of acceleration to make a driver use a car more gently.
The gadget Della Torre used in the demo was the Derive Systems X3. It can customize a car’s performance, adjusting idle speed, shift points, and torque and set speed limits. The company has been around since 2003, selling earlier versions of its device to car enthusiasts, who generally used it to make cars drive faster and more responsively.
Then, says Derive vice president Tom Kanewske, one of those car enthusiasts contacted the company, and said, “I get that you can turn a vehicle’s performance up, but I’m also a fleet manager, I’m interested in turning a bunch of vehicles down, can you do that, too?” That question set Derive on a path to developing an easy to use device to allow fleet managers to choose various performance parameters designed to make the vehicles last longer by mitigating harsh driving. It’s now being used on some 1.7 million vehicles.
The company’s secret sauce, Derive CTO Della Torre says, is its ability to unlock the engine control module. In some cases, Derive engineers had to figure out the “key,” but increasingly the company has developed partnerships with car manufacturers. A company spokesman says the technology works with all vehicles manufactured since 1996, but the company specializes in connecting to vehicles manufactured by GM, Ford, and a handful of non-U.S. companies.
The company is gathering data to improve its algorithms and customize settings for local conditions, accounting, say, for altitude and temperature, and create various bundles of settings for different uses.
Which brings us to that teen driver. Says Kanewske, “A parent with a teen driver probably doesn’t want a high degree of electronic throttle response,” that is, a fast acceleration when the gas pedal is suddenly depressed. “Or the ability to drive at high speeds.” The company isn’t marketing to these parents yet—and its fleet device looks industrial, and is only priced as a monthly subscription.
But, says Kanewske, a more consumer-friendly product is in the works. He won’t show me anything yet, but says, “We will be at CES in January.”
Executives at HAX, the five-year-old hardware accelerator and seed funder, know a lot about hardware. They’re getting ready to release a detailed analysis about hardware trends, and last week informally previewed some of their insights, expectations, and lessons learned. It was a bit of a drink-from-a-firehose experience. In five years, the group has learned a lot, and the HAX executives all seemed to want to say a lot more than they could cram into their time slots. Some takeaways:
On the consumer Internet of Things:
“Three years ago, the theory was people would buy families of products to link together in homes, possibly under one brand,” said HAX program director Kate Whitcomb. “You would enter through your smart door, the lights would turn on, the music adjust.”
That theory it turns out, was completely wrong.
“We are not seeing that,” Whitcomb indicated. “Consumers are not buying products as suites. Consumers buy individual products for a single purpose, and if they work together, do so through voice.”
That, said HAX general partner Duncan Turner, has made “a lot of investments in smart home look dumb until recently,” at least investments in those companies trying to market the gadgets directly to consumers.
Smart home investments do make sense for utility companies to help them run the grid, he said: Nest users, for example, are being paid $30 to $50 per year by some utility companies to allow them to level load on grid.
And, as general partner Ben Joffe points out, consumer IoT gadgets have turned out to be attractive to insurance companies, with home, car, and health insurance providers offering discounts tied to the use of specific connected products. And in the case of the Beam smart toothbrush, he said, the hardware maker is itself turning into an insurance company.
On the consumer health business:
Consumer gadgets, said Turner, are turning out to be potential Trojan Horses, getting into people’s lives and then collecting all sorts of data that will revolutionize healthcare in the future. Nura, for example, is marketing a set of headphones that measures characteristics of a user’s hearing for purposes of customization, and can also gather information of how hearing changes over time. That’s high value data, Turner says. Another headphone company gathers data about how well a person concentrates at different times. Combined, that could be used to build an interesting data set. Other companies are doing the same thing, but with sleep data. He indicated, sleep technology is going to be a huge market, as are various approaches to back care.
Getting the rights to use that data, however, is going to be tough, Turner said. “People don’t want to donate data. Do you donate organs when you die? Then you should donate your data, to help us be healthier in future.”
On other emerging gadget trends:
Sports tech companies that do real time coaching are going to be huge, said Joffe. Aftermarket personalization is becoming the new normal, he indicated, pointing to the Revols earphones that custom fit to individual ears as an example. The second wave of smart glasses, which will take a more pragmatic approach and be more successful, is imminent, Joffe says.
And personal mobility devices will be huge, he said. “Hoverboards that catch fire? That was so last year.” The next boom will involve Ninebot (a two-wheeled mini Segway), electric single-wheel transporters, and electric skateboards. “These aren’t jetpacks; they are things we will really use,” he said.
HAX sees huge opportunities in industrial agriculture, as new sensing devices are implemented to improve efficiencies. For home agriculture, Turner said, the opportunities are limited at best. The only companies he’s seen to date that have created successful products for home agriculture are either involved in farming insects for protein (Livin Farms), or growing weed (Grobo). “The cannabis area is the only one we think is high value enough to get this technology into the home,” Turner said.
On the future of manufacturing:
Manufacturing has been going to China, said Turner, but people have been wondering where it will go next. “The answer,” he said, “is nowhere, because robots are coming in to take over these manufacturing processes.” He pointed out that China, Europe, and Japan are investing heavily in robots for manufacturing, and the United States and Britain are falling behind.
On the Maker movement:
The gap is widening between makers and startups, said Joffe. “Maker Faire used to be the place for hardware startups to show innovation,” he said. “Now it is CES.”
On how to deal with hardware copycats:
“Software is your best protection,” says Joffe. “When the intelligence is in the software, it’s hard to copy. Patents can help, but for a young startup, they are hard to defend.”
On big failures:
Hardware companies don’t always succeed. Whitcomb pointed to Lily Robotics, Pebble, Hello Sense, and Scully as prominent failures. “Those explosions affect the whole marketplace, and hurt other startups,” she said. “But the reality is most products do ship, and explosions are few and far between.”
An ordinary smart meter gives your local utility useful information about how much energy you are using—every hour, or even as often as every minute. This helps utility planners efficiently adjust electricity generation to meet demand or encourage reductions in demand when necessary.
But machine learning systems, looking at that data, can tell something else about your home besides its energy use—they can tell if you are home, or if you are not. That’s what University of California at Berkeley researchers Ming Jin, Ruoxi Jia, and Costas Spanos found out. That information, Jin says, is also useful for utilities—they can call or show up to perform necessary maintenance when you are home, and not waste personnel time trying to reach you.
But they aren’t the only ones who can access this information, given the data is transmitted wirelessly, and isn’t necessarily encrypted at every stage of its journey.
“If you know a person is home, as an advertiser, you can make a phone call. If you know a person isn’t home, that information could be used for home intrusion or other bad activities,” Jin says.
In a recent paper, Jin and his colleagues demonstrated that machine learning systems can be trained to detect occupancy without any initial information from a home owner. “You just need a smart meter that listens over time,” he says, “as well as the basic assumption that different types of buildings have different occupancy patterns, for example, commercial buildings are typically occupied during the day and not the night and homes are the opposite.” Using this assumption, the machine learning algorithms were able to tease out more detailed characteristics about power consumption when a home is occupied; they then are able to tell when someone is home or not, even when that person’s patterns are outside the norm.
How to keep occupancy data private and still provide the information utilities need to manage their grids is the next area of research, Jin says. “Right now, meters are sending accurate information about energy consumption. To protect privacy, you could add some noise to that data. We are now looking to determine the optimal size of the added noise that would mask information about occupancy and still give the utility company an accurate enough reading for its needs.”
Who needs fireworks when you’ve got drones? Or event tickets when you’ve got virtual reality?
That’s Intel’s message as it prepares to bring technology to the 2018 Winter Olympics and future Olympic games.
The company today announced that it had joined the Olympics partner program as a major sponsor through 2024. No dollar figures were mentioned at the press event, held in New York City and via web conference, however, the rumor mill has been pegging the deal at nine figures, or somewhere over $100 million.
Intel was far more specific about the technologies it plans to deploy for the Olympics—drones, virtual reality, 5G communications, and artificial intelligence. Intel CEO Brian Krzanich suggested that Intel is also working with the Olympic committee to develop new training technology, but didn’t give details. Krzanich was joined by International Olympic Committee President Thomas Bach, who is clearly concerned about bringing young viewers to the games.
“Sports has to go where the people are,” he said, “and many people are leading a digital life.” Technology, he continued, “has a huge potential to connect the games with the young generation.”
Drones, according to Intel CEO Krzanich, will have two roles at the Olympics—entertainment, in the form of light shows, and to carry cameras for broadcast and other purposes. The ultralight entertainment drones, he indicated, will swarm the skies, acting as a safe and “more creative” replacement for traditional fireworks. These drones are so safe, he says, Intel staff members have launched a hundred at a time and purposely run into them. The heavier, camera-carrying drones, used to “measure and observe” athletes, will use obstacle avoidance technology still under development, Krzanich indicated.
On the VR front, Krzanich promised to bring two recently unveiled technologies to the 2018 Olympics. The company will stream 16 live and 16 on-demand events using the its True VR technology, which made its debut with the 2017 NCAA basketball playoffs. It will also showcase its 360-degree replay technology that recreates moments in events from the point of view of specific players, first used at the 2017 NFL Super Bowl.
As for 5G, Intel vice president Asha Keddy, along with the company’s 5G development team and Olympic three-time gold medalist Kerri Walsh Jennings, pushed a symbolic button to turn on Intel’s 5G test network in Silicon Valley, and promised a 5G network would be running throughout the venues of the 2018 Winter Olympics. That part of the announcement was live-streamed using the technology.
Artificial intelligence will, Krzanich expects, enable more detailed analysis and comparisons of player performances.
And going beyond the company’s current eight-year sponsorship deal, Krzanich said, Intel expects to have new technologies that are Olympic contenders, including more AI, deeper virtual experiences, and new roles for drones and autonomous vehicles.
The Silicon Valley Business Journal annually publishes a list of the tech companies who are the biggest local employers. In recent years, Apple and Google (now Alphabet) have vied for the number one spot, with Cisco holding a lock on number three. That hasn’t changed. But there have been wild swings in headcount among those on the list.
Looking at the 20 largest tech employers in Silicon Valley, the overall workforce as reported by the Business Journal ranges from 25,000 at Apple to 2789 at Symantec. But what a difference a year makes. Since the Business Journal’s 2016 report, Apple hired 5000, Tesla Motors hired 3471 (for a total local workforce of 10,000), Facebook hired 2586 (for a total of 9385), and Gilead Sciences hired 1719 (for a total of 6949).
Among those companies shedding staff, eBay led the list, losing 3222 employees (for a total of 2978), followed by Intel (minus 3000 for a total of 7801), and Yahoo (minus 193 for a total of 3800).
Overall, headcount gains among the top 20 far exceeded losses, with a total of 16,604 new employees at those tech firms with a growing Silicon Valley presence, compared with 3299 fewer employees among those companies making cutbacks.
(Note: Western Digital was on the list at number 18 this year, and not on previous years, having consolidated operations to its San Jose office. The Business Journal reported the company had 3000 local employees in 2017; it did not make the 2016 list, and the consolidation makes comparing annual totals complicated, so I didn’t include it in this discussion.)
Robots that sketch, play ping pong, solve mazes, and attempt to juggle strutted their stuff at the annual demo day for Stanford’s Experimental Robotics class. Each year, Professor Oussama Khatib’s students aim to teach a selection of industrial robots some new skills. The toughest project: teaching a Kuka robot to juggle. (It struggled, with balls getting stuck or flying wild… but as anyone who has tried to juggle objects can tell you, the learning curve is very steep.) The other projects included two robots that had been taught to draw (a Sawyer and a Puma), a Ping Pong–playing robot (the Kuka again) that scored a few points against its human opponents, a cowboy hat–wearing Sawyer robot that shot at a moving target, a Puma 500 robot that manipulated a maze to send a ball along the correct path, and a drone-loading Sawyer robot that tracked a less-than-stable hovering drone. Check them all out in the video below.
What could your computer, phone, or other gadget do differently if it knew how you were feeling?
Rana el Kaliouby, founder and CEO of Affectiva, is considering the possibilities of such a world. Speaking at the Computer History Museum last week, el Kaliouby said that she has been working to teach computers to read human faces since 2000 as a PhD student at Cambridge University.
“I remember being stressed,” she says. “I had a paper deadline, and “Clippy” [that’s Microsoft’s ill-fated computer assistant] would pop up and do a little twirl and say ‘It looks like you are writing a letter.’ I would think, ‘No I’m not!’”
(“You may,” Computer History Museum CEO John Hollar interjected, “be one of the few advanced scientists inspired by Clippy.”)
That was a piece of what led her to think about making computers more intelligent. Well, that, plus the fact that she was homesick. And the realization that, because she was spending more time with her computer than any human being, she really wanted her computer to understand her better.
Since then, she’s been using machine learning, and more recently deep learning, to teach computers to read faces, spinning Affectiva out of the MIT Media Lab in 2009 to commercialize her work. The company’s early customers are not exactly changing the world—they are mostly advertisers looking to better craft their messages. But that, she says, is just the beginning. Soon, she says, “all of our devices will have emotional intelligence”—not just our phones, but “our refrigerators, our cars.”
Early on, el Kaliouby focused on building smart tools for individuals with autism. She still thinks emotional intelligence technology—or EI—will be a huge boon to this community, potentially providing a sort of emotional hearing aid.
It’ll also be a mental healthcare aid, el Kaliouby predicts. She sees smart phones with EI as potentially able to regularly check a person’s mental state, providing early warning of depression, anxiety, or other problems. “People check their phones 15 times an hour. That’s a chance to understand that you are deviating from your baseline.”
Cars, she said, will need to have emotional intelligence as they transition to being fully automated; in the interim period, they will sometimes need to hand control back to a human driver, and need to know if the driver is ready to take control.
Smart assistants like Siri and Alexa, she says, “need to know when [they] gave you the wrong answer and you are annoyed, and say ‘I’m sorry.’”
Online education desperately needs emotional intelligence, she indicated, to give it a sense of when students are confused or engaged or frustrated or bored.
And the killer app? It just might be dating. “We have worked with teenagers who just want to have a girlfriend, but couldn’t tell if girls were interested in them,” el Kaliouby says. A little computer help reading their expressions could help with that. (Pornography and sex robots will likely be a big market as well, el Kaliouby says, but her company doesn’t plan on developing tools for this application. Nor for security, because that violates Affectiva’s policy of not tracking emotions without consent.)
While Affectiva is focusing on the face for its clues about emotions, el Kaliouby admits that the face is just part of the puzzle—gestures, tone of voice, and other factors need to be considered before computers can be completely accurate in decoding emotions.
And today’s emotional intelligence systems are still pretty dumb. “I liken the state of the technology to a toddler, el Kaliouby says. “It can do basic emotions. But what do people look like when inspired, or jealous, or proud? I think this technology can answer these basic science questions—we’re not done.”
The full recording of el Kaliouby’s talk is below.
Twenty years ago, at the Sutter Maternity Center in Santa Cruz, Calif., while his wife was in labor, Philippe Kahn hacked together a Motorola StarTAC flip phone, a Casio QV digital camera that took 320 by 240 pixel images, and a Toshiba 430CDT laptop computer. When he took a picture with the camera, the system would automatically dial up his Web server and upload the picture to it at 1200 baud. The server would send email alerts to a list of friends and family, who could then log on and view the photo.
It wasn’t a brand new concept for Kahn; he’d spent about a year working on a Web-based infrastructure that he called Picture Mail. Picture Mail would do what we now call “sharing”—that is, one user would upload a photo and text, designated as something to share with a particular list of contacts (say, “friends,” “family,” or “colleagues”). The system would send email notifications to everyone at that list, directing them to visit the host Web page to view the picture. Kahn says he was aiming to be the Polaroid of the 21st century, providing “Instant Picture Mail” that would be a digital update of Polaroid’s vision of the instant camera.
What he hadn’t gotten around to building was the consumer hardware piece of the puzzle. Photography wasn’t going to be instant if you had to hook your camera up to your computer and go to a particular website every time you took a picture.
“I had always wanted to have this all working in time to share my daughter’s birth photo,” Kahn recalls, “but I wasn’t sure I was going to make it.”
Thanks to his wife spending 18 hours in labor at the local maternity center, he had a little time to build the prototype. He realized he had most of what he needed with him—in particular, the phone’s car kit, including a plug that allowed the phone to connect to a car speaker system. For the rest of what he needed, he asked an assistant to make a run to Radio Shack and drop off the additional gear at the hospital.
“It’s always the case that if it weren’t for the last minute, nothing would ever get done,” Kahn says.
Kahn got it working before the baby came, and 11 June 1997 has gone down in history as the birth of a whole new world.
Some call this milestone the beginning of the camera phone. It’s not exactly that; Kahn acknowledges that others had put photo sensors in phones before. And it’s also not the first time someone sent someone else a digital photo on the Internet. But it was the first time that a photo went from one person to a broad list of his friends and family members instantly, with just a touch of a button. Kahn now calls the milestone Instant Share, and points out that this is the way social media still works today—you upload an image once to a site that stores it, and then notifications are broadcast and people follow a link back to the stored image.
Today, of course, instant sharing of photos—evolving to videos—is everywhere. It’s the idea behind Snapchat, Instagram, and Facebook Live. It has changed the way we connect with our friends and the world, and changed the way we experience things. For many, it’s hard to put the phone down and watch something interesting without sharing an image. Camera phones have even spawned dystopian visions of a world in which everything is shared, as in “The Circle.”
All this, looking back, seemed to grow organically. But, according to Kahn, that wasn’t exactly the case. He had to do a lot of plowing to prepare the soil, to extend the metaphor.
“After the baby,” he says, “I spent the next month integrating the design, using a microcontroller, a CMOS sensor, and a phone.” In early 1998, he founded a company around the technology, Lightsurf, and eventually received a handful of patents on the work, he recalls.
He took the technology, he says, “to Kodak, Polaroid, and [other camera companies]; they all had wireless camera projects, but none of them could imagine that the future was digital photography inside the phone, with Instant-Picture-Mail software and service infrastructure. They collectively came to the conclusion that phones would be focused on voice—this was before texting—and that cameras would become wireless.”
Having struck out in the U.S., Kahn moved on to pitch Japanese companies. He had no luck with dominant mobile phone service provider Docomo, but found enthusiasm at J-Phone. J-Phone, he says, then brought in Sharp to design their “Sha-Mail” (translated as “Picture-Mail”) phone, and the product was a success.
Back in the U.S., Wired magazine covered Kahn and LightSurf, prompting Sprint to contact him; Sprint worked with LightSurf and Casio to launch the first U.S. camera phone in 2002.
Even from the early days, Kahn says, he had a sense that instant photo sharing really was going to change the world. “Citizen journalism immediately came to mind; we were documenting the birth of my daughter, but that was just the beginning.” He believed that other, more political events would be documented, “and it has happened. People can’t hide things anymore. There is always someone with a camera phone taking a video; people can’t just claim that something didn’t happen.”
Bob Parks, who interviewed Kahn for the Wired article in 2000, confirms Kahn’s prescience. Parks says: “He was telling me things like, ‘In the future people will document crimes using video on their phones. Then everyone will know the real story.’ At the time I was skeptical. I thought, ‘OK, guy, I guess we'll see how that works out.’”
For Kahn personally, the invention worked out quite well: LightSurf was acquired by Verisign in 2005 for approximately $270 million, the intellectual property scattered in later sales and, Kahn said, was tussled over in courts. Kahn is no longer involved with the technology—he has a new startup, FullPower Technologies, that has developed under-the-mattress sensors and cloud based artificial intelligence to gather data and personalize recommendations to help customers improve their sleep. But he’s thrilled watching phone-based photo sharing explode around the world.
“If you go to Africa, people don’t have laptops. They have phones with cameras and they do everything with them—sell things, buy things, telemedicine. If a person’s house burns down these days, their pictures aren’t lost, their memories are stored in the cloud. I see tourists with selfie-sticks and I think it’s fantastic, the more cameras the better. It’s a fantastic power to be in the hands of Mr. and Mrs. Everyone.”
And that rush to cobble together a prototype in the maternity room? Absolutely worth it, Kahn says: “The picture of my daughter’s birth was a magical, unique, instant moment and worth a million words.”
(Kahn narrates a reenactment of the birth in the video below; the building of the prototype starts at 1:35.)
This season, on HBO’s “Silicon Valley,” fictional character Richard Hendricks set off on a new venture—reinventing the Internet into a decentralized network. The vision, to create a peer-to-peer Internet that is free from firewalls, government regulation, and spying, is one shared by the Decentralized Web movement. It isn’t exactly a new idea. In the real world, the Decentralized Web movement has been working for a couple of years to link people interested in advancing the effort, and pieces of the technology are being developed in various corporate and university labs. Making a true decentralized Web—or decentralized Internet (the two are a little different)—isn’t going to be fast or easy, Decentralized Web evangelist and Internet Archive founder Brewster Kahle told me last month, because, although it is a good idea, it is hard to execute.
Or maybe it is coming sooner than we think. After I wrote about HBO’s “Silicon Valley” joining the Decentralized Web movement, I heard from two teams who say they are close to rolling out a version of the technology very similar to that described on the show. However, their interpretation of what’s described on the show is somewhat different.