Pebblebee, makers of Finder smart tracking device, find a big investor as part of effort to raise $10M

Pebblebee, makers of Finder smart tracking device, find a big investor as part of effort to raise $10M

12:54pm, 2nd April, 2019
The PebbleBee BlackCard is a new credit-card-thin tracking device that can help locate a lost wallet or anything else. (Pebblebee Photo) , the Bellevue, Wash.-based startup that makes a smart tracker to help people find missing keys and more, has found an investor. The company, founded by engineers Daniel Daoura and Nick Pearson-Franks, has landed a “substantial investment” from , a division of the massive Japanese wireless carrier KDDI Corp. The amount, which was not disclosed on Tuesday, contributes to what Daoura called an “ongoing $10 million funding round.” Soracom is a global provider of smart IoT connectivity, offering cloud-native wireless service designed specifically for the needs of connected devices. The company previously invested $5 million in Seattle-based balena.io (). Pebblebee has been making moves toward growing its brand and reach since last fall when it landed the Finder tracking device across the U.S. Daoura told GeekWire that the product sold really well and “proved the market” and they have expanded to Canada and other countries. He said they started entertaining the idea of looking into acquiring capital because growing the consumer brand requires hefty investment. “We got quite a bit of interest from the Bay Area as well as international VCs. Not so much local just because the nature of us being hardware and not software focused,” said Daoura, the startup’s CEO. Where’s the kid?! Pebblebee’s new BlackCard shown being tucked into a child’s jacket. (Pebblebee Photo) In the meantime, as Pebblebee aims to attract even more investors, the company isn’t slowing on development, and is releasing a new product this week called BlackCard. “It’s essentially a wallet tracker; it’s very thin — as thin as two credit cards — and it’s rechargeable,” Daoura said. The BlackCard has a range up to 500 feet — “definitely more than any other tracker out there today” — and will hold a single charge up to five months, and it emits a very loud buzzing sound. The price will be $29.99. BlackCard will launch along with a new and improved Pebblebee website on Wednesday. With eight employees, Daoura credits Pebblebee’s small team for bringing a Kickstarter vision to reality. “Their level of commitment and perseverance has been integral to our success,” he said. Soracom Americas CEO Eugene Kawamoto said in a news release that his company is passionate about identifying and supporting companies like Pebblebee. “Pebblebee’s hardware expertise and impressive patent library are already advancing the state of the art in the crucial asset tracking category,” said Kawamoto, who will take a seat on the Pebblebee board of directors. “By providing both smart connectivity and strategic investments, Soracom helps to accelerate IoT development and create a more connected world.”
‘Huge awakening’ in data privacy drives big growth for Seattle startup Integris

‘Huge awakening’ in data privacy drives big growth for Seattle startup Integris

11:29pm, 1st April, 2019
Integris CEO Kristina Bergman. (Integris Photo). Back in 2016, a Seattle startup called Integris with a modest $3 million in funding and a vision to help companies manage customer data with integrity. Fast-forward to 2019, when privacy issues are making daily headlines as politicians seek to rein in Big Tech, and business is booming for Integris. In a little over two quarters, Integris more than tripled its team to 30 full-time employees. The startup opened a second office in Vancouver, B.C. and is working with a number of Fortune 500 companies to help them implement data protection and privacy standards. Integris’ growth is driven by new laws in the U.S. and Europe that seek to crack down on tech companies that handle consumer data. The European Union is spearheading the effort with its broad General Data Protection Regulation. In the U.S., federal regulation has been sluggish as states step in to implement their own laws. Last summer, to give consumers more control over their data and dozens of other states are considering similar laws. Related: “When we started three years ago, most people couldn’t spell GDPR … but fast forward a few years and privacy is in the headlines,” said Integris co-founder Kristina Bergman. “It’s front page news in all the major publications and so the biggest thing that we’ve seen is a huge awakening among people everywhere about the impacts of privacy, the importance of privacy, and we’ve seen a lot of market maturity happen over the last few years.” Ironic as it might sound, big tech companies are . Apple and Microsoft have been actively promoting themselves as the secure, privacy-sensitive foils to their younger tech industry peers. It’s catching on. In March, Facebook by doubling down on encrypted, ephemeral messaging. But there is a growing concern in the business community about a future in which companies that handle consumer data are forced to comply with different laws in every state. “The concern is that if the federal government doesn’t step up and unify it in the way that Europe unified privacy legislation under GDPR, we’re going to end up with a privacy legislation framework in the U.S. that’s incredibly fractured, very hard to comply with, and not really feasible and implementable,” said Bergman. That fear is leading a number of tech leaders to support a federal privacy law that would pre-empt state regulations. Related: Integris surveyed 258 business executives at companies with 500 employees or more and at least $25 million in annual revenue as part of released Monday. Of those surveyed, 80 percent believe there should be a federal privacy law, though they may not be ready for it. About half of the respondents said they take inventory of the personal data they store just once a year or in response to an audit. However, 88 percent said their companies are increasing their data privacy management budgets in 2019. “What’s been a boon to the business is not the murkiness but the opportunity that privacy presents,” Bergman said. “In our discussions with companies, they’re looking at privacy increasingly as a differentiator for their business … they look at that as an opportunity to differentiate against their competition by being able to prove that they’re operating with integrity, they’re treating customer data with the utmost care, and they can prove it.” Integris’ goal is to help companies set up best practices in data privacy. The company uses machine learning and other technology to map a company’s sensitive data, apply regulatory obligations, and automate actions like encryption and deletion. On top of its initial $3 million round, last summer to amp up its regulatory compliance services.
Seattle startup ioCurrents raises $5M to bring big data to the high seas

Seattle startup ioCurrents raises $5M to bring big data to the high seas

1:16pm, 26th March, 2019
(Bernard Spragg Photo via Flickr) For , maritime data is both personal and professional. King grew up sailing in New England and is now the owner of “Northern Lights,” a vintage Coronado 41 sloop that he restored. ioCurrents CEO Cosmo King. (ioCurrents Photo) He’s also the CEO and co-founder of Seattle startup , which today announced a $5 million investment to grow its platform for collecting and analyzing real-time data for the maritime industry. The company’s platform, MarineInsight, collects reams of data from various pieces of ship machinery and analyzes it in the cloud whenever a connection is available. The software then suggests actions based on any problems it finds or anticipates; it can help reduce fuel costs or prevent engine failures, for example. The startup has customers in commercial shipping, fishing and passenger industries. King was formerly an engineer at Isilon Systems, a Seattle startup that was acquired by EMC in 2010 for $2.25 billion. He launched ioCurrents in 2015 with co-founder and CTO. “This additional investment will allow ioCurrents to build on our existing success, and provide even more value to the maritime industry as a whole,” King said . The Series A round, which brings the company’s total amount raised to $6.4 million, was led by . Imagen, a Seattle-based venture capital firm focused on data and software startups, has also invested in Seattle-area companies such as and outdoors app maker BaseMap. “ioCurrents is defining itself as the market leader in the development of real-time, predictive analytics to the maritime industry,” John Polchin, managing director of Imagen, said in a statement. “Imagen’s investment will help ioCurrents capitalize on the global demand for their solutions and accelerate the company’s pace of product innovation.”
How earthquake patterns could let us know when the ‘Really Big One’ is coming

How earthquake patterns could let us know when the ‘Really Big One’ is coming

2:05pm, 16th February, 2019
A map of coastal Washington state and British Columbia shows the sweep of an episodic tremor and slow slip event, or ETS, from February to April 2017. The colors denote the time of the event as shown on the color-coded time bar at the bottom. The gray circles on the color bar indicate the number of tremor events per day. (UNAVCO Graphic / Kathleen Hodgkinson) WASHINGTON, D.C. — Is it the tick of Earth’s heartbeat, or a ticking time bomb? Either way, a 14-month pattern in seismic activity could serve as the start of a super-early warning system for the “Really Big One,” the massive earthquake that’s expected to hit the Pacific Northwest sometime in the next few centuries. The seismic ticks are known as episodic tremor and slow slip (“ETS”) events, and . They’re linked to the titanic clash between the Juan de Fuca tectonic plate and the North American plate, in a region known as the Cascadia subduction zone. The two plates grind into each other at a rate of an inch or two per year, about 25 miles below the surface. Usually, it’s a slow grind, but every so often, there’s a sharp spike in the rate of movement. Along the Washington state coast, the spike comes roughly every 14 months. (The most recent spike .) In California, the cycle takes 10 months. In Oregon, it’s more like 24 months. Based on historical and geological records, seismologists have determined that the Cascadia fault can produce catastrophic earthquakes, on the order of magnitude 9.0 or more. In 2015, worries about the potential effects of a big Cascadia quake led to an about the . , a geophysicist at Oregon State University, isn’t saying the Really Big One is coming anytime soon. But during a presentation at this week’s annual meeting of the American Association for the Advancement of Science, she said a steadily expanding network of seismometers and strainmeter could give us advance notice. The seismic detection network in the Pacific Northwest and California allows seismologists to map the pulls exerted by ETS events in three dimensions, day by day. “When there’s a little pull, it increases the risk, the stress increases, and the probability for a great earthquake increases,” Trehu said. “But it increases from one very small number to what’s still a very small number.” Trehu said the key thing to watch for is a quickening in the pattern of episodic tremors. “Potentially changes in the pattern, changes in that periodicity, could be indicative of something interesting,” she said. “But those are going to take longer monitoring times.” Efforts are already underway to extend the seismic monitoring network offshore through the , a project backed by EarthScope and the National Science Foundation with participation by the and the .
Xnor shrinks AI to fit on a solar-powered chip, opening up big frontiers on the edge

Xnor shrinks AI to fit on a solar-powered chip, opening up big frontiers on the edge

9:50am, 13th February, 2019
Xnor.ai machine learning engineer Hessam Bagherinezhad, hardware engineer Saman Naderiparizi and co-founder Ali Farhadi show off a chip that uses solar-powered AI. (GeekWire Photo / Alan Boyle) It was a big deal two and a half years ago when researchers the size of a candy bar — and now it’s an even bigger deal for Xnor.ai to re-engineer its artificial intelligence software to fit onto a solar-powered computer chip. “To us, this is as big as when somebody invented a light bulb,” Xnor.ai’s co-founder, Ali Farhadi, said at the company’s Seattle headquarters. Like the candy-bar-sized, Raspberry Pi-powered contraption, the camera-equipped chip flashes a signal when it sees a person standing in front of it. But the chip itself isn’t the point. The point is that Xnor.ai has figured out how to blend stand-alone, solar-powered hardware and edge-based AI to turn its vision of “artificial intelligence at your fingertips” into a reality. “This is a key technology milestone, not a product,” Farhadi explained. Shrinking the hardware and power requirements for AI software should expand the range of potential applications greatly, Farhadi said. “Our homes can be way smarter than they are today. Why? Because now we can have many of these devices deployed in our houses,” he said. “It doesn’t need to be a camera. We picked a camera because we wanted to show that the most expensive algorithms can run on this device. It might be audio. … It might be a way smarter smoke detector.” Outside the home, Farhadi can imagine putting AI chips on stoplights, to detect how busy an intersection is at a given time and direct the traffic flow accordingly. AI chips could be tethered to balloons or scattered in forests, to monitor wildlife or serve as an early warning system for wildfires. Xnor’s solar-powered AI chip is light enough to be lofted into the air on a balloon for aerial monitoring. In this image, the chip is highlighted by the lamp in the background. (Xnor. ai Photo) Sophie Lebrecht, Xnor.ai’s senior vice president of strategy and operations, said the chips might even be cheap enough, and smart enough, to drop into a wildfire or disaster zone and sense where there are people who need to be rescued. “That way, you’re only deploying resources in unsafe areas if you really have to,” she said. The key to the technology is reducing the required power so that it can be supplied by a solar cell that’s no bigger than a cocktail cracker. That required innovations in software as well as hardware. “We had to basically redo a lot of things,” machine learning engineer Hessam Bagherinezhad said. Xnor.ai’s head of hardware engineering, Saman Naderiparizi, worked with his colleagues to figure out a way to fit the software onto an FPGA chip that costs a mere $2, and he says it’s possible to drive the cost down to less than a dollar by going to ASIC chips. It only takes on the order of milliwatts of power to run the chip and its mini-camera, he told GeekWire. “With technology this low power, a device running on only a coin-cell battery could be always on, detecting things every second, running for 32 years,” Naderiparizi said in a news release. That means there’d be no need to connect AI chips to a power source, replace their batteries or recharge them. And the chips would be capable of running AI algorithms on standalone devices, rather than having to communicate constantly with giant data servers via the cloud. If the devices need to pass along bits of data, they could . That edge-computing approach is likely to reduce the strain of what could turn out to be billions of AI-enabled devices. “The carbon footprint of data centers running all of those algorithms is a key issue,” Farhadi said. “And with the way AI is progressing, it will be a disastrous issue pretty soon, if we don’t think about how we’re going to power our AI algorithms. Data centers, cloud-based solutions for edge-use cases are not actually efficient ways, but other than efficiency, it’s harming our planet in a dangerous way.” Farhadi argues that cloud-based AI can’t scale as easily as edge-based AI. “Imagine when I put a camera or sensor at every intersection of this city. There is no cloud that is going to handle all that bandwidth,” he said. “Even if there were, back-of-the-envelope calculations would show that my business will go bankrupt before it sees the light of day.” The edge approach also addresses what many might see as the biggest bugaboo about having billions of AI bugs out in the world: data privacy. “I don’t want to put a camera in my daughter’s bedroom if I know that the picture’s going to end up in the cloud,” Farhadi said. Xnor.ai was , or AI2, only a couple of years ago, and the venture is with millions of dollars of financial backing from Madrona Venture Group, AI2 and other investors. Farhadi has faith that the technology Xnor.ai is currently calling “solar-powered AI” will unlock still more commercial frontiers, but he can’t predict whether the first applications will pop up in the home, on the street or off the beaten track. “It will open up so many different things, the exact same thing when the light bulb was invented: No one knew what to do with it,” he said. “The technology’s out there, and we’ll figure out the exact products.”
Xnor shrinks AI to fit on a solar-powered chip, opening big frontiers on the edge

Xnor shrinks AI to fit on a solar-powered chip, opening big frontiers on the edge

9:20am, 13th February, 2019
Xnor.ai machine learning engineer Hessam Bagherinezhad, hardware engineer Saman Naderiparizi and co-founder Ali Farhadi show off a chip that can use solar-powered AI to detect people. (GeekWire Photo / Alan Boyle) It was a big deal two and a half years ago when researchers the size of a candy bar — and now it’s an even bigger deal for Xnor.ai to re-engineer its artificial intelligence software to fit onto a solar-powered computer chip. “To us, this is as big as when somebody invented a light bulb,” Xnor.ai’s co-founder, Ali Farhadi, said at the company’s Seattle headquarters. Like the candy-bar-sized, Raspberry Pi-powered contraption, the camera-equipped chip flashes a signal when it sees a person standing in front of it. But the chip itself isn’t the point. The point is that Xnor.ai has figured out how to blend stand-alone, solar-powered hardware and edge-based AI to turn its vision of “artificial intelligence at your fingertips” into a reality. “This is a key technology milestone, not a product,” Farhadi explained. Shrinking the hardware and power requirements for AI software should expand the range of potential applications greatly, Farhadi said. “Our homes can be way smarter than they are today. Why? Because now we can have many of these devices deployed in our houses,” he said. “It doesn’t need to be a camera. We picked a camera because we wanted to show that the most expensive algorithms can run on this device. It might be audio. … It might be a way smarter smoke detector.” Outside the home, Farhadi can imagine putting AI chips on stoplights, to detect how busy an intersection is at a given time and direct the traffic flow accordingly. AI chips could be tethered to balloons or scattered in forests, to monitor wildlife or serve as an early warning system for wildfires. Xnor’s solar-powered AI chip is light enough to be lofted into the air on a balloon for aerial monitoring. In this image, the chip is highlighted by the lamp in the background. (Xnor. ai Photo) Sophie Lebrecht, Xnor.ai’s senior vice president of strategy and operations, said the chips might even be cheap enough, and smart enough, to drop into a wildfire or disaster zone and sense where there are people who need to be rescued. “That way, you’re only deploying resources in unsafe areas if you really have to,” she said. The key to the technology is reducing the required power so that it can be supplied by a solar cell that’s no bigger than a cocktail cracker. That required innovations in software as well as hardware. “We had to basically redo a lot of things,” machine learning engineer Hessam Bagherinezhad said. Xnor.ai’s head of hardware engineering, Saman Naderiparizi, worked with his colleagues to figure out a way to fit the software onto an FPGA chip that costs a mere $2, and he says it’s possible to drive the cost down to less than a dollar by going to ASIC chips. It only takes on the order of milliwatts of power to run the chip and its mini-camera, he told GeekWire. “With technology this low power, a device running on only a coin-cell battery could be always on, detecting things every second, running for 32 years,” Naderiparizi said in a news release. That means there’d be no need to connect AI chips to a power source, replace their batteries or recharge them. And the chips would be capable of running AI algorithms on standalone devices, rather than having to communicate constantly with giant data servers via the cloud. If the devices need to pass along bits of data, they could . That edge-computing approach is likely to reduce the strain of what could turn out to be billions of AI-enabled devices. “The carbon footprint of data centers running all of those algorithms is a key issue,” Farhadi said. “And with the way AI is progressing, it will be a disastrous issue pretty soon, if we don’t think about how we’re going to power our AI algorithms. Data centers, cloud-based solutions for edge-use cases are not actually efficient ways, but other than efficiency, it’s harming our planet in a dangerous way.” Farhadi argues that cloud-based AI can’t scale as easily as edge-based AI. “Imagine when I put a camera or sensor at every intersection of this city. There is no cloud that is going to handle all that bandwidth,” he said. “Even if there were, back-of-the-envelope calculations would show that my business will go bankrupt before it sees the light of day.” The edge approach also addresses what many might see as the biggest bugaboo about having billions of AI bugs out in the world: data privacy. “I don’t want to put a camera in my daughter’s bedroom if I know that the picture’s going to end up in the cloud,” Farhadi said. Xnor.ai was , or AI2, only a couple of years ago, and the venture is with millions of dollars of financial backing from Madrona Venture Group, AI2 and other investors. Farhadi has faith that the technology Xnor.ai is currently calling “solar-powered AI” will unlock still more commercial frontiers, but he can’t predict whether the first applications will pop up in the home, on the street or off the beaten track. “It will open up so many different things, the exact same thing when the light bulb was invented: No one knew what to do with it,” he said. “The technology’s out there, and we’ll figure out the exact products.”