Ultra-low-power AI accelerator startup Syntiant has raised another $35 million in a series C round of funding to bring the total raised by the company to $65 million. Syntiant, whose 66 staff work out of Irvine, Calif., also announced that it has hit a shipping milestone with 1 million parts in the hands of customers. Third round Syntiant's C round was led by Microsoft's VC fund, M12, and Applied Ventures, the VC arm of Applied Materials. "[$35m] gets us pretty far into growing our sales team and ramping our revenue," Syntiant CEO Kurt Busch told EE Times. "We have the second-generation chip already back in the lab, which we expect to announce before the end of the year… this funding will also be used to fund development of third generation silicon and build out our customer base."
"I personally think that no matter which approach you use, you lose," said Emily Wenger, a Ph.D. student who helped create Fawkes. "You can have these technological solutions, but it's a cat-and-mouse game. And you can have a law, but there will always be illegal actors." Ms. Wenger thinks "a two-prong approach" is needed, where individuals have technological tools and a privacy law to protect themselves. Elizabeth Joh, a law professor at the University of California, Davis, has written about tools like Fawkes as "privacy protests," where individuals want to thwart surveillance but not for criminal reasons.
One of the challenges with modern machine learning systems is that they are very heavily dependent on large quantities of data to make them work well. This is especially the case with deep neural nets, where lots of layers means lots of neural connections which requires large amounts of data and training to get to the point where the system can provide results at acceptable levels of accuracy and precision. Indeed, the ultimate implementation of this massive data, massive network vision is the currently much-vaunted Open AI GPT-3, which is so large that it can predict and generate almost any text with surprising magical wizardry. However, in many ways, GPT-3 is still a big data magic trick. Indeed, Professor Luis Perez-Breva makes this exact point when he says that what we call machine learning isn't really learning at all.
Every time Congress holds a hearing about Silicon Valley companies, people mock the legislators for being out of their depth. Last week's effort by the antitrust subcommittee of the House Judiciary Committee was no exception. "The technological ignorance demonstrated by our elected officials ... was truly stunning," Shelly Palmer, CEO at the Palmer Group, a tech strategy advisory group, told USA Today. "People who are this clueless about the economic forces shaping our world should not be tasked with leading us into the age of AI," he said. "The data elite are playing a different game with a different set of rules. Apparently, Congress can't even find the ballpark."
Employees at Blizzard Entertainment, a division of Activision Blizzard Inc., began circulating a spreadsheet on Friday to anonymously share salaries and recent pay increases, the latest example of rising tension in the video game industry over wage disparities and executive compensation. Blizzard, based in Irvine, California, makes popular games including Diablo and World of Warcraft. In 2019, after an internal survey revealed that more than half of Blizzard workers were unhappy with their compensation, the company told staff it would perform a study to ensure fair pay, according to people familiar with the situation. Blizzard implemented the results of that study last month, which led to an outcry on the company's internal Slack messaging boards. One employee then created a spreadsheet and encouraged staff to share their compensation information.
Artificial intelligence researchers are always trying to replicate aspects of human senses through algorithms. AI has been used to dramatically enhance computer vision applications in recent years, and AI has also been used to generate fairly impressive audio samples, even creating whole songs in the style of one artist. Recently, a team of scientists from University of California, Riverside managed to create an AI capable of distinguishing smells from one another based on the chemical makeup of the odor in question. According to cell and systems biologist at UC Riverside, Anandasankar Ray, the researchers tried to base their AI model on how humans perceive smells. The human nose contains approximately 400 olfactory receptors (ORs) that are activated when chemicals enter the nose.
Bradford specializes in matters related to trade secrets and Artificial Intelligence. He is the Chair of the AI Subcommittee of the ABA. Recognized by the Daily Journal in 2019 as one of the Top 20 AI attorneys in California, Bradford has been instrumental in proposing federal AI workplace and IP legislation that in 2018 was turned into a United States House of Representatives Discussion Draft bill. He has also developed AI oversight and corporate governance best practices designed to ensure algorithmic fairness. What was it that initially ignited your interest in artificial intelligence?
Amazon's recent offer to acquire Zoox places them squarely in the Autonomous Vehicle (AV) space, competing with the likes of Waymo, Tesla and others for movement automation of people and goods. As a reminder, Zoox is the San Francisco, California based company with a breathtakingly bold vision – to develop purpose-made autonomous electric vehicles for ride-hailing, and deliver services to consumers through this platform. Executing this vision means competing on multiple fronts with big players- automotive OEMs (designing and building cars), tech companies like Google (who has spent a decade and a fortune to develop the Autonomous Vehicle Driving System or AVS), and ride-hailing companies like Uber and Lyft LYFT . To date, Zoox has raised $1B and hired close to 1000 people, but without any revenues, they probably need 10X the investment. A recent article covers the details of the Zoox acquisition, and posits that an important driver was Zoox's expertise in computer vision.
Back in 2016, Juan Pablo Torres-Padilla, who has been the CEO of an artificial intelligence (AI) company in France and has held other key positions in the telecommunications and financial investment world, decided to take the opportunity to buy the historic Napa Valley 26 acre Sullivan Rutherford Estate from the Sullivan family, the custodians of that piece of land for over 40 years. It would prove to be a good partnership in terms of handing over the estate to someone who not only wanted to bring this winery more to the forefront of the Napa fine wine world but that the history and legacy would be appreciated and built upon. The estate lies on land that has a deep and rich history which goes back almost two centuries to 1821 when Mexico took over ownership of Napa Valley from Spain. Mexico divided the Napa Valley into two parts: Rancho Carne Humana in the North and Rancho Caymus in the South. Sullivan Rutherford Estate director of winemaking, Jeff Cole, said that they are "essentially in the middle of the heart of Napa Valley vineyards" since the back of the border of their estate is along the Rancho Caymus line as it is right in the middle of where the property lines of Rancho Caymus and Rancho Carne Humana meet.
Amazon's recent offer to acquire Zoox places them squarely in the Autonomous Vehicle (AV) space, competing with the likes of Waymo, Tesla and others for movement automation of people and goods. As a reminder, Zoox is the San Francisco, California based company with a breathtakingly bold vision – to develop purpose-made autonomous electric vehicles for ride-hailing, and deliver services to consumers through this platform. Executing this vision means competing on multiple fronts with big players- automotive OEMs (designing and building cars), tech companies like Google (who has spent a decade and a fortune to develop the Autonomous Vehicle Driving System or AVS), and ride-hailing companies like Uber and Lyft LYFT. To date, Zoox has raised $1B and hired close to 1000 people, but without any revenues, they probably need 10X the investment. A recent article covers the details of the Zoox acquisition, and posits that an important driver was Zoox's expertise in computer vision.