Steady advances in machine vision techniques such as convolutional neural networks powered by graphics processors and emerging technologies like neuromorphic silicon retina "event cameras" are creating a range of new predictive monitoring and maintenance use cases. We've reported on several, including using machine vision systems to help utilities monitor transmission lines and towers linked to wildfires in California. Now, AI software vendor Ignitarium and partner AVerMedia, an image capture and video transmission specialist, have expanded deployment an aircraft-based platform for detecting railway track obstructions. The AI-based visual "defect detection" platform incorporates Ignitarium's AI software implemented on Nvidia's edge AI platform used to automatically control onboard cameras. The system is designed to keep cameras focused on the track center during airborne inspections.
San Diego Supercomputer Center makes high performance computing resources available to researchers via a "condo cluster" model. Many homebuyers have found that the most affordable path to homeownership leads to a condominium, in which the purchaser buys a piece of a much larger building. This same model is in play today in the high performance computing centers at many universities. Under this "condo cluster" model, faculty researchers buy a piece of a much larger HPC system. In a common scenario, researchers use equipment purchase funds from grants or other funding sources to buy compute nodes that are added to the cluster.
Managing Partner and Co-Founder of Scale-Up VC, a Silicon Valley venture capital firm based in Palo Alto, California. Experts have warned against its potential misuse. It's now affecting aspects of our lives that many of us never anticipated: healthcare, education, employment and even national security. What could I be talking about? Artificial intelligence, or the "big AI," as I call it.
Former Waymo and Uber self-driving car-whiz kid, Anthony Levandowski was sentenced last week to 18 months in federal prison for stealing trade secrets. Levandowski will also pay a $95,000 fine and $756,499.22 in restitution to Waymo. He co-founded Google's self-driving car program, now Waymo, in 2009 and served as the program's technical lead until January 2016, when he left to co-found self-driving truck start-up Otto. Seven months later Uber acquired Otto for $680M and named Levandowski the head of its self-driving car division. He was on top of the tech world. He appeared in Wired Magazine as the go-to voice in Silicon Valley for self-driving cars and LiDAR technology.
Would you entrust a personal-injury claim, divorce settlement or high-stakes contract to an algorithm? A growing number of apps and digital services are betting you will, attracting millions of Silicon Valley investment dollars but raising questions about the limits and ethics of technology in the legal sphere. Among the leaders in the emergent robo-lawyering field is DoNotPay, an app dreamed up by Joshua Browder in 2015, when he was a 17-year-old Stanford University student, to help friends dispute parking tickets. The app, which relies on an artificial intelligence-enabled chatbot, became popular, and has expanded its focus to other consumer legal services. In June it hit the million-case mark, helping save people upward of $30 million since it started, Mr. Browder says. It raised a new $12 million round of funding the same month.
Syntiant Corp., the "neural decision processor" startup, announced completion of another funding round this week along with the shipment of more than 1 million low-power edge AI chips. The three-year-old startup based in Irvine, Calif., said Tuesday (Aug. The round was led by Microsoft's (NASDAQ: MSFT) venture arm M12 and Applied Ventures, the investment fund of Applied Materials (NASDAQ: AMAT). New investors included Atlantic Bridge Capital, Alpha Edison and Miramar Digital Ventures. Intel Capital was an early backer of Syntiant, part of a package of investments the chip maker announced in 2018 targeting AI processors that promise to accelerate the transition of machine learning from the cloud to edge devices.
SANTA CLARA, Calif., Aug. 4, 2020 – Tachyum Inc. announced that its Prodigy Universal Processor has successfully completed software emulation testing across x86, ARM and RISC-V binary environments. This important milestone demonstrates that Prodigy will enable customers to run their legacy applications transparently at launch with better performance than any contemporary or future ARM or RISC-V processors. Coupled with hyperscale data center workhorse programs such as Hadoop, Apache and more, which Tachyum is recompiling to Prodigy native code, this capability will ensure that Prodigy customers can run a broad spectrum of applications, right out of the box. Tachyum customers consistently indicate that they would run 100% native applications within 9-18 months of transitioning to the Tachyum platform to exceed performance of the fastest Xeon processor. The emulation is to smoothly transition to native software for Tachyum Prodigy.
Last week three individuals filed a lawsuit against Microsoft Corporation in the United States District Court for the Northern District of California, with a request for class action certification. Microsoft's multitude of Business and Enterprise editions offer more advanced feature sets than the Home and Personal editions, with collaborative applications and management tools designed for meeting enterprise security and compliance challenges. The plaintiffs contend that Microsoft is routinely violating the privacy of customers who pay for business subscriptions to Microsoft 365 (formerly Office 365). They allege that "Microsoft shares its business customers' data with Facebook and other third parties, without its business customers' consent." The complaint also accuses Microsoft of sharing business customers' data with third-party developers and with "hundreds of subcontractors ... without requiring the subcontractors to keep the data private and secure." And they maintain that Microsoft uses their business customers' private data "to develop and sell new products and services--and otherwise benefit itself."
Syntiant, a startup developing AI edge hardware for voice and sensor solutions, today closed a $35 million round. CEO Kurt Busch says the funds will be used to ramp up production throughout the remainder of 2020. According to a report published by Meticulous Research, the speech and voice recognition hardware market is expected to reach $26.8 billion by 2025. That's because devices like smart speakers, smart displays, phones, headphones, hearing aids, and laptops require low-power chips to process utterances. While some system-on-chip offerings sport coprocessors to handle voice recognition, they're often not able to accommodate multiple form factors. Three-year-old Syntiant, which is headquartered in Irvine, California, provides hardware that merges machine learning with semiconductor design for always-on voice applications.
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."