Almost half a century after founding his pioneering motor-maker on the family farm, Japanese billionaire Shigenobu Nagamori is handing over leadership of Nidec Corp. to a former Nissan Motor Co. executive to lead an ambitious pivot into the electric-vehicle space. Jun Seki will take over from Nagamori as chief executive officer, the Kyoto-based company said last week as it announced better-than-projected annual results. The leadership change, which comes a little over a year after Seki's move from Nissan, will be finalized when Nidec's board meets June 22. Nagamori, who founded Nidec in a shack in 1973, will remain chairman. Seki, 59, was appointed president of Nidec after leaving Nissan, where he was vice chief operating officer and an unsuccessful contender for CEO after Hiroto Saikawa resigned amid a compensation scandal, following the shock arrest of former chairman Carlos Ghosn.
Almost half a century after founding his pioneering motor maker on the family farm, Japanese billionaire Shigenobu Nagamori is handing over leadership of Nidec Corp. to a former Nissan Motor Co. executive to lead an ambitious pivot into the electric-vehicle space. Jun Seki will take over from Nagamori as chief executive officer, the Kyoto-based company said last week as it announced better-than-projected annual results. The leadership change, which comes a little over a year after Seki's move from Nissan, will be finalized when Nidec's board meets June 22. Nagamori, who founded Nidec in a shack in 1973, will remain chairman. Seki, 59, was appointed president of Nidec after leaving Nissan, where he was vice chief operating officer and an unsuccessful contender for CEO after Hiroto Saikawa resigned amid a compensation scandal, following the shock arrest of former chairman Carlos Ghosn.
Every urban mobility EV concept needs some kind of fun gimmick, and Hyundai has delivered quite a few with its latest Mobis M.Vision concepts. The first model called the M.Vision POP is a small two seater not unlike Citroen's Ami, but with some unique features that make it much more tech-friendly and maneuverable. The POP was developed under Hyundai's "Tech Joy" theme, with a "core solution" called "Phobility." Translated from designer-speak, the idea is that your smartphone could not only be used to reserve a car, but would also be embedded in the steering wheel and "become the cockpit of the automobile itself," according to Hyundai. It can then interface with the vehicle's display, allow for voice recognition and "use smartphone sensors for wireless steering of the vehicle," somehow.
San Francisco, March 3, 2021 -- BrainChip Holdings Ltd. (ASX: BRN), a leading provider of ultra-low-power, high-performance AI technology, ended the 2020 calendar year having made significant strides in the development of its technology backed by the launch of its Early Access Program (EAP), availability of Akida evaluation boards, new partnerships, and expansion of its executive leadership and global facilities. The Company's EAP was launched in June targeting specific customers in a diverse set of end markets in order to ensure availability of initial devices and evaluation systems for key applications. Multiple customers have committed to the advanced purchase of evaluation systems for a range of strategic Edge applications including Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV), Unmanned Aerial Vehicles (UAV), Edge vision systems and factory automation. Among those joining the EAP include VORAGO Technologies in a collaboration intended to support a Phase I NASA program for a neuromorphic processor that meets spaceflight requirements. BrainChip is also collaborating with Tier-1 Automotive Supplier Valeo Corporation to develop neural network processing solutions for ADAS and AV.
Darryl Richardson was delighted when he landed a job as a "picker" at the Amazon warehouse in Bessemer, Alabama. "I thought, 'Wow, I'm going to work for Amazon, work for the richest man around," he said. "I thought it would be a nice facility that would treat you right." Richardson, a sturdily built 51-year-old with a short, charcoal beard, took a job at the gargantuan warehouse after the auto parts plant where he worked for nine years closed. Now he is strongly supporting the ambitious effort to unionize its 5,800 workers because, he says, the job is so demanding and working for Amazon has fallen far below his expectations. Last August, five months after the warehouse opened, Richardson began pushing for a union in what is not only the first effort to organize an entire Amazon warehouse in the United States, but also the biggest private-sector union drive in the south in years. "I thought the opportunities for moving up would be better. I thought safety at the plant would be better," Richardson said. "And when it comes to letting people go for no reason – job security – I thought it would be different."
Infrastructure around the world is being linked together via sensors, machine learning and analytics. We examine the rise of the digital twin, the new leaders in industrial IoT (IIoT) and case studies that highlight the lessons learned from production IIoT deployments. Honeywell will acquire life sciences software company Sparta Systems for $1.3 billion in a move that will expand the reach for the Honeywell Forge platform. Sparta Systems features quality management software delivered as a service with artificial intelligence. Honeywell's plan is to leverage Sparta Systems and combine it with the Forge platform and Experian Process Knowledge System to expand more into life sciences.
Honeywell to leverage Microsoft Azure cloud platform and connect Microsoft Dynamics 365 to Honeywell Forge, enabling predictive maintenance applications with closed-loop maintenance workflows in the buildings industry. Honeywell and Microsoft announced that Honeywell will bring to market its domain-specific applications built on the Microsoft cloud platform to drive new levels of productivity for industrial clients. With the integration of the AI-driven autonomous controls of the Honeywell Forge enterprise performance management software with Microsoft Dynamics 365 Field Service, customers will be able to access operating data that includes workflow management support to improve performance and energy efficiency within the enterprise environment. Workers in the field will benefit from real-time access to critical data that will help them prioritize, analyze and solve problems more quickly. The first area of focus will be in automating maintenance for building owners and operators.
In March, Japan's largest auto parts maker, Denso Corp., was facing the urgent task of how to secure enough face masks for its workers given the mass shortage that was occurring amid the spread of COVID-19 infections. While the company, located in Kariya, Aichi Prefecture, had sufficient stocks of masks back then, executives were getting worried that if the company ran short, its production might be affected, since each factory worker needs five masks a day. At an executive meeting March 2, all eyes turned to Yasuhiko Yamazaki, 56, senior executive officer in charge of production, when he said, "How about making them ourselves?" After returning home, Yamazaki cut a mask he had with a pair of scissors, looked at its three-layered structure with nonwoven material used as a middle layer, and felt certain it could be made by Denso. The following day, he gathered seven to eight employees who were well-versed in auto parts production technology and were engaged in the designing and manufacturing of machinery and equipment.
This paper introduces structured machine learning regressions for prediction and nowcasting with panel data consisting of series sampled at different frequencies. Motivated by the empirical problem of predicting corporate earnings for a large cross-section of firms with macroeconomic, financial, and news time series sampled at different frequencies, we focus on the sparse-group LASSO regularization. This type of regularization can take advantage of the mixed frequency time series panel data structures and we find that it empirically outperforms the unstructured machine learning methods. We obtain oracle inequalities for the pooled and fixed effects sparse-group LASSO panel data estimators recognizing that financial and economic data exhibit heavier than Gaussian tails. To that end, we leverage on a novel Fuk-Nagaev concentration inequality for panel data consisting of heavy-tailed $\tau$-mixing processes which may be of independent interest in other high-dimensional panel data settings.