Kyle Wiggers reports in Venture Beat:
Authorities in China have tapped artificial intelligence (AI) to clamp down on unsanitary cooks in kitchens — and to reward those who adhere to best practices.A camera-based system recognizes “poor [sanitation] habits” and alerts managers to offending workers via a mobile app. The system can identify 18 different “risk management” areas, including smoking and using a smartphone. (phones carry 10 times more bacteria than toilet seats.) On the flip side, it recognizes four positive habits, like disinfecting surfaces and hand washing, and monitors kitchen conditions that might impact food safety, such as temperature and humidity.
According to the report, a camera-based system currently being piloted in the Zhejiang city of Shaoxing automatically recognizes “poor [sanitation] habits” and alerts managers to offending workers via a mobile app. It’s reportedly the fruit of a six-year project — Sunshine Kitchen — that seeks to bring transparency to food preparation in catering, hotels, school cafeterias, and restaurants.
Zhou Feng, director of the Food Service Supervision Department in Shaoxing, told Thepaper.cn that the system can identify 18 different “risk management” areas, including smoking and using a smartphone. (Some studies have shown that phones carry 10 times more bacteria than toilet seats.) On the flip side, it recognizes four positive habits, like disinfecting surfaces and hand washing, and monitors kitchen conditions that might impact food safety, such as temperature and humidity.
So far, the local Xianheng Hotel and over 87 catering companies are said to have trialed the system, and authorities reportedly plan to expand the number to over 1,000 this year.
It’s not the first time AI has been applied to food safety.
In November 2018, a study led by researchers at Google and Harvard’s T.H. Chan School of Public Health described a machine learning model — FINDER (Foodborne IllNess DEtector in Real time) — that leveraged search and location data to highlight “potentially unsafe” restaurants. FINDER took in anonymous logs from users who opted to share their location data, and it identified search queries indicative of food poisoning (e.g., “how to relieve stomach pain”) while looking up restaurants visited by the users who performed those searches.
In the end, FINDER not only outperformed complaint-based inspections and routine inspections concerning precision, scale, and latency (the time that passed between people becoming sick and the outbreak being identified), it managed to better attribute the location of foodborne illness to a specific venue than did customers.
San Francisco-based startup ImpactVision, meanwhile, leverages machine learning and hyperspectral imaging — a technique that combines spectroscopy and computer vision — to assess the quality of food in factories and elsewhere automatically. It’s now working with avocado distributors to replace their current systems, and with large berry distributors to potentially automate manual processes, such as counting strawberries.
Nvidia stock falls $14 billion on crypto-related earnings preannouncement
Above: Nvidia CEO Jensen Huang shows off the Nvidia GeForce RTX 2080 Ti at Gamescom 2018.Image Credit: Nvidia
The stock fell 15 percent so far today, knocking out $14.2 billion in market value, as Nvidia said fourth-quarter revenue would be $2.2 billion, compared to previous guidance of $2.7 billion.
On top of the crypto effect, Nvidia said that both gaming and data center revenue are below the company’s expectations. Nvidia will report final resources for the quarter ending January 31on its February 14 earnings call.
Nvidia had previously anticipated a sequential decline due to excess inventory of mid-range graphics chips in the sales channel, following the cryptocurrency boom and subsequent bust. The stock price fall today comes after Nvidia’s price decline in the fall, where its stock fell $23 billion in a day when it announced the crypto effect.
The reduction in that inventory and its impact on the business have proceeded largely inline with management’s expectations. However, deteriorating macroeconomic conditions, particularly in China, impacted consumer demand for Nvidia gaming graphics processing units (GPUs).
Above: MSI’s RTX 2070 for $500.Image Credit: MSI
In addition, sales of certain high-end GPUs using Nvidia’s new Turing architecture — the GeForce RTX graphics cards that can do real-time ray tracing — were lower than expected.
“These products deliver a revolutionary leap in performance and innovation with real-time ray tracing and AI, but some customers may have delayed their purchase while waiting for lower price points and further demonstrations of RTX technology in actual games,” Nvidia said.
On top of that, data center revenue also came in short of expectations. A number of deals in the company’s forecast did not close in the last month of the quarter as customers shifted to a more cautious approach. Despite these near-term headwinds, Nvidia said it has a large and expanding addressable market opportunity in artificial intelligence and high-performance computing, and the company believes its competitive position is intact.
“Q4 was an extraordinary, unusually turbulent, and disappointing quarter,” said Jensen Huang, CEO of Nvidia, in a statement. “Looking forward, we are confident in our strategies and growth drivers. The foundation of our business is strong and more evident than ever – the accelerated computing model Nvidia pioneered is the best path forward to serve the world’s insatiable computing needs. The markets we are creating – gaming, design, HPC, AI and autonomous vehicles – are important, growing and will be very large. We have excellent strategic positions in all of them.”
Nvidia expects its GAAP and non-GAAP gross margin to be impacted by approximately $120 million in charges for excess dynamic random access memory and other components associated with the updated revenue guidance and current market conditions.
0 comments:
Post a Comment