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Tesla settles with ex-employee over Autopilot code theft accusations

Engadget

Tesla has settled with a former employee that it sued for downloading data related to its Autopilot feature, Reuters has reported. Tesla filed the lawsuit against Cao Guangzhi back in 2019, accusing its former engineer of copying data to an iCloud account and taking it to his new employer, China's XMotors (owned by Xpeng). Cao reportedly made a monetary payment to Tesla as part of the terms of settlement, but the amount and other details were not disclosed. Cao's legal representative confirmed the settlement, saying he never provided Tesla information to XMotors or any other company. XMotors was not a party in the case, and said it developed its own self-driving technology in-house and respected intellectual property rights.


Autonomous-Truck Developer TuSimple Plans Driverless Road Test This Year

WSJ.com: WSJD - Technology

After opening at $40.25, the stock stumbled, slipping about 20%. But it regained much of its loss to close at $40. "I guess it was a rough awakening to life as a public company for a few hours, but we are optimistic," Chief Financial Officer Pat Dillon said. Top news and in-depth analysis on the world of logistics, from supply chain to transport and technology. Chief Executive Cheng Lu said the company is planning to conduct a "driver-out" pilot program without anyone at the wheel in the fourth quarter on a roughly 100-mile run between Tucson and Phoenix. The company has a fleet of 50 trucks it is testing in the U.S. Southwest and approximately 20 more in China, running with two people in the cab.


Microsoft's Acquisition of Nuance Communications: A Second Go at Language Processing

#artificialintelligence

Welcome to the Capital Note, a newsletter about business, finance, and economics. On the menu today: the history of Nuance's Dragon brand, J&J vaccine halted, Jack Ma capitulates, and W. Brian Arthur on "Economics in Nouns and Verbs." To sign up for the Capital Note, follow this link. Dragon 2.0 Yesterday, Microsoft announced a $16 billion acquisition of language-processing firm Nuance Communications, the latest in a string of big-ticket deals closed by CEO Satya Nadella, who spearheaded the purchases of LinkedIn and Github, among others. With the addition of Nuance's cutting-edge language-processing technology (the lion's share of which is in the health-care sector), Microsoft hopes to beef up its enterprise cloud offering.


Artificial Intelligence (AI) in Pharmaceutical Market Report 2021-2031

#artificialintelligence

Forecasts by Application (Drug Discovery, Precision Medicine, Medical Imaging & Diagnostics, Research), by Technology (Machine Learning, Other Technologies), by Offering (Hardware, Software, Services), by Deployment (Cloud, On-Premises) AND Regional and Leading National Market Analysis PLUS Analysis of Leading AI Companies AND COVID-19 Recovery ScenariosNew York, April 15, 2021 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Artificial Intelligence (AI) in Pharmaceutical Market Report 2021-2031" - https://www.reportlinker.com/p06061831/?utm_source=GNW How Adoption of Artificial Intelligence Impacting Pharmaceutical Industry? The global pharmaceuticals industry is in the throes of transition, both clinical trials and regulatory approvals have been challenged by the proliferation of specialized drugs catering to smaller patient groups. In order to boost results in drug discovery, clinical trials, and research and development, the pharmaceutical and life sciences companies are switching to robotic process control, artificial intelligence and machine learning. All these factors are anticipated to propel demand for artificial intelligence in pharmaceutical across the globe. Artificial Intelligence Anticipated to Revolutionize Several Aspects of Pharmaceutical Industry The way drugs are made, prescribed and ingested today will be standardized by artificial intelligence. Many facets of the pharmaceuticals and life sciences industry will also be revolutionized but will not heal sickness or replace physicians. Understanding the main aim of artificial intelligence, which is to improve human capability and accomplishment instead of challenging it, would dispel much of the technology’s concerns and put out its excellent ability to serve humanity. Which Factors are Fueling AI in Pharmaceuticals Industry Growth? . Growing Complexity of Modern Pharmacology . Growing Demand for Viable Therapeutic Candidates . Improves Overall R&D Productivity . Concerns Associated with Rising Capital Requirements in Drug Discovery . Increasing Awareness Related to Artificial Intelligence Among Pharmaceutical Manufacturers Which Factors are Restraining Growth? . Lack of Skilled Professionals . Limited Availability of Datasets UNIQUE COVID-19 VARIATIONS- only available in this Visiongain report are dedicated analysis of 4 different rebound scenarios of how the market will develop - no matter how COVID-19 affects the economy. To access the data contained in this document please email contactus@visiongain.com How do prominent players strengthen their position throughout the world? You must read this newly updated report if you are involved in this sector. The report from Visiongain shows you potential revenues up to 2031, evaluate information, trends, opportunities and business outlooks. Discover how to stay ahead Our 350+ page report provides 500+ tables and charts/graphs. Read on to discover the most lucrative areas in the industry and the future market prospects. Our new study lets you assess forecasted sales at overall world market and regional level. See financial results, trends, opportunities, and revenue predictions. Much opportunity remains in this growing AI in Pharmaceuticals Market. See how to exploit the opportunities. Forecasts to 2031 and other analyses reveal the commercial prospects . In addition to revenue forecasting to 2031, our new study provides you with recent results, growth rates, and market shares. . You find original analyses, with business outlooks and developments. . Discover qualitative analyses (including market dynamics, drivers, opportunities, restraints and challenges), SWOT Analysis, PEST Analysis, Porter’s Analysis, product profiles and commercial developments. Discover sales predictions for the world market and submarkets Application . Drug Discovery . Precision Medicine . Medical Imaging & Diagnostics . Research Technology . Machine Learning . Other Technologies Offering . Hardware . Software . Services Deployment . Cloud . On-Premises In addition to the revenue predictions for the overall world market and segments, you will also find revenue forecasts for 5 regional and 13 leading national markets: By Region (Segmental Breakdown for All the Regions) . North America - U.S. - Canada . Europe - Germany - France - UK - Italy - Spain - Rest of Europe . Asia Pacific - China - Japan - India - Rest of Asia Pacific . RoW Need industry data? Please contact us today. Leading companies and the potential for market growth Overall world revenue for AI in Pharmaceuticals Market will surpass $xx billion in 2021, our work calculates. We predict strong revenue growth through to 2031. Our work identifies which organizations hold the greatest potential. Discover their capabilities, progress, and commercial prospects, helping you stay ahead. Prospects for established firms and those seeking to enter the market- including company profiles for 16 of the major companies involved in the AI in Pharmaceuticals Market. Some of the companies profiled in this report include are Microsoft Corporation, NVIDIA Corporation, IBM Corporation, Alphabet Inc., Atomwise, Inc., Deep Genomics, Cloud Pharmaceuticals, Inc., Insilico Medicine, BenevolentAI, Exscientia, Biosymetrics, Euretos, Insitro, Cyclica, Biovista, and OWKIN, INC. Key Questions Answered by this Report . What is the current size of the overall global AI in Pharmaceuticals market? How much will this market be worth from 2021 to 2031? . What are the main drivers and restraints that will shape the overall AI in Pharmaceuticals market over the next ten years? . What are the main segments within the overall AI in Pharmaceuticals market? How much will each of these segments be worth for the period 2021 to 2031? How will the composition of the market change during that time, and why? . What factors will affect that industry and market over the next ten years? . What are the largest national markets for the world AI in Pharmaceuticals? What is their current status and how will they develop over the next ten years? What are their revenue potentials to 2031? . How will market shares of the leading national markets change by 2031, and which geographical region will lead the market in 2031? . Which are the leading companies and what are their activities, results, developments, and prospects? . What are the main trends that will affect the world AI in Pharmaceuticals market between 2021 and 2031? . What are the main strengths, weaknesses, opportunities, and threats for the market? . How will the global AI in Pharmaceuticals market evolve over the forecasted period, 2021 to 2031? . How will market shares of prominent national markets change from 2021, and which countries will lead the market in 2031, achieving highest revenues and fastest growth? Read the full report: https://www.reportlinker.com/p06061831/?utm_source=GNWAbout ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.__________________________ CONTACT: Clare: clare@reportlinker.com US: (339)-368-6001 Intl: +1 339-368-6001


Surveillance is All About the (Software) Brain

#artificialintelligence

Eyes are important, don't get me wrong. So are ears, noses, tongues, fingers, balance calibration organs and everything else that feeds that massive brain of yours.1 Salinity detectors in narwhals, electrical sensors in freshwater bottom feeders, echolocation in bats all provide sensory input that humans couldn't adequately process. Every beast has its own senses relevant to its own living conditions. Even your smartphone has cameras, microphones, gyroscopes, an accelerometer, a magnetometer, interfaces for phone/GPS/Bluetooth/WiFi, and some have a barometer, proximity sensors, and ambient light sensors. Biometric sensing equipment in today's phones can include optical, capacitive or ultrasonic fingerprint readers and an infrared map sensor for faces.


The EU is considering a ban on AI for mass surveillance and social credit scores

#artificialintelligence

The European Union is considering banning the use of artificial intelligence for a number of purposes, including mass surveillance and social credit scores. This is according to a leaked proposal that is circulating online, first reported by Politico, ahead of an official announcement expected next week. If the draft proposal is adopted, it would see the EU take a strong stance on certain applications of AI, setting it apart from the US and China. Some use cases would be policed in a manner similar to the EU's regulation of digital privacy under GDPR legislation. Member states, for example, would be required to set up assessment boards to test and validate high-risk AI systems.


Machine Learning App Ideas 2021 - ValueCoders

#artificialintelligence

Artificial Intelligence shapes a lot of things we do in our day-to-day lives. The Netflix show you're binge-watching while on quarantine, the compulsive purchases you make on Amazon, and even the things you search on the internet come to us courtesy of AI. Investments in AI and its key subset – machine learning, are increasing more than ever. The total global investments by private businesses on AI accumulated to a total of $70 Billion in 2020. A survey by McKinsey reported that 82% of enterprises using AI and machine learning across their organizational activities have received a significant return on investment.


China Rivalry Spurs Republicans and Democrats to Align on Tech Spending

WSJ.com: WSJD - Technology

WASHINGTON--Legislation with bipartisan support in Congress would expand the role of the National Science Foundation and provide up to $200 billion in tech and related research funding to meet what backers say is a growing threat from China. The centerpiece of the package is a bill that would rename the federal government's science agency as the National Science and Technology Foundation, and authorize it to spend $100 billion over five years for research into artificial intelligence and machine learning, robotics, high-performance computing and other advanced technologies. An additional $10 billion would be authorized for the Commerce Department to designate at least 10 regional technology hubs for research, development and manufacturing of key technologies. Additional funding would likely be made available for domestic semiconductor manufacturing and other tech-related supply-chain proposals. The Endless Frontier Act got a hearing before the Senate Commerce Committee on Wednesday, drawing support from Republicans and Democrats.


Artificial Intelligence: Regulatory Trends

#artificialintelligence

The potential positive economic effects of artificial intelligence (AI) have been well-documented, with several high-profile studies highlighting its impact on areas such as workforce productivity and wealth creation. At the same time, widespread adoption of AI technologies has contributed to increased scrutiny and a sharper focus on AI's potentially harmful implications. Listed below are the key regulatory trends impacting the AI theme, as identified by GlobalData. In 2020, the US and Europe have taken steps to regulate AI, but there are notable differences in approach. Europe appears more optimistic about the benefits of regulation, while the US has warned of the dangers of overregulation.


The ulti-mutt pet? Chinese tech company develops robot dogs that uses AI to 'hear' and 'see'

#artificialintelligence

It's whip fast, obeys commands and doesn't leave unpleasant surprises on the floor – meet the AlphaDog, a robotic response to two of China's burgeoning loves: pets and technology. The high-tech hound uses sensors and Artificial Intelligence (AI) technology to'hear' and'see' its environment – and can even be taken for walks. "It's really very similar to a real dog," says Ma Jie, chief technology officer at Weilan, the company behind the product. The Nanjing-based creators say their robot dog – which moves at a speed of almost 15 kilometres (nine miles) per hour and spins on the spot like an excited puppy – is the fastest on the market. With four metal legs it is more stable than a real dog, Ma explains as one of his team swiftly kicks it to prove the point.