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Tesla Stock Gains Monday As Model 3 Reservations Pass 276,000

Loading the player…   Tesla Motors ( TSLA ) stock climbed 4% in premarket trading Monday, compounding Friday’s gain as reservations for its new Model 3 electric car soared far beyond views. CEO Elon Musk tallied 276,000 reservations by the beginning of Sunday and said he’d give another update Wednesday. The pre-order period opened Thursday ahead of a Thursday-night reveal event. Musk said in Twitter posts that  he’s definitely going to have to rethink production planning. Tesla had expected only one quarter to one half of the 115,000 reservations that came in before anyone even got to see what the car looked like. The refundable reservations are $1,000 each and worth $11.6 billion dollars in revenue if everybody were to go through with a purchase. “While there was clearly a lot of excitement and optimism around both the car and the company, roughly one-third of the respondents we talked to sounded undecided on whether they would actually purchase when the option came up in two years,” Pacific Crest Securities analyst Brad Erickson said in a research note written Friday and distributed late Sunday. The focus now is on how all the numbers — and Tesla stock — will play out. The company has just effectively crowdfunded more than a quarter billion dollars from reservations. That’s more than it raised in its IPO. The 276,000 reservations worldwide also tops the number of electric and plug-in hybrid vehicles sold around the U.S. in the last two years by the entire auto industry. And it’s more than the 245,000 BMW passenger cars sold in the U.S. last year. Tesla delivered almost 51,000 electric vehicles — its Model S sedan and Model X crossover — last year worldwide. Tesla Stock Analysis Going into Monday, Tesla stock was just below where it started 2016. It closed Friday at 237.59 after hitting its highest point since early October. The stock isn’t highly rated by IBD now, factoring in its history of losses and earnings, stock performance and other factors. The Model 3 is the electric car meant for the entry-level luxury mass market, priced at $35,000 for the base model before any tax credits. Musk expects the average purchase price with add-ons to be $42,000. The car is seen as a challenger to BMW’s 3 Series and similarly priced models from Daimler ’s ( DDAIF ) Mercedes-Benz, Volkswagen ’s ( VLKAY ) Audi and Toyota ’s ( TM ) Lexus, as well as electrics like General Motors ’ ( GM ) Chevrolet Bolt EV. Among the many things analysts and investors will be deconstructing is how much content from Tesla’s tech partners Nvidia ( NVDA ) and Mobileye ( MBLY ) go into the Model 3. Nvidia chips power the entertainment console in Tesla’s current vehicles. Mobileye is a maker of camera-based advanced driver assistance systems, and its technology is used by Tesla in conjunction with Autopilot self-driving car features. RELATED: Tesla Model 3 Reservations Hit 276,000 By Sunday

Google Self-Driving Car Chief Urges Congress To OK Safety Tech

The chief of self-driving car development at Google told a U.S. Senate panel Tuesday that “Congress has a huge opportunity to help ensure that self-driving cars can be safely deployed at scale,” as the  Alphabet ( GOOGL ) subsidiary and others push the pedal to the metal on the fast-emerging technology. Chris Urmson, director of the self-driving car program at Google X, was among those testifying at a hearing titled “Hands Off: The Future of Self-Driving Cars,” convened by U.S. Sen. John Thune, R.-S.D., chairman of the Senate Committee on Commerce, Science and Transportation. “We need cars that are fully self-driving,” Urmson said. “The car must be designed to do all the work, so the occupants are not expected to take control of the vehicle at any time.” Urmson pointed to National Highway Traffic Safety Administration estimates that “38,000 people were killed on America’s roads last year, and 94% of accidents involve human error. Self-driving cars can help us change that. Not only could our roads be a lot safer, but self-driving cars could bring everyday destinations and new opportunities within reach of those who might otherwise be excluded from their inability to drive a car.” Google is testing self-driving prototype vehicles in three states, driving 1.4 million miles “in autonomous mode” over the past several years, Urmson said. Senator Urges Rethink To Boost Self-Driving Cars Sen. Thune, in comments before the testimony by Urmson and others, sounded ready to act. He urged federal and state governments to rethink how they regulate and license vehicles for the future. “We must ensure that the United States remains the cradle of innovation and that we continue to lead the way in the development and deployment of automated vehicles,” Thune said. “In addition, questions regarding liability, insurance, privacy, security and infrastructure need answers. These aren’t small things, but none of them is insurmountable.” He pointed to the technology’s ability to not only clear up gridlock, but also improve communities. “To implement this future, we need to challenge ourselves to overcome the 20th century conception of what a car must have … and even the concept of a licensed human driver. Because so much is possible, we must be careful not to stymie innovation because of a lack of imagination,” he said. But the technology is facing a patchwork of state regulations. “Over the past two years, 23 states have introduced 53 pieces of legislation that affect autonomous vehicles, all of which include differ approaches and concepts,” Google’s Urmson said. The hearing comes a month after one of Google’s self-driving cars hit a municipal bus in California. Google has said new software changes will avoid future incidents, but at least one speaker Tuesday urged caution. Mary Louise Cummings, director of the Humans and Autonomy Lab and Duke Robotics at Duke University, said there remain concerns over the cars’ sensors not working properly in some areas. Moreover, she said, “we know people will try to hack into these systems.” And the technology, while developing fast, remains relatively untested. She said that while Google’s cars have driven those 1.4 million miles the past several years, “New York cabs drive 1.4 million miles” every day. Still, there is no question automakers and tech firms are fast heading down the road toward the day they can start selling vehicles that can drive themselves.  Apple ( AAPL ) is among those in the car game, it’s been widely reported, though the company hasn’t confirmed this. NXP Semiconductors ( NXPI ), Mobileye ( MBLY ), Nvidia ( NVDA ) and Ambarella ( AMBA ), among others, are partnering with automakers to develop chips and technology for self-driving cars and sophisticated safety systems in such cars. California’s Proposed Law Seen As Detour For Self-Driving Cars But Google and others have complained about laws impeding progress. In December, California proposed draft rules banning autonomous vehicles that aren’t equipped with human controls and don’t have a licensed human driver aboard. In January, U.S. Transportation Secretary Anthony Foxx introduced the Obama administration’s $4 billion, 10-year plan to get self-driving cars onto U.S. roads in “corridors” throughout the country. The NHTSA said this year that it may set aside some vehicle safety rules to allow more driverless cars to operate on U.S. roads, as part of a broader effort to speed up development of self-driving vehicles. On Friday, the NHTSA said in a report that there are significant legal hurdles to allowing fully autonomous vehicles without steering wheels, according to Reuters. The federal agency will write guidelines for self-driving cars within six months, Foxx said in January. Last month, the agency said the artificial intelligence system piloting a self-driving Google car could be considered the driver under federal law.  

AI Meets ROI: Where Artificial Intelligence Is Already Smart Business

Decades of research and billions of dollars have poured into developing artificial intelligence, which has crossed over from science fiction to gameshow novelty to the cusp of widespread business applications. Artificial intelligence is an area of computer science where computers are designed to think and operate much like a human brain, supported by advanced forms of computing and software. But it’s only as smart as the amount of information fed into its memory banks. The more information, the smarter it gets. The greatest advancements have been demonstrated in the area of game playing, but AI is now showing its mettle in the business world. “People are starting to kick the tires, looking to see how it can help their business and the bottom line,” said David Schubmehl, who follows the AI field for research firm IDC. “The return on investment evidence is not yet clear, but it’s starting to happen.” Facebook ( FB ), Alphabet ( GOOGL ), IBM ( IBM ) and Nvidia ( NVDA ) are among tech leaders with big artificial intelligence ambitions. “We’re starting to see a lot of companies beginning to use different types of AI tech for various uses,” said Schubmehl. “We’re also seeing a lot of venture capital money flowing in and a lot of acquisitions taking place.” IBM, which may have the deepest AI investments and most far-reaching ability of any company, has pitched “cognitive computing” as a tool for businesses via its cloud-based Watson platform. Facebook is using AI to decipher the best ways to bring Internet service to remote areas of the world and to make its News Feed feature more relevant to users of the social network. Alphabet is using it to enhance Google search abilities, improve voice recognition and to derive more data from images and video. Nvidia has developed chip technology for AI platforms used in autonomous driving features, and to enhance how a driver and car communicate. Alphabet,  Mobileye ( MBLY ) and others also are tapping AI in the race for driverless cars. It’s not enough to have Google Maps loaded up: A self-driving system must identify potholes, weather conditions, traffic congestion and other drivers’ behavior — improvising and improving on the fly. AI: Ready, Chess, Go Artificial intelligence, a term coined in 1955, was popularized when IBM’s “Big Blue” became the first computer to beat a reigning world chess champion, Gary Kasparov, in 1997. IBM won again in 2011, when its Watson computer on “Jeopardy!” outsmarted the game show’s two top players ever. Last October, an AI computer beat a three-time European champion in the ancient Asian game of “Go.” AphaGo, built by DeepMind, part of Alphabet’s Google, beat Fan Hui by 5 games to 0, the first time a computer program has ever beaten a professional Go player and a feat thought to be a decade away. On Tuesday, AlphaGo won the first game vs. Lee Sodol, who is ranked No. 5 in the world. Tuesday’s match shows that AlphaGo has made big improvements since beating the No. 633 ranked Fan Hui last year. Google paid $400 million to acquire DeepMind in 2014. But despite rapid advances, artificial intelligence is still in the early stages of business deployment. “A lot of what AI is being used for today only scratches the surface of what can be done,” said Babak Hodjat, co-founder and chief scientist at Sentient Technologies . “It will become so ubiquitous that we won’t even call it AI anymore.” AI Picks Out Your Shoes Sentient emerged from stealth mode in late 2014 with a massively distributed AI platform that companies can use to boost performance. As shoppers at Shoes.com  browse through photos of shoes and click on ones they like, Sentient’s technology narrows the selection, so people don’t get overwhelmed by choices. There’s no need for text-based searches or drill-down navigation, said Hodjat. The AI technology deciphers what shoppers are looking for, letting them quickly dive deeper into a catalog to find the perfect item that might otherwise go undiscovered. “We’ve revolutionized the user experience on an e-commerce website,” said Hodjat. “It’s a huge change in the way users interact with products online and therefore drives conversion.” Sentient has received $143 million in venture capital funding, the most of any AI startup, according to research firm CB Insights. Since 2010, AI startups have received $967 million in funding.  Intel ( INTC ) alone has invested in 16 AI companies, including  Saffron Technology . Saffron says its platform “mimics the fundamental principles of how humans remember and learn.” In a case study on its website, Saffron helped an insurer to identify fraudulent auto insurance claims. Over 10 weeks, Saffron examined 113,000 claims from one year in one state and found three potential fraud rings. It then detected that these rings were part of a larger ring involved with 38 claims, of which the insurance company had paid out about $400,000 in claims. Saffron was able to collect data that identified relevant and unknown relationships, including different providers, demographics and injury descriptions, creating a knowledge store that had never been done before. Saffron forecasts that the insurer can avoid a payout of tens of millions of dollars a year. AI goes by terms such as machine learning and deep learning. IBM calls it cognitive computing. In October it launched Cognitive Business Solutions, with 2,000 consultants skilled in data analytics, cloud computing and other areas. More than 500 companies have deals to use Watson, as a cloud service, to develop commercial products, apps and services. Turner Broadcasting on Feb. 29 signed a deal to use Watson in its ad sales efforts. The  Time Warner ( TWX ), unit owns TBS, TNT and CNN. Using IBM Watson, Turner expects to parse through all manner of data to help draw in more advertisers and provide them with greater impact. Watson Can Predict Low Blood Sugar Watson Health is a platform for physicians, researchers, insurers and other companies focused on health and wellness. Medtronic ( MDT ) is collaborating with IBM on personalized care for people with diabetes. By analyzing patient info and data from Medtronic devices, Watson can predict low blood sugar programs three hours in advance. Artificial intelligence is all about using advanced technologies to help develop brainy reasoning from disorganized information — unstructured data — to derive accurate decisions. “What we’ve done with all our research is to really understand how to add unstructured data to a decision,” said David Kenny, general manager of IBM Watson. Unstructured data comes from a multitude of sources that is not organized. It can be the data bits from photos, medical images or video and audio transmissions. It can be the tons of data that flows in from cameras or sensors in buildings or smartphones, from Web traffic, tweets, inside emails, government filings or business documents. The more information an artificially intelligent computer can digest the smarter it gets. Today The Weather, Tomorrow… Collecting data on a massive scale is among the reasons IBM acquired several Weather Co. properties, including Weather.com, Weather Underground and mobile and cloud-based assets, for a reported $2 billion in October. IBM will be able to analyze data from more than 2 billion weather reference points, over 40 million smartphones and 50,000 airplane flights per day, letting it offer a broad range of data-driven products and services to more than 5,000 clients in the media, aviation, energy, insurance and government industries. IBM said it can provide predictive weather analytics along with real-time analysis of social media chatter, detailed understanding of transportation flows and other data that will benefit retailers and distributors. The Weather Co. assets will serve as the foundation of a new Watson unit focused on the Internet of Things (IoT). Early this year, IBM announced that it would invest $3 billion to build out IoT products and services. “The more we do this, the smarter Watson gets and the smarter AI gets,” said Kenny. As to why AI is becoming more widespread: “It works,” Kenny said. “Users of AI are saving time and money. They’re making faster decisions and getting better outcomes.” An analysis of Facebook and Alphabet’s Google by research firm Innography shows a surge in AI patent filings that began in 2010. Alphabet currently has more than 3,000 AI patents that are active or pending government approval. Facebook has about 870. AI Knows Where You Live Facebook last June opened an artificial intelligence lab in Paris with a goal of improving the way users interact on the world’s largest social network. “It’s our hope that this research will ultimately help us make services like News Feed, photos and search even better and enable an entirely new set of ways to connect and share,” Facebook said at the time. It also has AI research teams at its Menlo Park, Calif., headquarters and in New York. Facebook in February revealed its Connectivity Lab project. It used AI to analyze 8.3 million square miles of land, using roads, schools and other structures to determine where and how many people live in a given area. That can tell Facebook’s Aquila drones where to go to provide Internet access to less-developed areas, as part of the company’s Internet.org initiative. “This data will give us a greater understanding of how populations are dispersed, so governments and others can prioritize investments in infrastructure, from transportation to healthcare and education,” Facebook said.