INTC - Intel Corporation

NasdaqGS - NasdaqGS Real Time Price. Currency in USD
58.22
+0.32 (+0.55%)
At close: 4:00PM EST
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Previous Close57.90
Open57.49
Bid0.00 x 3100
Ask0.00 x 4000
Day's Range57.41 - 58.30
52 Week Range42.86 - 59.59
Volume13,917,337
Avg. Volume18,557,889
Market Cap251.865B
Beta (3Y Monthly)0.93
PE Ratio (TTM)13.63
EPS (TTM)4.27
Earnings DateJan. 22, 2020 - Jan. 27, 2020
Forward Dividend & Yield1.26 (2.16%)
Ex-Dividend Date2019-11-06
1y Target Est56.53
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  • Investing.com

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  • Bull of the Day: Applied Materials, Inc. (AMAT)
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  • Apple, Intel file antitrust case against SoftBank-owned firm over patent practices
    Reuters

    Apple, Intel file antitrust case against SoftBank-owned firm over patent practices

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  • AMD at Supercomputing 2019: New Platforms, Deal Wins & More
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  • NVIDIA & Microsoft Intend to Democratize Use of Supercomputer
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  • Accenture, Airbus, GE and Hitachi Join Intel Neuromorphic Research Community
    Business Wire

    Accenture, Airbus, GE and Hitachi Join Intel Neuromorphic Research Community

    What’s New: Today, Intel announced the first corporate members – Accenture, Airbus, GE and Hitachi – to join the fast-growing Intel Neuromorphic Research Community (INRC). The INRC has tripled in size over the past year and now has more than 75 organizations, spanning leading universities around the world, government labs, neuromorphic startup companies, and now several Fortune Global 500 members.

  • Intel at Supercomputing 2019: Xe Architecture GPUs & More
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  • Investing.com

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  • Business Wire

    Lenovo and Intel Fuel Harvard University’s First Liquid-Cooled Supercomputer, Create Visionary Council to Drive Broad Adoption of Exascale Technology

    RALEIGH, N.C.-- -- Lenovo and Intel deliver advanced supercomputing infrastructure to enable discoveries into earthquake forecasting, predictions on the spread of disease and star formation Harvard University Faculty of Arts and Sciences Research Computing’s newest supercomputing cluster performs 3-4x faster with the upgrade of Lenovo’s ThinkSystem SD650 NeXtScale servers with Neptune™ liquid cooling ...

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  • Intel Unveils New GPU Architecture with High-Performance Computing and AI Acceleration, and oneAPI Software Stack with Unified and Scalable Abstraction for Heterogeneous Architectures
    Business Wire

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  • Quantum Leap for Computing Is a Small Step for Computers
    Bloomberg

    Quantum Leap for Computing Is a Small Step for Computers

    (Bloomberg Opinion) -- In a landmark paper published in 1950, the mathematician Alan Turing proposed the eponymous Turing Test to decide whether a computer can demonstrate human-like intelligence. To pass the test, the computer must fool a human judge into believing it’s a person after a five-minute conversation conducted via text. Turing predicted that by the year 2000, a computer would be able to convince 30% of human judges; that criterion became a touchstone of artificial intelligence.Although it took a bit longer than Turing predicted, a Russian chatbot presenting itself as a 13-year-old Ukrainian boy named Eugene Goostman was able to dupe 33% of judges in a competition held in 2014. Perhaps the cleverest aspect of the machine’s design was that its teenage disguise made it more likely that people would excuse its broken grammar and general silliness. Nevertheless, the strategy of misdirection comes across as transparent and superficial in conversations the chatbot had with skeptical journalists — so much so that one marvels not at the computer’s purported intelligence, but at the gullibility of the judges. Sadly, conquering the Turing Test has brought us no closer to solving AI's big problems.Last month, quantum computing achieved its own controversial milestone. This field aims to harness the laws of quantum mechanics to revolutionize computing. Classical computers rely on memory units called bits that encode either zero or one, so a state of the memory is a sequence of zeros and ones. Quantum computers, by contrast, use qubits, each of which encodes a “combination” of zero and one. In a quantum computer, multiple qubits interact, which means that each of the exponentially(1) many sequences of bits is represented simultaneously.The key question is whether this strange power can be exploited to perform computations that are beyond the reach of classical computers. Demonstrating even one such computation, however contrived, would lead to “quantum supremacy” — a term coined by physicist John Preskill of the California Institute of Technology in 2012. By this standard, Google appears to have achieved quantum supremacy. Specifically, the company said in October that its team used a 53-qubit quantum computer to generate random sequences of bits, which depend on controlled interactions between its qubits. By Google’s calculations it would take 10,000 years to carry out the same task using classical computation.(2) There is no doubt that controlling a 53-qubit quantum computer is a feat of science and engineering. As Preskill put it, “the recent achievement by the Google team bolsters our confidence that quantum computing is merely really, really hard,” rather than being “ridiculously hard.”As long as Google’s quantum computer works as intended, however, its dominance isn’t surprising — because the competition is rigged. It’s a bit like building a robotic hand that flips coins according to given parameters (such as, totally off the top of my head, the angle between the normal to the coin and the angular momentum vector), and then challenging a classical computer to generate sequences of heads and tails that obey the same laws of physics. This robot hand would perform astounding feats of coin-flipping but wouldn’t be able to do kindergarten arithmetic — and neither can Google’s quantum computer.It’s unclear, therefore, whether quantum supremacy is a meaningful milestone in the quest to build a useful quantum computer. To mention just one major obstacle (there are several), reliable quantum computing requires error correction. The catch is that quantum error correction protocols themselves demand fairly reliable qubits — and lots of them.In some ways, quantum supremacy is akin to iconic AI milestones like the Turing Test, or IBM’s chess victory over Gary Kasparov in 1997, which was also an engineering tour de force. These achievements demonstrate specialized capabilities and garner widespread attention, but their impact on the overarching goals of their respective fields may ultimately be limited.The danger is that excessive publicity creates inflated expectations of an imminent revolution in computing, despite measured commentary from experts. AI again provides historical precedent: The field has famously gone through several AI winters — decades in which talent fled and research funding ran dry — driven in large part by expectations that failed to materialize.Quantum computing research started three decades after AI, in the 1980s, and experienced a burst of excitement following the invention in 1994 by the Massachusetts Institute of Technology mathematician Peter Shor of a quantum algorithm that would, in theory, crush modern cryptography. But eventually the dearth of, well, quantum computers caught up with quantum computing, and by 2005 the field was experiencing a massive downturn. The current quantum spring started only a few years ago; its signs include a surge of academic research as well as major investments by governments and tech giants like Alphabet Inc., International Business Machines Corp. and Intel Corp.Quantum computing and AI are two distinct fields — despite what whoever came up with the name Google AI Quantum would have you believe — and what is true for one isn't necessarily true for the other. But quantum computing can learn from AI's much longer career as an alternatively overhyped and underappreciated field. I am tempted to say that the chief lesson is “winter is coming,” but it is actually this: the pursuit of artificial milestones is a double-edged blade.(1) I am reminded of a mathematician’s plea to stop abusing the word “exponentially”; here I am using it in a way he would approve of.(2) The calculation was credibly disputed by IBM, but both companies agree that quantum computers are vastly more efficient than classical computers at this particular task.To contact the author of this story: Ariel Procaccia at arielpro@cs.cmu.eduTo contact the editor responsible for this story: Jonathan Landman at jlandman4@bloomberg.netThis column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.Ariel Procaccia is an associate professor in the computer science department at Carnegie Mellon University. His areas of expertise include artificial intelligence, theoretical computer science and algorithmic game theory.For more articles like this, please visit us at bloomberg.com/opinion©2019 Bloomberg L.P.

  • Investing.com

    StockBeat: AMD Gets Some Data Center Wall Street Love

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  • Reuters

    Former Apple chip executives found company to take on Intel, AMD

    NUVIA Inc was founded by Gerard Williams III, Manu Gulati and John Bruno in early 2019 and is developing a processor code-named Phoenix. The company on Friday said it raised $53 million from Dell Technologies Capital and several Silicon Valley firms, which will help it expand from 60 employees to about 100 by the end of this year.

  • Business Wire

    Intel Board of Directors Elects New Director

    Intel Corporation today announced that James (Jim) J. Goetz was elected to Intel’s board of directors. “Jim has a keen understanding of how technology is evolving and a strong track record helping technology companies capitalize on disruptive innovation,” said Intel Chairman Andy Bryant. Goetz, 54, has served as a partner of Sequoia Capital, a venture capital firm, since June 2004.

  • Bloomberg

    Applied Materials Projects Strong Sales on Bounceback in Demand

    (Bloomberg) -- Applied Materials Inc. gave a sales forecast for the current quarter that topped analysts’ estimates, suggesting a slump in orders for chipmaking equipment is ending.The company is the largest maker of machinery used in the manufacture of semiconductors, which are among the most important parts of the electronics supply chain. Customers of the Santa Clara, California-based company include Samsung Electronics Co., Intel Corp. and Taiwan Semiconductor Manufacturing Co., giving it a reach that makes its results and forecasts an important early indicator of business confidence. Intel and other chipmakers order equipment months in advance of starting new factories and production lines.Key InsightsFiscal first-quarter sales will be about $4.1 billion, Applied Materials said Thursday in a statement. That compares with analysts’ average estimate of $3.71 billion, according to data compiled by Bloomberg.Adjusted earnings per share will be 87 cents to 95 cents, the company said. Analysts projected 75 cents a share.The results “reflect a healthy uptick in demand for semiconductor equipment, combined with strong execution across the company,” Chief Executive Officer Gary Dickerson said in the statement.Chip-equipment makers often experience wild earnings swings. Machines cost tens of millions of dollars each. Delaying factory build outs is one of the fastest ways a chipmaker can preserve cash when they’re unsure of future demand.Net income was $698 million, or 75 cents a share in the period ended Oct. 27, compared with $757 million, or 77 cents a share, a year earlier.Revenue was little changed at $3.75 billion. Analysts were looking for $3.68 billion.Stock ReactionShares rose about 4% in extended trading after the announcement. The stock closed at $56.96 in New York and has increased 74% this year.More InformationFor more details, click here.To see the statement, click here.To contact the reporter on this story: Ian King in San Francisco at ianking@bloomberg.netTo contact the editors responsible for this story: Jillian Ward at jward56@bloomberg.net, Andrew Pollack, Alistair BarrFor more articles like this, please visit us at bloomberg.com©2019 Bloomberg L.P.