|Bid||0.00 x 3100|
|Ask||0.00 x 4000|
|Day's Range||57.41 - 58.30|
|52 Week Range||42.86 - 59.59|
|Beta (3Y Monthly)||0.93|
|PE Ratio (TTM)||13.63|
|Earnings Date||Jan. 22, 2020 - Jan. 27, 2020|
|Forward Dividend & Yield||1.26 (2.16%)|
|1y Target Est||56.53|
Despite the U.S.-China trade setback, stocks could still climb in 2019 and beyond, and the tech industry remains a key growth driver. Therefore, we searched for tech companies with our Zacks Stock Screener that also pay a dividend...
The latest U.S.-China trade war news. President Trump's Apple factory trip. Retail earnings, including Target. And why Applied Materials (AMAT) is a Zacks Rank 1 (Strong Buy) stock right now, all on today's episode of Free Lunch...
HP's (HPQ) fourth-quarter fiscal 2019 results are likely to reflect high demand in the commercial PC market. However, weakness in the Printing business might have posed a threat to the stock.
Investing.com - Advanced Micro Devices (NASDAQ:AMD) has racked up impressive gains this year. Before Thursday, shares were up more than 120%. But one Wall Street analyst downgraded AMD Thursday and warned that investors are likely to cash in on the chipmaker's rally in the year ahead.
Apple Inc and Intel Corp on Wednesday filed an antitrust lawsuit against Fortress Investment Group, alleging the SoftBank Group Corp unit stockpiled patents to hold up tech firms with lawsuits demanding as much as $5.1 billion. The lawsuit follows an earlier case that Intel filed against Fortress in October. Intel withdrew that lawsuit and on Wednesday filed a new version in the U.S. District Court for the Northern District of California with Apple joining as a plaintiff.
AMD unveils new platforms and declares new deal wins on strength in its 2nd Gen EPYC processors and Radeon Instinct GPU accelerators at Supercomputing 2019 event.
NVIDIA (NVDA) and Microsoft attempt to democratize the utilization of supercomputer by enabling companies to rent the robust capabilities of one according to demand.
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 (INTC) makes a slew of announcements at Supercomputing 2019 event pertaining to its latest GPUs based on Xe architecture, and divulged details on OneAPI software and Aurora exascale system.
Investing.com – Chip stocks climbed Monday as semiconductor companies like Micron Technology that count Huawei as an important customer were given a lifeline after the U.S. extended a license that lifts restrictions on U.S. companies from selling or transferring technology to Huawei.
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 ...
We highlight blue-chip companies slated to gain in the near term as they have large market capitalization, strong balance sheet and solid cash flow.
Intel launches oneAPI, a unified and scalable programming model to harness the power of diverse computing architectures in the era of HPC/AI convergence. Intel unveils additional architectural details of the Aurora Supercomputer, delivering convergence at exascale at Argonne National Laboratory. At Supercomputing 2019, Intel unveiled its vision for extending its leadership in the convergence of high-performance computing (HPC) and artificial intelligence (AI) with new additions to its data-centric silicon portfolio and an ambitious new software initiative that represents a paradigm shift from today’s single-architecture, single-vendor programming models.
We searched for semiconductor stocks utilizing our Zacks Stock Screener that investors might want to consider buying ahead of what could be a strong year for chip companies in 2020...
(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 firstname.lastname@example.orgTo contact the editor responsible for this story: Jonathan Landman at email@example.comThis 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 – The good times are returning to data-center products as clients are set to ramp-up spending, likely leading to higher deamnd for AMD’s chips, RBC said as it upgraded its price target on the chipmaker Friday.
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.
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 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 firstname.lastname@example.orgTo contact the editors responsible for this story: Jillian Ward at email@example.com, Andrew Pollack, Alistair BarrFor more articles like this, please visit us at bloomberg.com©2019 Bloomberg L.P.