Advanced searches left 3/3
Search only database of 8 mil and more summaries

Deepmind Stock

Summarized by PlexPage
Last Updated: 02 July 2021

* If you want to update the article please login/register

General | Latest Info

Artificial Intelligence is a misunderstood term, thanks in part to dystopian views of technology across pop culture, from the iconic Terminator to Cylons in Battlestar Galactica to HAL 9000 in 2001: Space Odyssey. In reality, most scientists working on Artificial Intelligence arent trying to simulate true human intelligence at all. They are simply trying to create practical machines capable of analyzing data and making decisions to achieve their goal. Case in point salesforce. Com CRM, + 0. 32 % have a valuable Artificial Intelligence application called Einstein that it provides to clients. This AI engine helps marketing and sales teams by suggesting which customers are most valuable, and which products they are most likely to buy. Not only is that a far-less sinister example of AI, it is also an exemplary of how businesses can use this technology to create serious profits. Salesforce stock, for example, is up 40 % year-to-date compared with less than 15 % for the broader S & P 500 SPX, + 0. 24 %. In fact, most practical applications of Artificial Intelligence are side-by-side with Big Data and cloud-computing applications that many investors are already familiar with. Think of Artificial Intelligence as just natural next step now that weve created all this Data something has to make sense of it. For example, retailers have been trying for years to harness the predictive power of your shopping habits in order to put offers in front of you. Case-in-point: now-infamous story about TGT,-0. 02 % invested in how to predict when a customer was pregnant. While fears of robot apocalypse may never completely disappear from pop culture, business case for AI is clear in this age of information. The only question is who will provide Artificial Intelligence engines in future, and which companies and investors will profit. If youre interested in playing this emerging-tech trend, here are three AI plays to consider: Google parent Alphabet Inc. GOOGL, + 1. 29 % GOOG, + 1. 22 % made a splash few years ago as it seem to be diving into deep machine learning with the acquisition of DNNresearch, DeepMind Technologies, and JetPac among others. Flurry of acquisitions in 2013 and 2014 made waves at time, and in the near term were seen as incrementally improving areas of Googles internet business, such as improving search or providing better bidding on ad rates. But the tech giant hasnt taken its eye off the ball in intervening years, and overlooking its long-term commitment to AI would be a mistake. Just like it has cemented its role in the smartphone ecosystem with its Android operating system, Google is pushing hard to share its open-source TensorFlow machine learning software with developers and companies of all sizes, while many companies like Amazon. Com AMZN, + 0. 32 % are using AI internally to improve customer experience or to create products like voice assistant Alexa, Google has opened up gates and is welcoming the world into its AI ecosystem.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Baidu (BIDU)

Chinese AI and search conglomerate Baidu joined the growing list by announcing plans to train five million AI developers by 2025 while deploying an equal number of AI Cloud servers across its 10 datacenters by 2030. Beijing infrastructure initiative will be new driver for China's economic development in coming decades, and emerging technologies such as AI, Cloud computing, 5G, IoT and blockchain are its key technological pillars, say Baidu CTO Haifeng Wang. As an AI platform company, Baidu will use its many achievements and years of practical experience in AI Technology to help speed up development of new infrastructure and facilitate implementation of AI so that all industries can leverage it for unprecedented new momentum. Beijing-base tech titan notes that its goal of five million AI Cloud servers amounts to about half of global shipments during 2019. Consider China's leading AI developer, Baidu tout its PaddlePaddle deep learning platform used to develop AI applications delivered by Baidu Brain via Baidu Cloud, China's largest public Cloud service. As is its AI Cloud. Along with more than 10 000 worldwide AI patents, Baidu claims the largest number of Chinese patents in areas ranging from speech recognition and natural language Processing to knowledge graphs and self-driving vehicles. It also claim growing list of AI chip sets, including its Kunlun chip for industrial applications and its Honghu voice chip. Baidu recently announced a manufacturing deal with Samsung Electronics to begin manufacturing the Kunlun Cloud-to-edge AI chip earlier this year. Beyond Technology development and infrastructure deployment is an emerging issue of nurturing AI talent. China is pouring vast resources into training the next generation of AI developers, and Baidu says it is funding deep learning and other AI courses at China's top universities. A recent study tracking global AI talent found the US nevertheless maintain large lead in cutting-edge AI Research, with nearly 60 percent of leading AI experts working for US companies and universities. By far the largest employer is Google, whose Google Brain and DeepMind units account for more than 90 scientific papers during last year's Conference on Neural Information Processing Systems. Researcher MacroPolo, which tracks Chinese economic development, notes in its AI study that many top researchers at US companies and universities are immigrants. The majority are Chinese researchers who come to the US to study and work. Without researchers from abroad, America's lead in talent would likely be considerably diminish, MacroPolo concludes in its recent analysis of AI Conference Research papers. Base on where AI researchers earn their undergraduate degree, analysts find that 29 percent come from China while only 20 percent earn degrees at US universities. By contrast, vast majority of Chinese AI ph. D students88 percentwork in the US after completing graduate school, MacroPolo report. After Google, top five institutions for AI Research are Stanford University, Carnegie Mellon University, Massachusetts Institute of Technology and Microsoft Research, in that order. Only two Chinese institutions, Tsinghua University and Peking University, are among the top 25, according to MacroPolo study.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

NVIDIA

While NVIDIA Corp.-Get Report has received a lot of attention lately from the cryptocurrency craze, NVIDIA is also one of the biggest beneficiaries from the increasing popularity of machine learning. That's because NVIDIA invested heavily in creating CUDA for its GPUs, platform that enables machine learning acceleration on NVIDIA hardware. The Datacenter business has been one of NVIDIA's fastest-growing segments in recent years, as more commercial GPU users come online. Today, all of the major cloud computing services offer computing time on NVIDIA GPUs, and AI-specific chips like NVIDIA's Titan V are finding difficulty keeping up with on-premise customer demand. As big data gets even bigger, demand for high-powered NVIDIA hardware should continue to swell. Google and NVIDIA are holdings in Jim Cramer's Action alert PLUS Charitable Trust Portfolio. Want to be alert before Cramer buys or sells them? Learn more now. This article is commentary by an independent contributor. At time of publication, author hold no positions in Stocks mention.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

IBM

AI is nothing new for IBM. The company has been developing this type of technology for many years. For example, back in 1985, it developed its AI computer called Deep Blue. Deep Blue actually beat chess world champion Garry Kasparov in 1996. Then in 2011, IBM created Watson to take on the best players on the quiz show Jeopardy!. Computer won. IBM has definitely had its troubles. But investments in AI and other cutting-edge technologies have been making a difference. Note that during over recent 12 month period, IBMs Strategic Imperatives, which include cloud computing, security, analytics, Big Data and mobile, generate 40 billion, more than 50 % of itstotal revenues. This has helped improve the growth rate of the overall business. IBM stock also has an attractive dividend yield, which is at 4. 9 %. This is one of highest in the tech industry. And its valuation is reasonable as well. Consider that the forward P / E ratio is only 1ten.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Micron

Micron Technology manufactures memory chips, including dynamic random-access memory and NAND flash memory found in solid-state drives. Most of what companies make are commodity products, meaning that supply and demand dictate pricing. This leads to sometimes brutal cycles where oversupply of chips pushes down prices. In the long run, demand for memory chips will only grow, and that is especially true in the AI industry. Self-driving cars are a good example. All sensors and cameras produce a lot of data-Micron estimate it at around 1 GB per second. Back in 2018, company forecast that fully autonomous vehicle would require 74 GB of DRAM and 1 TB of NAND, and that there would be 26 million vehicles equipped with Level 3 autonomy by 2025. For comparison, PC today may have 16 GB of RAM and 1 TB of NAND. Outside of self-driving cars, data centers running AI workloads need plenty of memory as well. So do smartphones that may be doing AI work. Newer iPhones, for example, do all sorts of AI magic with camera to produce improved images. Investing in Micron will come with ups and downs due to the nature of its business. Even though AI will drive increased demand for memory chips in the long run, supply and demand will reign supreme in the short run. But if you have a stomach for volatile stock, Micron isnt bad way to bet on AI.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Deep Blue to DeepMind

In early December, researchers at DeepMind, artificial-Intelligence company owned by Googles parent corporation, Alphabet Inc., File dispatch from frontiers of Chess. A year earlier, on Dec. 5 2017, team had stunned Chess World with its announcement of AlphaZero, machine-Learning algorithm that had Master not only Chess but shogi, or Japanese Chess, and Go. Algorithms start with no knowledge of games beyond their basic rules. It then plays against itself millions of times and learns from its mistakes. In a matter of hours, algorithm has become the best player, human or computer, world has ever see. Details of AlphaZeros achievements and inner workings have now been formally peer-reviewed and published in the journal Science this month. The new paper addresses several serious criticisms of the original claim. Consider those concerns dispel. AlphaZero has not grown stronger in the past twelve months, but evidence of its superiority has. It clearly displays a breed of intellect that humans have not seen before, and that we will be mulling over for a long time to come. Computer Chess has come a long way over the past twenty years. In 1997, IBMs Chess-playing program, Deep Blue, managed to beat the reigning Human World champion, Garry Kasparov, in a six-Game Match. In retrospect, there was little mystery in this achievement. Deep Blue could evaluate 200 million positions per second. It never gets tired, never blunders in calculation and never forgets what it had been thinking moments earlier. For better and worse, it plays like a machine, brutally and materialistically. It could out-compute Mr. Kasparov, but it couldnt outthink him. In Game 1 of their match, Deep Blue greedily accepted Mr. Kasparovs sacrifice of rook for bishop, but lost Game 16 moves later. The current generation of the world's strongest Chess programs, such as Stockfish and Komodo, still play in this inhuman style. They like to capture opponents ' pieces. They defend like iron. But although they are far stronger than any human player, these Chess engines have no real understanding of the game. They have to be tutored in basic principles of Chess. These principles, which have been refined over decades of human grandmaster experience, are program into engines as complex evaluation functions that indicate what to seek in position and what to avoid: how much to value king safety, piece activity, pawn structure, control of center, and more, and how to balance trade-offs among them. Today, Chess engines, innately oblivious to these principles, come across as brutes: tremendously fast and strong, but utterly lacking insight. All of that has changed with the rise of machine learning. By playing against itself and updating its Neural network as it learns from experience, AlphaZero discovers principles of Chess on its own and quickly becomes the best player ever. Not only could it have easily defeat all the strongest human masters, it didnt even bother to try it crushed Stockfish, reigning computer World champion of Chess.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Exploiting AI Internally

The Holy grail of high finance doesnt look like much: eight rows of servers enshrine in a black metal frame. But inside this austere enclosure, incredible alchemy IS taking place. Four hundred computers blink and hum as market data IS digested at a rate of One quadrillion calculations per second, firing order requests to electronic traders in Chicago, 2 000 miles away. Outside containment, bank of 10 glowing monitors displays results as money rolls back in. Even now, as the world economy slumps into recession, Jeff Glickman and his boutique investment firm, J4 Capital, are quietly making gains. Suffice it to say were making a profit in this market, he say. This somewhat understate miracle that Glickman claims to have perform. When we speak on March 20, J4 Capital was up nearly 4 % for the year, according to internal documents Glickman share, while the Dow Jones Industrial Average was down nearly 27 %, a heroic beat of nearly 31 percentage points. Many other hedge funds were down by double digits and teetering. When we spoke again on May 7, he was approaching 5 % return. Most financial engineers believe that it is impossible for a machine, leave to its own devices, to beat the stock market. Data IS too noisy, too random to be predictable. Observable trading records are Limit to past hundred years, and the law of averages IS relentless. Any signal that is obvious enough to exploit absent inside informationbarrels of oil prices nearly free, for examplewill, quickly be discovered and eliminated by competitors. While some quantitative hedge funds use algorithms to make high-frequency trades, they must frequently be reprogrammed and refine. All this competition leaves slim margins for profit. An exceptional trader would be thrilled with 51 % success ratesimilar to house edge at Las Vegas blackjack table. Renaissance Technologies, perhaps the most profitable quant firm in the world, has generated vast fortune by leveraging bets with these odds. J4 Capital, which has only two other employees, claims to have a success rate of nearly 60 %. Glickman himself knew little about finance. The 59-year-old computer scientist has never worked on Wall Street or for any big bank. For that reason, his supercomputer doesnt leverage its bets or trade in derivatives, which limit, for now, amount of money J4 can make. Nor does Glickman write an investment algorithm to tell machine which input to use. Instead, Glickman say, he created autodidactic superintelligence that could reprogram itself. Glickman got computer bug early. One day, when he was around six, his mother asked him to change batteries on the transistor radio. He wondered instead about the electronics inside. His mother was impressed by his curiosity, so she enlisted a family friend who was an engineer at Sperry Univac, early computer company, to teach her son everything he know. By time I was seven, I was building my own circuits, Glickman say. And by the time I was nine, I had Build my own computer.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Yext (YEXT)

Artificial Intelligence is an industrial, as well as scientific paradigm shift with real potential to disrupt the current business status quo. The general public is thrilled by its recent developments and at the same time anxious about possible scenarios of its application. Enterprises are rushing to lay their hands on promising AI software to improve their productivity and enhance their revenue streams. Whereas, investors who are pooling substantial funds might still find IT challenging to identify potentially successful projects, startups, and companies relying on AI. Despite general optimism surrounding the progress of AI, IT is necessary to understand underlying concepts and possible implications associated with this technology before investing in IT. Read on to find out about the most relevant terms, techniques, and critical factors to consider when investing in AI, where value lies for investors, and learn about the most profitable AI stocks.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Sources

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

logo

Plex.page is an Online Knowledge, where all the summaries are written by a machine. We aim to collect all the knowledge the World Wide Web has to offer.

Partners:
Nvidia inception logo

© All rights reserved
2021 made by Algoritmi Vision Inc.

If you believe that any of the summaries on our website lead to misinformation, don't hesitate to contact us. We will immediately review it and remove the summaries if necessary.

If your domain is listed as one of the sources on any summary, you can consider participating in the "Online Knowledge" program, if you want to proceed, please follow these instructions to apply.
However, if you still want us to remove all links leading to your domain from Plex.page and never use your website as a source, please follow these instructions.