Artificial intelligence (AI) in Medicine Market is analyzed with industry experts in mind to maximize return on investment by providing clear information needed for informed business decisions. This research will help both established and new entrants to identify and analyze market needs, market size and competition. It explains the supply and demand situation, the competitive scenario, and the challenges for market growth, market opportunities and the threats faced by key players.

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Top Key Players Profiled in This Report: Welltok, Inc., Intel Corporation, Nvidia Corporation, Google Inc., IBM Corporation, Microsoft Corporation, General Vision, Inc., Enlitic, Inc., BioXcel Corporation, Berg Health etc.

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Detailed outline of the Global Artificial intelligence (AI) in Medicine Market includes a comprehensive analysis of different verticals of businesses. North America, Latin America, Asia-Pacific, Africa, and Europe have been considered for the studies on the basis of several terminologies.

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Artificial intelligence (AI) in Medicine Market Global Industry Analysis, By Manufacturers, Segmentation, Application, Demand And Forecast By 2026 -...

This year is likely to be remembered for the COVID-19 pandemic and for a significant presidential election, but there is a new contender for the most spectacularly newsworthy happening of 2020: the unveiling of GPT-3. As a very rough description, think of GPT-3 as giving computers a facility with words that they have had with numbers for a long time, and with images since about 2012.

The core of GPT-3, which is a creation of OpenAI, an artificial intelligence company based in San Francisco, is a general language model designed to perform autofill. It is trained on uncategorized internet writings, and basically guesses what text ought to come next from any starting point. That may sound unglamorous, but a language model built for guessing with 175 billion parameters 10 times more than previous competitors is surprisingly powerful.

The eventual uses of GPT-3 are hard to predict, but it is easy to see the potential. GPT-3 can converse at a conceptual level, translate language, answer email, perform (some) programming tasks, help with medical diagnoses and, perhaps someday, serve as a therapist. It can write poetry, dialogue and stories with a surprising degree of sophistication, and it is generally good at common sense a typical failing for many automated response systems. You can even ask it questions about God.

Imagine a Siri-like, voice-activated assistant that actually did your intended bidding. It also has the potential to outperform Google for many search queries, which could give rise to a highly profitable company.

GPT-3 does not try to pass the Turing Test by being indistinguishable from a human in its responses. Rather, it is built for generality and depth, even though that means it will serve up bad answers to many queries, at least in its current state. As a general philosophical principle, it accepts that being weird sometimes is a necessary part of being smart. In any case, like so many other technologies, GPT-3 has the potential to rapidly improve.

It is not difficult to imagine a wide variety of GPT-3 spinoffs, or companies built around auxiliary services, or industry task forces to improve the less accurate aspects of GPT-3. Unlike some innovations, it could conceivably generate an entire ecosystem.

There is a notable buzz about GPT-3 in the tech community. One user in the U.K. tweeted: "I just got access to gpt-3 and I can't stop smiling, i am so excited." Venture capitalist Paul Graham noted coyly: "Hackers are fascinated by GPT-3. To everyone else it seems a toy. Pattern seem familiar to anyone?" Venture capitalist and AI expert Daniel Gross referred to GPT-3 as "a landmark moment in the field of AI."

I am not a tech person, so there is plenty about GPT-3 I do not understand. Still, reading even a bit about it fills me with thoughts of the many possible uses.

It is noteworthy that GPT-3 came from OpenAI rather than from one of the more dominant tech companies, such as Alphabet/Google, Facebook or Amazon. It is sometimes suggested that the very largest companies have too much market power but in this case, a relatively young and less capitalized upstart is leading the way. (OpenAI was founded only in late 2015 and is run by Sam Altman).

GPT-3 is also a sign of the underlying health and dynamism of the Bay Area tech world, and thus of the U.S. economy. The innovation came to the U.S. before China and reflects the power of decentralized institutions.

Like all innovations, GPT-3 involves some dangers. For instance, if prompted by descriptive ethnic or racial words, it can come up with unappetizing responses. One can also imagine that a more advanced version of GPT-3 would be a powerful surveillance engine for written text and transcribed conversations. Furthermore, it is not an obvious plus if you can train your software to impersonate you over email. Imagine a world where you never know who you are really talking to "Is this a verified email conversation?" Still, the hope is that protective mechanisms can at least limit some of these problems.

We have not quite entered the era where "Skynet goes live," to cite the famous movie phrase about an AI taking over (and destroying) the world. But artificial intelligence does seem to have taken a major leap forward. In an otherwise grim year, this is a welcome and hopeful development. Oh, and if you would like to read more, here is an article about GPT-3 written by GPT-3.

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Opinion: Artificial intelligence is the hope 2020 needs - Crain's Cleveland Business

As it has been observed that many cities are forced to go back to lockdown again with the rise of the number of cases of coronavirus. Due to the emerging lockdowns, public transport will be facing new challenges in the days ahead. They have to avoid overcrowding buses and trains to prevent the virus from spreading ensuring to maintain the overall number of passengers to sustain the system. Meanwhile, the commuters are temporarily returning to public transport but it can be used widely if they see it as a safe way to reach their destinations.

According to the safety measure rules to protect against Covid-19 are to maintain social distancing. Overcrowding poses the risk to the major transmission of coronavirus and other diseases. Therefore, there is a need to flatten the typical morning and evening peak hours of passenger numbers. With the lack of passengers, this means the public transport companies have to put relatively frequent trains and buses all day long rather than back-to-back transport rush.

An all-day service provides special benefits and reduces passenger density resulting in social distancing. This also benefits drivers as they are less likely to change their shifts and passengers can rely on fairly frequent buses all day long. However, with the surge in the cases of Covid-19 infection, it can anytime affect the ridership demand. This can happen so quickly that transport companies wont have that much time to prepare and adjust. Therefore, there is a need to maintain the flexibility to reach within days or even hours and implements the changes that usually take months of preparation. Here is when digital technologies like Artificial Intelligence comes in the view.

Artificial Intelligence can help in maintaining a large amount of data the level of passengers demand, number of drivers on duty, availability of buses and trains, maximum hours driver can work between breaks, as well as the length of each break- and many more which are needed to be taken care of.

With the help of some algorithms, scenarios can be created. They can change the routes and travel times, the update on the schedules will be updated automatically. They can compare the revenue and costs based on different scenarios. It will help to take steps quickly as the circumstances changes, be it lockdown or staggered shifts, like quickly putting extra trains and buses if needed.

AI can also help to solve the unmanageable transport problems. For example, if any transport company wants to add 5% more trips to get passenger numbers over their journey. But they have 14% fewer drivers at hand. It seems impossible to handle. However, AI-driven software can found a way to add more trips with fewer drivers by optimizing the schedule and extending the average shifts by 45 minutes, and providing a necessary break time.

The Artificial Intelligence system that is added to buses is mainly to operate as quickly as possible by providing extra buses when needed to maintain social distancing. Though it sounds simple, it is not. It requires planning in the form of complex algorithms. These algorithms will generate alternative scenarios to figure out which part of the transportation network is needed to be modified to ensure extra vehicles and drivers to be available.

However, transport providers have to make sure that people reach their destination on time even if the schedule changes in a short period. The increase in time duration can lead to unhappy customers. This does not sound any good for business.

There is no saying what transit demand will be there in the upcoming months but cooperating with local government and private institutes to flatten peak hours, using AI for different scenarios management, and monitoring the impact whenever the service changes, will somehow help transportation providers to move ahead. This will actually help the general public to commute safely during the lockdown. Implementing such measures will give public transportation a move towards digitalization.

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How Artificial Intelligence Can Be Used In Public Transport- Will People Be Able To Commute Safely After Covid-19? - Inventiva

August 4th, 2020

1:00 PM - 2:30 PM ET

Today, data-driven decisions are used in everything from credit to education to housing to employment to policing and beyond. This 90-minute session will cover what AI is, how it works, different ways AI is being used today in the legal industry, and some of the challenges with AI, focusing, in particular, on the issue of bias. Our presenter will address whether data-driven decisions are objective and fair, or whether they simply perpetuate bias and the status quo. Using the example of risk-based assessment tools applied in the criminal justice system, she will explore how to balance the competing considerations of the need for broad, representative data sets with the need to protect individual privacy, and what technologists, lawyers, and regulators can and should be doing to meet the challenges and opportunities inherent in data-driven decision-making.

*This webinar will be presented via Zoom - details will be sent via email once registration has been completed.

Speaker:

Maura R. GrossmanResearch ProfessorUniversity of Waterloo

Maura is a Research Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, in Ontario, as well as an e-discovery attorney and consultant in New York City. Previously, Grossman was of counsel at Wachtell, Lipton, Rosen & Katz, where for 17 years, she represented Fortune 100 companies and major financial services institutions in corporate and securities litigation and white-collar criminal and regulatory investigations, and advised the firms lawyers and clients on legal, technical, and strategic issues involving e-discovery and information governance, both domestically and abroad. Grossman is a well-known and influential e-discovery lawyer and a pioneer in the use and evaluation of technology-assisted review.

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[Webinar] ACEDS Detroit Chapter: Fundamentals of Artificial Intelligence and Issues of Bias - August 4th, 1:00 pm - 2:30 pm ET - JD Supra

According to Orbis Research industry statistics, the Global Artificial Intelligence in Medical Imaging Market will inventory a CAGR of about xx% by 2026. This market research report offers a comprehensive analysis of the Artificial Intelligence in Medical Imaging markets growth based on end-users and geography.

This report focuses on the Global Artificial Intelligence in Medical Imaging Market status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Artificial Intelligence in Medical Imaging development in North America, Europe, China, Japan, Southeast Asia, India and Central & South America.

Top Companies:

Google Inc.CiscoIBM Corp.Microsoft Corp.Apple Inc.Salesforce Inc.Infineon Technologies AGIntel Security GroupNVIDIA Corp.Amazon Inc.

Request a sample of this report @ https://www.orbisresearch.com/contacts/request-sample/4869018?utm_source=golden

The research report on Artificial Intelligence in Medical Imaging provides regional market insights, rising growth, business growth factors, application, future guide, characterization, opportunities, future guide, openings, innovation, and in-depth market players along with their revenues. Likewise, the Artificial Intelligence in Medical Imaging research report also evaluates the market growth rate as well the current market value according to the market dynamics as well as the growth prospects. The market analysis offered in this report is assessed on the basis of market data, market trends, and the number of growth potentials. It includes an extensive investigation of the market scenario with the in-depth analysis of their major service providers.

Likewise, the Artificial Intelligence in Medical Imaging research report provides market insights from the huge number of statistics which are collected from robust Artificial Intelligence in Medical Imaging market data such as channel partners, manufacturers, regulatory bodies, as well as decision makers. In addition to this, on the basis of several clients conditions, the Artificial Intelligence in Medical Imaging report produces highly customized data that will help regional as well as global service providers to increase their market position over the globe.

Moreover, the Artificial Intelligence in Medical Imaging research report offers a holistic overview of the Artificial Intelligence in Medical Imaging market, several factors driving the market growth, as well as the companies involved in the Artificial Intelligence in Medical Imaging market. Furthermore, the Artificial Intelligence in Medical Imaging report also provides a detailed value chain analysis of the Artificial Intelligence in Medical Imaging market across the world. In addition to this, every section of the Artificial Intelligence in Medical Imaging research report has offered significant information to provide for service providers to increase their revenue margin, marketing strategy and sales, as well as profit margin. Furthermore, the Artificial Intelligence in Medical Imaging research report used as a tool for getting extensive market analysis, service providers can recognize the required changes into their operation and gain their position across the global market.

Browse the Complete report @ https://www.orbisresearch.com/reports/index/covid-19-impact-on-global-artificial-intelligence-in-medical-imaging-market-size-status-and-forecast-2020-2026?utm_source=golden

Market segment by Type, the product can be split into

Deep LearningComputer VisionOthers

Market segment by Application, split into

NeurologyCardiovascularBreast & LungOther

The study objectives of this report are:To analyze global Artificial Intelligence in Medical Imaging status, future forecast, growth opportunity, key market and key players.To present the Artificial Intelligence in Medical Imaging development in North America, Europe, China, Japan, Southeast Asia, India and Central & South America.To strategically profile the key players and comprehensively analyze their development plan and strategies.To define, describe and forecast the market by type, market and key regions.In this study, the years considered to estimate the market size of Artificial Intelligence in Medical Imaging are as follows:History Year: 2015-2019Base Year: 2019Estimated Year: 2020Forecast Year 2020 to 2026For the data information by region, company, type and application, 2019 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.

Table of Content:Chapter One: Report Overview1.1 Study Scope1.2 Key Market Segments1.3 Players Covered: Ranking by Artificial Intelligence in Medical Imaging Revenue1.4 Market Analysis by Type1.4.1 Global Artificial Intelligence in Medical Imaging Market Size Growth Rate by Type: 2020 VS 20261.4.2 Cloud-based1.4.3 Web-based1.5 Market by Application1.5.1 Global Artificial Intelligence in Medical Imaging Market Share by Application: 2020 VS 20261.5.2 Hospitals1.5.3 Clinics1.5.4 Other1.6 Coronavirus Disease 201Chapter Nine: (Covid-19): Artificial Intelligence in Medical Imaging Industry Impact1.6.1 How the Covid-1Chapter Nine: is Affecting the Artificial Intelligence in Medical Imaging Industry1.6.1.1 Artificial Intelligence in Medical Imaging Business Impact Assessment Covid-191.6.1.2 Supply Chain Challenges1.6.1.3 COVID-19s Impact On Crude Oil and Refined Products1.6.2 Market Trends and Artificial Intelligence in Medical Imaging Potential Opportunities in the COVID-1Chapter Nine: Landscape1.6.3 Measures / Proposal against Covid-191.6.3.1 Government Measures to Combat Covid-1Chapter Nine: Impact1.6.3.2 Proposal for Artificial Intelligence in Medical Imaging Players to Combat Covid-1Chapter Nine: Impact1.7 Study Objectives1.8 Years ConsideredChapter Two: Global Growth Trends by Regions2.1 Artificial Intelligence in Medical Imaging Market Perspective (2015-2026)2.2 Artificial Intelligence in Medical Imaging Growth Trends by Regions2.2.1 Artificial Intelligence in Medical Imaging Market Size by Regions: 2015 VS 2020 VS 20262.2.2 Artificial Intelligence in Medical Imaging Historic Market Share by Regions (2015-2020)2.2.3 Artificial Intelligence in Medical Imaging Forecasted Market Size by Regions (2021-2026)2.3 Industry Trends and Growth Strategy2.3.1 Market Top Trends2.3.2 Market Drivers2.3.3 Market Challenges2.3.4 Porters Five Forces Analysis2.3.5 Artificial Intelligence in Medical Imaging Market Growth Strategy2.3.6 Primary Interviews with Key Artificial Intelligence in Medical Imaging Players (Opinion Leaders)Chapter Three: Competition Landscape by Key Players3.1 Global Top Artificial Intelligence in Medical Imaging Players by Market Size3.1.1 Global Top Artificial Intelligence in Medical Imaging Players by Revenue (2015-2020)3.1.2 Global Artificial Intelligence in Medical Imaging Revenue Market Share by Players (2015-2020)3.1.3 Global Artificial Intelligence in Medical Imaging Market Share by Company Type (Tier 1, Tier Chapter Two: and Tier 3)3.2 Global Artificial Intelligence in Medical Imaging Market Concentration Ratio3.2.1 Global Artificial Intelligence in Medical Imaging Market Concentration Ratio (CRChapter Five: and HHI)3.2.2 Global Top Chapter Ten: and Top 5 Companies by Artificial Intelligence in Medical Imaging Revenue in 20193.3 Artificial Intelligence in Medical Imaging Key Players Head office and Area Served3.4 Key Players Artificial Intelligence in Medical Imaging Product Solution and Service3.5 Date of Enter into Artificial Intelligence in Medical Imaging Market3.6 Mergers & Acquisitions, Expansion PlansContinued.

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Artificial Intelligence in Medical Imaging Market Research Report 2020, Regional Analysis by Key Manufacturers, Application, Types, Growth...

KandJ market research added a new market research report on Global Artificial Intelligence as a Service Market Report 2020 by Key Players, Types, Applications, Countries, Market Size, Forecast to 2026 (Based on 2020 COVID-19 Worldwide Spread) in the database of market research collaterals consisting of overall market scenario with prevalent and future growth prospects, among other growth strategies used by key players to stay ahead of the market.

Report Overview

It is our aim to provide our readers with report for Artificial Intelligence as a Service market, which examines the industry during the period 2015 2026. One goal is to present deeper insight into this line of business in this document. The first part of the report focuses on providing the industry definition for the product or service under focus in the Artificial Intelligence as a Service market report. Next, the document will study the factors responsible for hindering and enhancing growth in the industry. After covering various areas of interest in the industry, the report aims to provide how the Artificial Intelligence as a Service market will grow during the forecast period.

The Artificial Intelligence as a Service market report between the years 2020-2026 will highlight the current value of the industry. At the same time, there is also an estimate of how much this line of business will be worth at the end of the forecast period. As it is our goal to maintain high levels of accuracy at all times, we will take a look at the CAGR of the Artificial Intelligence as a Service market. We make sure that all the information available in this report has excellent levels of readability. One way we achieve this target is by Artificial Intelligence as a Service market segmentation. Going through the report for 2020 -2026 will bring our readers up-to-date regarding this industry.

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COVID-19 can affect the global market in 3 ways: by directly affecting the production and demand, by creating supply chain and market disturbance, and by its financial impact on enterprises and financial markets.

While examining the information from this document, one thing becomes clear, the elements which contribute to increase in demand for the product or service. At the same time, there will be a focus on what drives the popularity of these types of products or services. This report is for those who want to learn about Artificial Intelligence as a Service market, along with its forecast for 2020-2026. Information regarding market revenue, competitive partners, and key players will also be available.

Segmentation

As discussed earlier, there is segmentation in the Artificial Intelligence as a Service market report, to improve the accuracy and make it easier to collect data. The categories which are the dividing factors in the industry are distribution channels, application, and product or service type. With this level of segmentation, it becomes easier to analyze and understand the Artificial Intelligence as a Service market. At the same time, there is emphasis on which type of consumers become the customers in this industry. When it comes to distribution channels, the Artificial Intelligence as a Service market report looks at the different techniques of circulation of the product or service.

Market Analysis By Key Companies

Market Analysis By Type

Market Analysis By Applications

Market Analysis By Regions

Latest Industry News

From this Artificial Intelligence as a Service market report, the reader will also get to learn about the latest developments in the industry. The reason is that these products or services have the potential to disrupt this line of business. If there is information about company acquisitions or mergers, this information will also be available in this portion of the Artificial Intelligence as a Service market report.Additionally, recent trends, mergers and acquisitions, region-wise growth analysis along with challenges that are affecting the growth of the market are also stated in the report.

The Final Report Will Include the Impact of COVID 19 Analysis in This Artificial Intelligence as a Service Industry. Read Full Summary of the Research Study at @ https://www.kandjmarketresearch.com/reports/375966-global-artificial-intelligence-as-a-service-market-report-2020-by-key-players-types-applications-countries-market-size-forecast-to-2026-based-on-2020-covid-19-worldwide-spread

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Artificial Intelligence as a Service Size, Analytical Overview, Growth Factors, Demand, Trends and Forecast to 2026 - Jewish Life News

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San Francisco: The increasing use of artificial intelligence is going to extract a heavy price in power unless the chip industry steps up and heads that off, according to one of the industrys biggest companies.

Data centers are on course to consume 15% of the worlds electricity by 2025, according to Applied Materials Inc., the worlds largest maker of chip equipment. Those giant warehouses of computers currently suck in about 2%, the company said.

AI has the potential to change everything, said Applied Materials Chief Executive Officer Gary Dickerson speaking in a prerecorded remote keynote for the industrys Semicon West conference. But AI has an Achilles heel that unless addressed will prevent it from reaching its true potential. That Achilles heel is power consumption. Training neural networks is incredibly energy-intensive when done with the technology thats available today.

A flood of new devices are getting internet connections, generating more data and increasing the need for more computing power with artificial intelligence to make sense of that new information. Chipmakers, most of which use Applieds machinery, have made their electronic components more energy efficient but not enough, according to Dickerson. The industry needs to come up with new custom designs tailored for AI processing and new ways of connecting those chips, he said.

Widths on the tiny circuits that give chips their functions are measured in billionths of a meter. But to move and store data quickly they require large amounts of power. An Intel Corp. Xeon processor may draw more than 200 watts, as much as an old-fashioned portable tube TV. Put thousands of those processors in close proximity and couple them with all of the other components needed to make a server and the electricity drain adds up.

Applieds CEO made a promise to reduce the companys power footprint and to innovate on the basics of manufacturing and materials to help his customers make more efficient components. One example he gave Tuesday involves a technique for growing tungsten atoms in a vacuum to make more efficient connections between parts of the chip.

Applied will move to 100% renewable energy and cut its carbon footprint by 50% over the next 10 years, Dickerson pledged. Even relatively simple changes in practices can help, he said. Flying an engineer from the U.S. to Asia and back generates about 2 metric tons of carbon dioxide. Applied has learned during the Covid-19 pandemic how to improve remote research and development and customer support, he said, making fewer such trips necessary. Bloomberg

Also read: Siri & Alexa under fire in EUs antitrust inquiry into Internet of things

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Power consumption can explode with increasing use of artificial intelligence - ThePrint

Global Artificial Intelligence in Video Games Market 2020 by Company, Type and Application, Forecast to 2025 conducted by MarketsandResearch.biz presents a better understanding of the current market size, landscape, and development, and status. The report features an overview of the definition, factors, competition, strategic moves taken in recent years. The report highlights the growth opportunities available in the global Artificial Intelligence in Video Games market from 2020 to 2025. It comprises a market assessment of historical data and projections with an appropriate set of assumptions and methodology. The report explores the industrys competitive landscape to consider the domestic and global competition.

How Is The Market Examination Classified In This Report?

The report throws light on categories such as market segments, countries, and product types. This market report covers a top to bottom examination of top worldwide industry players. The global Artificial Intelligence in Video Games market has been studied by researchers to understand the dynamics between diverse factors. The segmentation is covered with charts, graphs, and data. This segmentation encompasses all the necessary aspects of the market right from the production to distribution and behavioral patterns of the end-users.

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NOTE: Our analysts monitoring the situation across the globe explains that the market will generate remunerative prospects for producers post COVID-19 crisis. The report aims to provide an additional illustration of the latest scenario, economic slowdown, and COVID-19 impact on the overall industry.

What Does The Report Cover With Respect To The Regional Landscape of The Market?

The market report, with respect to the geological spectrum of this scope, analyzes examines each geographical segment of the market with supply, import, export, consumption, and production in these regions to provide a complete understanding of the market, covering, North America (United States, Canada and Mexico), Europe (Germany, France, United Kingdom, Russia and Italy), Asia-Pacific (China, Japan, Korea, India, Southeast Asia and Australia), South America (Brazil, Argentina), Middle East & Africa (Saudi Arabia, UAE, Egypt and South Africa). Moreover, the report compares the production value and growth rate of Artificial Intelligence in Video Games market across different geographies.

The market competitive landscapes provide details by topmost manufactures like Ubisoft, NetEase, Sony, EA, Activision Blizzard, Tencent, Google, Playtika, Microsoft, Nintendo, NCSoft, Nexon, Take-Two Interactive, Square Enix, Konami, including capacity, production, price, revenue, cost, gross, gross margin, growth rate, import, export, market share, and technological developments.

The key product type investigation is as per the following: On-Premise, Cloud-based, etc.

The top applications or end-client investigation is: PC, TV, Smartphone & Tablet, etc.

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Global Artificial Intelligence in Video Games Market 2020 with (Covid-19) Impact Analysis: Growth, Latest Trend Analysis and Forecast 2025 - Cole of...

Future Market Insights (FMI)s upcoming research study on the global Artificial Intelligence Chip market lays bare undercurrents and opportunities for key market stakeholders. The report provides in-depth insights on the Artificial Intelligence Chip market through a detailed analysis of key growth drivers, restraints, trends, challenges, and revenue growth based on historical data. Valuable information and forecast statistics covered in the Artificial Intelligence Chip market report will help existing and potential new market players to craft long-term strategies as well as maintain business continuity during a crisis.

COVID-19 Impact Analysis

As with many industries, the recent outbreak of the COVID-19 has adversely affected the industrial automation & equipment industry. The Artificial Intelligence Chip market is no exception. Following governments measures, particularly social distancing norms and shelter-in-place orders, companies active in the Artificial Intelligence Chip market have put their production on a halt. Additionally, movement restrictions have created a logistical nightmare for market players, while the lack of essential status caused a decline in sales.

The FMIs report covers an exclusive chapter on the initial COVID-19 impact on the Artificial Intelligence Chip market. This allows both incumbent companies and new entrants to understand the market scenario during a crisis and helps them make sound decision to gain a distinct competitive edge.

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Artificial Intelligence Chip Market: Segmentation

To analyze the Artificial Intelligence Chip market effectively and efficiently, the information has been segregated into key segments and sub-segments.

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Artificial Intelligence Chip Market: Competition Analysis

The FMIs study presents an extensive analysis of global, regional, and country-level players operating in the Artificial Intelligence Chip market based on their innovative launches, distribution channels, local networks, industrial penetration, production methods, and revenue generation. Furthermore, growth strategies and mergers & acquisitions (M&A) activities associated with the players are enclosed in the Artificial Intelligence Chip market report.

Key players covered in the report include:

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Consumption of Artificial Intelligence Chip to Remain High During 2018 2028 - 3rd Watch News

This year is likely to be remembered for the Covid-19 pandemic and for a significant presidential election, but there is a new contender for the most spectacularly newsworthy happening of 2020: the unveiling of GPT-3.

As a very rough description, think of GPT-3 as giving computers a facility with words that they have had with numbers for a long time, and with images since about 2012.

The core of GPT-3, which is a creation of OpenAI, an artificial intelligence company based in San Francisco, is a general language model designed to perform autofill. It is trained on uncategorised Internet writings, and basically guesses what text ought to come next from any starting point. That may sound unglamorous, but a language model built for guessing with 175 billion parameters 10 times more than previous competitors is surprisingly powerful.

The eventual uses of GPT-3 are hard to predict, but it is easy to see the potential. GPT-3 can converse at a conceptual level, translate language, answer email, perform (some) programming tasks, help with medical diagnoses and, perhaps someday, serve as a therapist. It can write poetry, dialogue and stories with a surprising degree of sophistication, and it is generally good at common sense a typical failing for many automated response systems. You can even ask it questions about God.

Imagine a Siri-like voice-activated assistant that actually did your intended bidding. It also has the potential to outperform Google for many search queries, which could give rise to a highly profitable company.

GPT-3 does not try to pass the Turing test by being indistinguishable from a human in its responses. Rather, it is built for generality and depth, even though that means it will serve up bad answers to many queries, at least in its current state. As a general philosophical principle, it accepts that being weird sometimes is a necessary part of being smart. In any case, like so many other technologies, GPT-3 has the potential to rapidly improve.

It is not difficult to imagine a wide variety of GPT-3 spinoffs, or companies built around auxiliary services, or industry task forces to improve the less accurate aspects of GPT-3. Unlike some innovations, it could conceivably generate an entire ecosystem.

There is a notable buzz about GPT-3 in the tech community. One user in the UK tweeted: I just got access to gpt-3 and I cant stop smiling, I am so excited. Venture capitalist Paul Graham noted coyly: Hackers are fascinated by GPT-3. To everyone else it seems a toy. Pattern seem familiar to anyone? Venture capitalist and AI expert Daniel Gross referred to GPT-3 as a landmark moment in the field of AI.

I am not a tech person, so there is plenty about GPT-3 I do not understand. Still, reading even a bit about it fills me with thoughts of the many possible uses.

It is noteworthy that GPT-3 came from OpenAI rather than from one of the more dominant tech companies, such as Alphabet/Google, Facebook or Amazon. It is sometimes suggested that the very largest companies have too much market power but in this case, a relatively young and less capitalised upstart is leading the way. (OpenAI was founded only in late 2015 and is run by Sam Altman.)

GPT-3 is also a sign of the underlying health and dynamism of the Bay Area tech world, and thus of the US economy. The innovation came to the US before China and reflects the power of decentralised institutions.

Like all innovations, GPT-3 involves some dangers. For instance, if prompted by descriptive ethnic or racial words, it can come up with unappetising responses. One can also imagine that a more advanced version of GPT-3 would be a powerful surveillance engine for written text and transcribed conversations. Furthermore, it is not an obvious plus if you can train your software to impersonate you over email. Imagine a world where you never know who you are really talking to Is this a verified email conversation? Still, the hope is that protective mechanisms can at least limit some of these problems.

We have not quite entered the era where Skynet goes live, to cite the famous movie phrase about an AI taking over (and destroying) the world. But artificial intelligence does seem to have taken a major leap forward. In an otherwise grim year, this is a welcome and hopeful development. Oh, and if you would like to read more, here is an article about GPT-3 written by... GPT-3. Bloomberg

(Tyler Cowen is a Bloomberg Opinion columnist. He is a professor of economics at George Mason University and writes for the blog Marginal Revolution. His books include Big Business: A Love Letter To An American Anti-Hero.)

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Opinion: Artificial Intelligence is the hope 2020 needs - The Star Online