Artificial Intelligence Market Size, Overview, Segmentation And Geographical Forecast Till 2027 …

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Artificial Intelligence Market Size, Overview, Segmentation And Geographical Forecast Till 2027 …

The global artificial intelligence market is expected to rise with an impressive CAGR and generate the highest revenue by 2026. Fortune Business Insights™ in its latest report published this information. The report is titled “Artificial Intelligence (AI) Market Size, Share and Industry Analysis By Component (Hardware, Software, Services), By Technology (Computer Vision, Machine Learning, Natural Language Processing, Others), By Industry Vertical (BFSI, Healthcare, Manufacturing, Retail, IT & Telecom, Government, Others) and Regional Forecast, 2019-2026”. The report discusses research objectives, research scope, methodology, timeline and challenges during the entire forecast period. It also offers an exclusive insight into various details such as revenues, market share, strategies, growth rate, product & their pricing by region/country for all major companies.

For more information, Get sample pdf @ https://www.fortunebusinessinsights.com/enquiry/request-sample-pdf/artificial-intelligence-market-100114

The report provides a 360-degree overview of the market, listing various factors restricting, propelling, and obstructing the market in the forecast duration. The report also provides additional information such as interesting insights, key industry developments, detailed segmentation of the market, list of prominent players operating in the market, and other artificial intelligence market trends. The report is available for sale on the company website.

List of Key Players Mentioned in the Artificial Intelligence Market Research Report:

  • Alphabet (Google Inc)
  • Apple Inc
  • Baidu
  • IBM Corporation
  • IPsoft
  • Microsoft Corporation
  • MicroStrategy, Inc
  • NVIDIA
  • Qlik Technologies Inc
  • Verint Systems Inc

“The Natural Language Processing Segment to Witness Growth Driven by Extensive Usage of AI”

The report classifies the global artificial intelligence (AI) market on the basis of components, technology, industry vertical, and geography. In terms of technology, the market is divided into machine learning, computer vision, natural language processing, and others. Out of these, the natural language processing segment is expected to gain the highest share of the global artificial intelligence (AI) market during the forecast period. This will occur because of the application of AI techniques in analyzing natural language in spoken as well as written forms.

View press release for more information @ https://www.marketwatch.com/press-release/artificial-intelligence-market-key-players-application-demand-industry-research-report-by-regional-forecast-to-2026-2020-06-24

Regional Analysis for Artificial Intelligence Market:

  • North America (the USA and Canada)
  • Europe (UK, Germany, France, Italy, Spain, Scandinavia and Rest of Europe)
  • Asia Pacific (Japan, China, India, Australia, Southeast Asia and Rest of Asia Pacific)
  • Latin America (Brazil, Mexico and Rest of Latin America)
  • Middle East & Africa (South Africa, GCC and Rest of the Middle East & Africa)

Major Table of Contents for Artificial Intelligence Market:

  1. Introduction
  2. Executive Summary
  3. Market Dynamics
  4. Key Artificial Intelligence Market Insights
  5. Global Market Analysis, Insights and Forecast, 2015-2026
  6. North America Market Analysis, Insights and Forecast, 2015-2026
  7. Europe Market Analysis, Insights and Forecast, 2015-2026
  8. Asia Pacific Market Analysis, Insights and Forecast, 2015-2026
  9. The Middle East and Africa Market Analysis, Insights and Forecast, 2015-2026
  10. Latin America Market Analysis, Insights and Forecast, 2015-2026
  11. Competitive Landscape
  12. Global Artificial Intelligence Market Revenue Share Analysis, By Key Players, 2020
  13. Company Profiles
  14. Conclusion

Other Exclusive Reports:

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About Us:
Fortune Business Insights™ offers expert corporate analysis and accurate data, helping organizations of all sizes make timely decisions. Our reports contain a unique mix of tangible insights and qualitative analysis to help companies achieve sustainable growth. Our team of experienced analysts and consultants use industry-leading research tools and techniques to compile comprehensive market studies, interspersed with relevant data.

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Published at Thu, 20 Aug 2020 17:15:00 +0000

The problem isn’t the algorithm. It’s the class system

“Fuck the algorithm!”  

A slogan for Gen Z, on whose lives algorithms will have a much greater impact than any before?  

Well maybe.   

But the really important thing in the UK’s exams debacle wasn’t the imposition of an algorithm. It was the decision made by those creating the algorithm to protect the ‘integrity of the qualification’ by aligning results with exam centre performance over the previous 3 years. Which might be what you would do if your only concern was the perceived value of a qualification. 

This is important in itself. And it’s important because it’s going to happen much more as artificial intelligence and machine learning, driven by algorithms, become a shaping force in governance around the world. 

The key questions here are not about algorithms, they are about what we as a society – or the institutions administering systems – want to achieve. We see this with ‘racist algorithms’ in the US. The algorithms are not racist, of course. When you apply large data sets to advise on who is likely to be committing a crime, or to what sentence someone should receive on conviction, it can expose the systematic biases, because writing the algorithm means writing them down. 

If the police are more likely to arrest Black people, the algorithm will suggest that you should arrest more Black people. Used uncritically, it will amplify existing biases. Looked at critically, it can help to expose those very biases. 

And this is important for the exam system because it is also marked by deep systematic biases. In this case against students at schools in poorer areas. 

The exam system doesn’t work

When I was at Edinburgh University, the institution did some data crunching and discovered that students from schools in poorer areas were more likely to get a first class degree than students from wealthier schools who had arrived with the same A-Level or Higher grades. Which wasn’t surprising. 

Anyone who was paying attention could see that wealthier schools had learned to game the exam system to get less bright students into top universities. But over four years of a degree, it was the bright kids who had got in without that advantage who shone. Ultimately, this became such a problem that the university decided to apply ‘contextual data’ to admissions to correct for this bias. 

A-Levels and GCSE’s serve several purposes. The main ones are to gauge progress, for university admission, and for employers. As an employer I have never looked at A-Levels, nevermind GCSE’s, though others might. And universities find that, especially since the reforms imposed by Michael Gove and Dominic Cummings, A-Levels do not tell us much about what a school student will achieve at university. 

If one of the main reasons why we have school exams is to help with university admission, and if universities have to interpret the grades, it suggests the exam authorities could have done something different. They could have learnt from the Edinburgh University approach and applied contextual data, boosting students from schools in poorer areas: recognising that getting a 70% from a college in one of Britain’s poorest areas is more of an achievement than getting 70% if you’re at Eton.

This would have given results that actually reflected the performance of individual students – a much more important outcome than the abstract aim of ‘protecting the integrity’ of qualifications which, as we discovered at Edinburgh, didn’t have much integrity in the first place. It would help to correct the systematic biases that amplify the existing social divisions. And from Edinburgh’s experience, it wouldn’t dumb down, but sharpen up: since the university adopted this approach, it has become a much stronger and more desirable institution.

Doing this would have been simple in data terms. But it would have been hard politically because it would have reduced the advantages of the wealthy. And wealthy parents have more power. 

Every year that Edinburgh University admitted students on their potential rather than just their grades from a broken exam system, there was a systematic attack by private school headteachers and the right-wing media. They claimed that offering places to those most likely to succeed was ‘dumbing down’ and ‘reverse discrimination’. It is with this in mind that the exam authorities no doubt chose to increase the grades of students at private and selective schools while reducing the grades of those at state schools in poorer areas. 

The answer to this problem is not less use of algorithms. It is for us to understand how algorithms work and to make sure that they work for the right outcomes. It is the system that is the problem, not the algorithm. 

And perhaps the lesson is that the slogan should be “Fuck the System” rather than “Fuck the Algorithm”.

Published at Thu, 20 Aug 2020 15:56:15 +0000