Artificial Intelligence in Utilities Industry Analysis and Thematic Research by Key Players(Alphabet, Amazon, Apple) and Technology Brief

Artificial Intelligence in Utilities-Thematic Research Report with 42 pages and price US $ 3995 is added by Analytical Research Cognizance

Summary

Machine learning is an artificial intelligence (AI) technology which allows machines to learn by using algorithms to interpret data from connected ‘things’ to predict outcomes and learn from successes and failures.

There are many other AI technologies – from image recognition to natural language processing, gesture control, context awareness and predictive APIs – but machine learning is where most of the investment community’s funding has flowed in recent years. It is also the technology most likely to allow machines to ultimately surpass the intelligence levels of humans.
Many companies, like Alphabet, have already become ‘AI-first’ companies, with machine learning at their core. At the same time, many ML techniques are getting commoditized by being open sourced and pre-packaged into developer toolkits that anyone can use.

This report focuses on Artificial Intelligence in Utilities.

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Scope

This report is part of our ecosystem of thematic investment research reports, supported by our “thematic engine”.About our Thematic Research Ecosystem –

– GlobalData has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, GlobalData’s thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, GlobalData tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores. The algorithms in GlobalData’s “thematic engine” help to clearly identify the winners and losers within the TMT sector. Our 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. Our thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Multi-Theme report, covering all stocks, all sectors and all themes, giving readers a strong sense of how everything fits together and how conflicting themes might interact with one another.

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Reasons to buy

– Our thematic investment research product, supported by our thematic engine, is aimed at senior (C-Suite) executives in the corporate world as well as institutional investors.

– Corporations: Helps CEOs in all industries understand the disruptive threats to their competitive landscape

– Investors: Helps fund managers focus their time on the most interesting investment opportunities in global TMT.

– Our unique differentiator, compared to all our rival thematic research houses, is that our thematic engine has a proven track record of predicting winners and losers.

Companies Mentioned:

Alphabet
Amazon
Apple
Ayasdi
Baidu
Blue Yonder
Cognex
Darktrace
DataFox
Descartes Labs
E.ON
Enel
Exelon
EDF Energy
Facebook
Iberdrola
IBM
Intel
iFlytek
Ipsoft
Kensho
Mobvoi
Nvidia
Numenta
National Grid
Palantir
Preferred Networks
Quid
Salesforce
SAP
Splunk
Sentient Technologies
Vicarious
Zephyr Health

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List of Table:

PLAYERS 3
TRENDS 4
Technology trends 4
Macro-economic trends 7
Applications of AI in Utilities 8
VALUE CHAIN 11
Ten categories of AI software 12
INDUSTRY ANALYSIS 19
The tech sector’s angle 19
The Web-Scale companies 19
Enterprise software players 20
Proprietary datasets are also important 20
AI and ML are transforming the chipset market 21
The two critical components of any successful AI engine 21
Timeline 24
IMPACT OF AI ON UTILITIES 26
Utilities case studies 26
How AI vendors sell into the utilities sector 28
Recommendations for IT vendors 28
COMPANIES SECTION 30
Listed tech companies 30
Privately held tech companies 33
Utilities companies 36

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