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Global Electric Vehicles in Utilities Market 2018:We are at the very beginning of the EV cycle. Today, there are 3m electric vehicles on the world’s roads, but this could rise to 300m by 2040. This implies EVs, as a proportion of new registrations of the world’s passenger vehicles, will rise from barely 1% in 2017 to over 15% by 2030. Large scale commercial production of EVs by the big car makers is unlikely to take off until 2025.
Power utilities are showing increased interest in EV programs. Utility programs are offering discounts and rebates on the purchase of EVs or charging equipment, free smart charge installation, along with EV time-of-use plans (on-peak and off-peak rate plans) for EV owners.
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Scope:
- This report focuses on electric vehicles, but also touches on the connected car theme.
- It identifies winners and losers in areas such as batteries, electric power trains, assembly, and charging stations.
- It contains global market size and growth forecasts for electric vehicles, as well as market share figures.
- Includes a timeline highlighting key milestones in the story of vehicle electrification.
- It identifies the impact of electric vehicles on power utilities.
Reasons to buy:
- Electric vehicles are having a major disruptive effect on the automobile industry.
- This report highlights the key trends in electric vehicles, analyzes each of the key segments of the electric vehicle value chain.
- Identifies both the companies best positioned to succeed in this theme and those that are lagging behind, and also identifies the impact of electric vehicles on power utilities.
Key Players:
• Albemarle
• BYD
• Byton
• BMW
• CATL
• Didi Chuxing
• Dyson
• Geely
• GM
• Great Wall Motors
• Infineon
• LG Chem
• NIO
• Nissan
• Panasonic
• Robert Bosch
• SAIC
• Samsung SDI
• Toshiba
• Tata Motors
• Tesla
• Toyota
• VW
• XCharge
• Xiaopeng Motors
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Key Points from TOC:
PLAYERS 3
TRENDS 4
Technology trends 4
Macroeconomic themes 6
Regulatory themes 8
VALUE CHAIN 10
Batteries 11
Semiconductors 13
Auto components 14
Assembly 15
In-car infotainment 16
Autonomous driving systems 17
Charging stations 18
INDUSTRY ANALYSIS 19
IMPACT OF EVS ON POWER UTILITIES 28
COMPANIES SECTION 30
TECHNOLOGY BRIEFING 37
GLOSSARY 38
APPENDIX: OUR “THEMATIC” RESEARCH METHODOLOGY 40
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Part 2:
Global Machine Learning in Utilities Market 2018:
For six decades’ machine learning (ML) was poised to take off because members of the ‘artificial intelligentsia’ had already come up with the theoretical models that could make it work. The problem was that they were waiting for rich data sets and affordable ‘accelerated computing’ technology to ignite it.
These arrived in 2010.
Now, amid a swirl of hype, machine learning - software that becomes smarter as it trains itself on large amounts of data - is going mainstream, and within five years its deployment will be essential to the survival of companies of all shapes and sizes across all sectors.
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.
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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 commoditised by being open sourced and pre-packaged into developer toolkits that anyone can use. This means that the time taken for Alibaba and Baidu to catch-up with Alphabet and Microsoft will be minimal.
Scope:
- This report analyses machine learning in utilities.
- The report highlights some of the global leaders in the top ten AI technologies and identifies the leaders and laggards in the machine learning industry and where do they sit in the value chain.
- It analyses the main trends across the machine learning sector.
- It identifies the applications of machine learning in utilities.
- It provides an industry analysis of the machine learning sector and highlights its timeline.
- It identifies listed and privately held companies at the forefront of machine learning technology and some of the power utilities actively involved in ML applications.
Reasons to buy:
- The report provides a comprehensive analysis of the present scenario and emerging market trends in the global machine learning industry.
- To gain insights of the global market leaders and challengers in the machine learning industry and where do they sit in the value chain.
- Provide detailed information regarding the ten categories of AI software and the machine learning timeline.
- Extensive analysis of the applications of machine learning in power utilities.
- Major market players within the machine learning industry are profiled in this report and their action plans are studied thoroughly, which aid in interpreting the competitive outlook of the machine learning sector.
Make an Inquiry before Buying "Global Machine Learning in Utilities Market" Report@ http://www.orbisresearch.com/contacts/enquiry-before-buying/2415186
Key Players:
• Accenture
• Alphabet
• Amazon
• AMD
• Apple
• Baidu
• Broadcom
• Cognex
• GE
• Tesla
• Goertek
• IBM
• iFlytek
• Infosys
• Intel
• Knowles
• Mediatek
• Micron
• Microsoft
• Nuance Communications
• Nvidia
• NXP
• New Relic
• Oracle
• Qorvo
• Qualcomm
• Salesforce.com
• Samsung Electronics
• SAP
• SK Hynix
• Skyworks
• Softbank
• Splunk
• STMicroelectronics
• Tableau
• Texas Instruments
• Toshiba
• Xilinx
• E.ON
• Enel
• Iberdrola
• Exelon
• National Grid
• EDF Energy
• Darktrace
• Vicarious
• Mobvoi
Key Points from TOC:
PLAYERS
TECHNOLOGY BRIEFING
TRENDS
VALUE CHAIN
INDUSTRY ANALYSIS
COMPANIES SECTION
APPENDIX: OUR “THEMATIC” RESEARCH METHODOLOGY
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