Hottest top trends in artificial intelligence and

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The top trend of artificial intelligence and machine learning in 2018

since the term artificial intelligence (AI) was created by John McCarthy, a master of artificial intelligence at Dartmouth College in 1955, it has made great progress. 63 years later, AI is changing and overturning the business development of healthcare, financial technology and other industries. Although the real humanized AI is still being explored, the progress of big data and machine learning (ML) will help AI become the mainstream of technology. This article will introduce the development trend of top artificial intelligence and machine learning in 2018:

1. Accenture, a healthcare consulting firm, said that by 2021, the size of the U.S. artificial intelligence healthcare market is expected to reach $6.6 billion, with a compound annual growth rate (CAGR) of 40%

medical imaging and diagnosis companies are promoting the development of artificial intelligence in medical and health technology. For example, arteries is an artificial intelligence assistant for radiologists based on cloud computing. It was approved by the U.S. Food and Drug Administration (FDA) through its oncology AI suite in February 2018 to analyze lung and liver tumor images

using artificial intelligence, personalized medical care and precision medicine have also made great progress. In August this year, researchers at the University of Singapore used artificial intelligence to identify and optimize the combined drug treatment of myeloma, a blood cancer

2. Fintech

from asset management, financing to loans and mobile payments, fintech has proved itself to be a disruptive technology. AI is helping financial technology to raise these core competitiveness to a new level

AI allows users to deposit funds into the bank through their preferred mobile device. Last October, the first artificial intelligence ETF (Exchange Traded Fund) was released, and Elson is helping large financial institutions deal with big data. There is also a growing community of quantitative traders who want to test and share trading algorithms, some of which are supported by machine learning

3. energy

from oil and gas giants to green technologies for renewable energy, the energy industry has produced a large amount of data. AI is well suited for processing large data sets and providing actionable insights that can help energy producers and consumers make better use of electricity

for example, the energy storage optimizer Athena processes 400 megabytes of energy data per minute in more than 800 energy storage systems to simplify the time of energy use and help customers save $8million a year

at home, smart constant low smoke and smoke thermostat nest reduces energy consumption by adapting to the habits of family residents. UK's national power will combine Google deepmind technology to simplify UK electricity operations

4. enterprise

according to the latest Market Research Report of technavio, it is expected that the global enterprise artificial intelligence market will achieve a compound annual growth rate of 45% from 2018 to 2022. Technavio attributed most of the growth to the business growth of using customer service chat robots

machine learning solutions for processing big data are another reason for this significant growth. Technology giants such as Google, Amazon, IBM, Intel and Microsoft are leading the technology trend by providing and/or supporting many basic AI frameworks and tools that bring machine learning to the public. Google owns deepmind, IBM owns Watson, and the combination of AWS and Apache spark can help enterprises process a large amount of data

5. Retail

the retail industry is still a hotbed of innovation in the field of artificial intelligence. As mentioned above, retailers are reducing customer service costs through chat robots. They also use predictive analysis to optimize product pricing and build customer roles from databases

of course, artificial intelligence in the retail industry has become so common that people may already know all this. The new change in recent years is how enterprises will become more creative with the maturity of technology

people may have heard of chat robots, but how can robots in physical retail stores increase customer traffic by 70%? Or kairos, which uses artificial intelligence and facial recognition, will inform store employees of their preferences once customers enter the door

when Softbank, a multinational enterprise group, is negotiating with zume, a company that mainly provides pizza robot delivery services, for up to $750million, people may feel that they are already living in the future

6. software development

encoder is always looking for a higher level of abstraction to improve the productivity of programmers. This is how the latest software development tools, libraries and frameworks simplify the development process

maybe one day, the final level of abstraction is to let the program write itself. But before that, there are many AI based tools that can make the work of developers easier

Google's Bug prediction tool has long used machine learning algorithms and statistical analysis to identify defective code. Deepcode is more in-depth, providing programmers with Grammarly, which can identify problems in their public and private GitHub repositories and provide solutions

from digital assistant to autonomous vehicle

now it is 2018, and AI is closer to science fiction than ever before. Exciting and observed results are not fully included in the list. We should also consider whether the oil is too thin and dirty. These include:

digital assistants, such as Alexa, Cortana, Siri, can be found in millions of families around the world

the major display of Google duplex at I/O 2018 shows how far NLP (natural language processing) has gone. The voice of its digital assistant sounds very humanized, even including voice prompts, such as "mm HMM" and "Hmm"

driverless cars are not only applicable to Google and waymo. General motors, Daimler, BMW and Ford are all auto manufacturers actively developing this technology in 2014

manufacturing automation also benefits from the progress of artificial intelligence. Fanuc robot learning vibration control (LVC) software can be used to accelerate the deep learning of robots on assembly lines to perform specific tasks

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