[Infographic] AI and Machine Learning in the enterprise

Machine Learning is a broad term for the action you teach computers to improve a task that it is performing and is the main technology behind the use of artificial intelligence applications. Without machine learning, the current artificial intelligence (AI) will be much limited because it gives the computer the power to find everything without being explicitly programmed.

AI applications are developing very fast and powerful, so businesses focused on the effective use of such applications are becoming a task for every organization. Quantrimang would like to highlight some views, facts, figures as well as findings about AI and Machine Learning in the form of infographic. Invites you to read the track.

[Infographic] AI and Machine Learning in the enterprise Picture 1

Define

Machine Learning is a method of data analysis that automates the construction of analytical models. Using data repetition algorithms, Machine Learning allows computers to find hidden knowledge that is not explicitly programmed to find. An example is predicting vehicles at a crowded intersection - the program can run the Machine Learning algorithm on data of past traffic and give a better prediction of traffic patterns in the future. hybrid

What is needed to create a good Machine Learning system?

1. Ability to prepare data
2. Algorithm - basic & advanced
3. Automatic process and repeat process
4. Scale capability
5. Ensemble modeling

Field of use

1. Research
2. Analyzing consumer behavior
3. Fraud detection
4. Forecast of sales or market forecast
5. Monitoring Internet security and IT
6. Office automation

Subject to use

1. Financial services
2. Goverment
3. Health care
4. Marketing and Sales
5. Oil and Gas
6. Carriage

Process of using AI in enterprises

1. Start identifying the problem. Deciding the stage you will use AI to improve performance.
2. Identify data sources and focus on collecting data from customer contact points.
3. Develop optional AI-based solutions to support decision-making algorithms.
4. An AI solution is created and developed to be operational, so action and solutions should be put into practice.

Statistics

According to Bank of America Merrill Lynch, the AI-based analytical market is expected to increase to 70 billion dollars by 2020.

Among the respondents who have experience in AI and Machine Learning:

1. 54% said that potential users in their organizations were less interested in Machine Learning and AI.
2. 28% have personal experience working with AI and Machine Learning.
3. 28% of colleagues have worked with AI and Machine Learning.
4. 49% heard about AI and Machine Learning.
5. 8% unknown to AI and Machine Learning.
6. 42% of respondents say their company lacks the skills to deploy, implement or support AI and Machine Learning. However, 30% said they are investing in skill development.
7. 42% of respondents said they are working and adding AI and Machine Learning to the company's IT security plan.

Respondents with companies planning to implement AI and Machine Learning:

1. 19% are currently in use
2. 24% plan to use it in the next few years
3. 26% plan to use it next year
4. 31% have no plans to use it in the near future

See more:

1. Entertainment on Neural Networks, Artificial Intelligence and Machine Learning
2. Scientists have created the world's strongest AI, defeating the best AI in chess
3. The difference between AI, machine learning and deep learning
4. [Infographic] The trend of Chatbot will explode in the future