A new generation of machine learning created by AI is born

Headquartered in Silicon Valley with offices in Shanghai and Hangzhou in China, R2.ai Inc. is growing rapidly. We met with the founder and CEO of the company to talk about the AI ​​that creates the AI ​​and how automation will affect jobs in the future.

Originally a chemist, Yiwen Huang, PhD, ended up working in the fields of artificial intelligence (AI) and machine learning (ML) 23 years ago, while doing research on AI to identify the molecular structures of chemicals .

"I found the world of the computer and learning machine so fascinating that I decided to move on to the computer. Since then, I have been working for 20 years in this space with data management, machine learning and software development, "he said. tells interesting engineering.

"The reason I started R2ai is that when I was at Teradata, we developed the world premiere Automated learning platform based on a distributed parallel computing architecture, capable of forming a machine-learning model of terabytes of data in minutes unlike traditional methods, which take weeks . It's really fast in terms of the speed of the machine learning model can be formed. "

SEE ALSO: A LOOK AT THE MOST USED TERMINOLOGY AROUND ARTIFICIAL INTELLIGENCE

Despite the constant feedback from almost all R2ai customers who have emphasized the speed and fascination of technology, they have not found enough machine learning experts to use this tool. This shows a significant lack of machine learning skills, even though we need them so much.

Artificial intelligence is considered the most powerful technology, but it has no human talent.

According to one Gartner inquiry Out of more than 3,000 DSIs, Artificial Intelligence (AI) was by far the most cited technology and positioned itself as the game-changing, far from data and badytics technology that now ranks second. .

"What we see here is an important step in the transition to the third era of computer, the digital age," said Andy Rowsell-Jones, vice president and distinguished badyst at Gartner.

Indeed, in response to this and the comments made by R2 customers, Yiwen Huang now thought to have a new mission: to work on a new machine learning development on an operational platform that should not only be fast, but also easy to use; so easy to use, in fact, that even non-machine learning experts could quickly learn how to use it.

"That's why I wondered why we could not use artificial intelligence technology to develop a new generation of machine learning development and learning platform that can automatically calculate models without creating problems in the dataset, "says Huang.

"It's like that we started R2, and that's how it was developed." R2 learn, which is now a tool with Software as a Service (SaaS) the availability for that. That's how we ended up learning automatically at the machine. "Before the SaaS application, R2 Learn was only available on site.

Narrow AI, general intelligence, cognitive intelligence, reinforcement learning, and automation technology

Yiwen Huang explains that the current stage of R2 Learn lies in the Narrow AI technological parameters. "I guess the General AI in the end comes from a combination of all other Narrow AI technologies, he says.

"So, when Narrow AI technologies combine in a very significant way, you have something that has a very good chance of becoming a general artificial intelligence.I think it's a gradual, step-by-step process."

There are so many new terminologies around artificial intelligence that one has to be careful and learn about the different aspects that each of them encompbades.

"The HAVE the space is very wide, "says Huang. You have Machine learningwhich is the most popular trend at this stage; but there is also Cognitive AIwho tries to understand and imitate human behavior and tries to translate human knowledge into artificial intelligence. This is the cognitive AI. "

"There is also a technology like the Reinforcement learning, which is part of the Learning machine, but there is the idea that he is able to simulate. Simulation somehow allows you to imitate human creativity. And then there is also Automation technology, that you can put everything in place very effectively, "he says.

Models of construction learning

R2 Learn is a space that lets people create machine learning models. They provide a problem and they provide a set of data. According to Yiwen Huang, there are two ways to build machine learning models.

"The machine learning models are usually used to predictive badytics. Thus, the use cases are also quite wide, "says Huang. For example, in marketing and customer service, you can create a predictive model to predict what customers like or do not like. "

"You can predict the demand for certain commodities, you can also predict customer satisfaction, you can also contribute to fraud, or you can contribute to stock performance by forecasting the ups and downs of stocks. In health insurance, you can predict the risk of certain conditions and the cost of medical treatment. "

According to Huang, the purpose of the tool is to allow people who have trouble finding AI talent. "That's a big point we've seen on the market," he says. This tool is also useful for people who want to speed up the curve of an machine learning project.

"Usually it takes them a month to develop a single model, and with our tool they can do the same thing or even create a better model in minutes or hours," he says.

The R2ai solution was first launched on site. Recently, the company made it available as a SaaS solution. "If we launched it on SaaS, it's because we want people to know that there is a lot to do. best alternative it's there at what they do today. "

Huang explains that R2 Learn is particularly useful for people who are intimidated by machine learning because they do not have a solid knowledge of it. R2 Learn facilitates the immediate creation of machine learning models.

Industries Can Benefit From Creating Automated Machine Learning Models

R2 Learn is the next-generation AutoML tool that turns big data into sophisticated, high-quality machine learning models in a fast, simple, and affordable way. R2 Learn allows experts and non-specialists in artificial intelligence to develop and deploy their own artificial intelligence solutions.

R2.ai is a market pioneer with these combined technologies that tackle the major problems of AI development:

• End-to-end automatic model development and operating mode for non-automatic learning experts;

• Advanced model development and mode of operation for machine learning experts;

• Superior performance and modeling efficiency

• Transparent and explainable modeling process;

• Self-learning skills for continuous self-improvement;

• SaaS and on-site offers for different market demands.

Technology is actually agnostic of the industry. It is a generic tool and a platform. But the industry must be ready to learn the machine. According to Huang, one of the conditions is the need to have the data.

"So, have their data collected and consolidated.It's when they need the tool to start translating the data into the real turnover and satisfied customers. That's why the machine learning development tool is needed, "he says.

For Huang, the industries that are currently the most ready for machine learning are life insurance, health, finance, manufacturing and telecommunications.

"I think a lot of other industries are already ready, but I think all the other industries are already ready to get ready for machine learning, so their main goal is to collect as much data as possible. So when the data is ready, they can start using machine learning, "says Huang.

Huang explains that the first R2ai SaaS offer is based on Amazon AWS. Being available online, Internet users around the world can access it. The AWS Instance Data Center will initially be located in North America and Japan before expanding to a global scale. He says there are two main types of customers that can benefit from the use of the tool.

"The SaaS offer can be very useful for people who are active in machine learning, but have trouble finding machine-learning developers or those who want to speed up their projects or those who want to have their minds in mind." value of the data, "he explains.

The second group of customers includes "those who wish to embark on Machine Learning but are now intimidated by the investment and lack of expertise in machine learning." It is the customers who benefit enormously from the solution and technology R2ai SaaS ".

Virtually all industries use Machine Learning in one degree or another, depending on their needs and capabilities. This trend will only increase in the coming years.

"That's why we think we need to make this information widely available so that people in all sectors can begin to explore the possibilities offered by their data, "Huang said.

Companies and individuals wishing to develop their own AI solutions or speed up slow AI projects are welcome to sign up for a free trial. Huang is also pleased to offer an initial free consultation to clients seeking help evaluating the possibilities of AI.

Adoption of AI and Engineering

In the manufacturing and other sectors, some people fear losing their jobs due to automation. Even though industry experts and future specialists have said that automation will create new jobs for those who have prepared for the acquisition or development of new skills, especially general skills. .

SEE ALSO: ENGINEERS MUST MASTER SOFT SKILLS FOR A SUCCESSFUL CAREER

"I guess the goal of engineering is to free people by automating tasks, making things easier for people, so that they can focus more on the important elements."

In terms of business, I think the most important thing for them is to solve business problems otherwise than by learning to use sophisticated machine learning tools.

Thus, the engineering developed this tool to make the work of the employees really easy, very fast, more effective and to increase their productivity. I would say easy, fast, better and cheaper.

"I guess the goal of engineering is to free people by automating tasks, making things easier for people, so that they can focus more on the important elements."

"The value of these tools lies in how they help the business to generate more value, and how quickly they can generate that value." There are aspects related to cost savings, but I think that the most important area is how I can use this tool with my existing resources, "says Huang.

Huang reminds us that in the broader sense of evolution of the industry there is always a process of automation, as we have observed. "But in the process, we do not see people losing jobs because there will always be more jobs to be created," he said.

"Even today, there will always be new trades and jobs." I think the trend is that automation will help us be more efficient at generating more value, more wealth as a result. than society. "

Huang think that there will be a short-term change for some people because they will have to change domain, career or industry. "In this sense, we need vocational training or repositioning programs.But I do not think that in general, AI will reduce employment opportunities as a whole", a- he declared.

For Huang, it is all about change, learn, improve and make things easier than before for everyone. It is also about constantly learning new skills in order to stay in tune with our times and with the technology that exists between us.

"I guess the new skills will be more about creativity and human-to-human communication (H2H) .I think these are the areas in which AI will take longer to learn," he says. .

"More collaboration will happen across ministries, sectors and industries ".

"Our vision of AI is to increase the number of people to not replace them.Once, the goal of AI is to simplify people's lives.And this will help people to generate more values, to acquire more knowledge, "said Huang.

Huang thinks that there will be no potential problem unless we limit ourselves to a very confined space. "But the reality is that we are expanding," he says.