Fourth normal form was selected into Gartner 2020's Top Ten Strategic Technology Trends Report and became a representative global AutoML manufacturer

Recently, Gartner, an international authoritative organization, released the report "Top Ten Strategic Technology Trends in 2020: AI Democratization", and 4Paradigm, as a representative of automatic machine learning (AutoML), was selected as a recommended vendor in the report. Gartner believes that the "AI democratization" represented by AutoML has the advantages of low threshold and high efficiency, and will accelerate the process of large-scale application of artificial intelligence in enterprises.

Gartner's "Top Ten Strategic Technology Trends" is known as the "Technology Weathervane". Every year, it summarizes strategic technologies that have great disruptive potential, are about to enter a mature commercial stage, and have an ever-expanding scope of influence and use. These technologies will grow rapidly. The critical point will be reached within the next five years. Gartner recommends that enterprises focus on these technological trends in order to deal with their significant impact on business strategies and make corresponding adjustments.

In the forecast of strategic technology trends in 2020, "AI democratization" became one of the top ten strategic technology trends, and was given the mission of "radically simplifying the experience without extensive and expensive training" to ensure wider access to users Technical expertise (such as machine learning, application development) or business expertise (such as sales process and economic analysis) to achieve the goal of AI "universal availability".

Gartner's special report on "AI democratization" technology trends specifically emphasizes the key role of AutoML in "AI democratization". Gartner found that the rapid development of AI spreads across all types of enterprises and all regions. Enterprises not only benefit from a single, large-scale AI solution, but also benefit from hundreds of small and medium-sized solution deployments. With the large-scale application of AI in enterprises, its deployment challenges are becoming clearer—according to Gartner survey results, the lack of technical talents is the biggest challenge faced by major enterprises and organizations when building and implementing AI applications.

The "AI democratization" with AutoML technology as the core can reduce the threshold and improve efficiency, so as to solve the problem of unable to carry out machine learning projects and applications normally caused by the shortage of professionals in the development of AI, and accelerate the large-scale application process of AI in the enterprise.

In terms of lowering the threshold, "AI democratization" transfers the ability of enterprises to build AI solutions from data scientists to business personnel-more and more non-AI technical personnel can master the creation of AI solutions through cloud deployment or locally deployed AI platforms. In terms of improving efficiency, "AI democratization" can enable data scientists to focus on using artificial intelligence to explore more application cases.

In the report, Gartner paid special attention to the 4Paradigm AutoML technology, and quoted the 4Paradigm AutoML concept and technical logic for explanation (as shown in the figure below). In the past, the machine learning process was mainly carried out by AI technical experts, and it usually required several iterations of parameter tuning to make the process efficient. The 4Paradigm AutoML automates the machine learning process, improves the construction of machine learning applications, and reduces the dependence on professional knowledge. It is an enhanced solution to help experts and ordinary business personnel improve machine learning development capabilities and performance.

In the report, Gartner highlighted two representative cases from 4Paradigm and Google, clarifying that AutoML is already helping experts and business users with non-technical backgrounds improve the performance of machine learning applications. More and more enterprises are using AutoML to deploy AI applications and generate business value.

• Chevron's seismic image processing technology team installed Google's automated machine learning image analysis tools to conduct an internal literature search to identify new opportunities for oil drilling.

• Based on 4Paradigm's AutoML technology and products, doctors at Changchun Obstetrics and Gynecology Hospital established newborn weight prediction and premature rupture of membranes prediction models. Doctors without machine learning experience thus proved the relationship between atmospheric pressure and premature rupture of membranes. close correlation.

Gartner predicts that by 2024, 75% of large enterprises will use at least four low-code development tools to support IT application development and citizen (developers and business personnel without professional AI skills) development; by 2025, data The scarcity of scientists is no longer an obstacle for companies or organizations to adopt technologies such as digitalization and machine learning.

Under the technological trend of "AI democratization", Gartner recommends that relevant teams use processes and tools to undertake more artificial intelligence work as soon as possible. Based on a detailed survey of platform tools, Gartner recommends mainstream automatic machine learning vendors in the report. 4Paradigm was selected as the representative manufacturer of the automatic machine learning platform category, together with Google (representative manufacturer of public cloud platform with machine learning functions and services), H2O.ai (representative manufacturer of open source artificial intelligence platform), DataRobot ( Machine learning platform represents manufacturers) and other overseas technology companies.