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AI - April 24, 2023

Info-Tech highlights eight AI trends for 2023

Info-Tech has released its Artificial Intelligence (AI) Trends 2023 report detailing an overview of AI trends that will continue to drive innovation and new opportunities throughout the year for organizations. 

The report, written by Irina Sedenko and Anuradha Ganesh, is broken down into eight trends: design for AI,  event-based insights, synthetic data, edge AI, AI in science and engineering, AI reasoning, digital twin, combinatorial optimization

Trend highlights include: 

Design for AI: Info-Tech reports that design for AI systems will change as the technology becomes more popular. Sustainable AI system design needs to consider several aspects such as the business application of the system, data, software and hardware, governance, privacy, as well as security. According to the report, an AI system design approach should cover all stages of AI lifecycle, from design to maintenance. It should also support and enable iterative development of an AI system.

To take advantage of different tools and technologies for AI system development, deployment, and monitoring, the design of an AI system should consider software and hardware needs. 

AI in science and engineering:

The report details the impact AI has and will continue to have on the science and engineering fields. AI helps sequence genomes to identify variants in a person’s DNA that indicate genetic disorders. It allows researchers to model and calculate complicated physics processes, to forecast the genesis of the universe’s structure, and to understand the planet ecosystem to help advance the climate research. AI has been able to make advances in drug discovery.

“The role of AI in science will grow and allow scientists to innovate faster,” Info-Tech reports. It will continue to further contribute to science by assisting scientists with research to help find new insights, generalize scientific concepts, and transfer them between areas of scientific research.

Using synthetic data and combining physical and machine learning models and other advances of AI/ML will accelerate the use of AI in science and engineering, the report adds.

Synthetic data:

Synthetic data is…

Read The Full Article at IT World Canada

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