Intel launches 34 open source AI kits, developers are expected to embark on the "fast lane"

**Source: **Financial Association

Edit Zhou Ziyi

Tech giant Intel Corp. has partnered with consulting firm Accenture to launch 34 open-source artificial intelligence (AI) reference kits designed to simplify and speed up the process of deploying AI for data scientists and developers, according to an announcement on Monday (July 24).

Each set of kits includes model code, training data, machine learning pathway description, database and oneAPI components (oneAPI is a cross-platform, open source software development tool set and programming model launched by Intel). The suite's ease of use is high, optimizing AI whether it's on-premises, in the cloud, or at the edge.

"The Intel AI Reference Kit provides millions of developers and data scientists with a simple, efficient, and cost-effective way to build and scale their AI applications in health and life sciences, financial services, manufacturing, retail, and many other fields," said Wei Li, Intel vice president and general manager of the AI and Analytics Group.

"The reference kit uses components from the Intel AI Software Portfolio and is built on the open source, standards-based oneAPI multi-architecture programming model."

So, how effective are these AI kits? Developers can more smoothly introduce AI into their applications, power their smart solutions, and deploy everything faster. **It's like "taking the fast track" instead of a traditional model development workflow. **

Also, these kits are not one-size-fits-all, they have been pre-configured to meet the specific needs of a range of industries. Therefore, whether it is consumer goods, energy, utilities, financial services, health and life sciences, manufacturing, retail, telecommunications, or other industries, there are 34 specific AI suites.

For example, one set of suites is designed for enterprise conversational AI chatbot interaction, and users can reason faster by 45% in batch mode; another set is designed for automated visual quality control inspections in the life sciences field, which can increase training speed by 20% and inference speed by 55% in terms of visual defect detection; for utility companies, with the blessing of specific AI suites, the prediction accuracy of utility asset health has increased by 25%.

The magic of these AI reference kits is reducing the potential development time, from weeks to days. Developers and data scientists can train models faster and more affordably without the constraints of proprietary environments.

John Giubileo, managing director at Accenture, noted, "Working with Intel on these AI reference kits improves our clients' productivity on AI workloads."