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As ChatGPT and other generative artificial intelligence technologies change the face of the global AI landscape, many companies are in the process of starting or expanding their AI business efforts. Either way, getting the most out of your AI investment requires leveraging the right resources. As AI research and development requires cutting-edge insights and the development of digital infrastructure, establishing effective partnerships between companies, governments and academic institutions is critical.
Validate the success of AI today
Before we look at how collaboration will drive tomorrow’s AI innovation, let’s take a look at what AI success looks like today and how we can meaningfully drive AI innovation to create an extraordinary tomorrow. Let’s crack the code.
Industry 4.0 (digitalization of the manufacturing sector) offers several important AI use cases that are already being implemented. These include examples of predictive maintenance, energy reduction, production increase, and demand forecasting. Here are some pictures of what it looks like today.
- A Vietnamese home appliance manufacturer recently leveraged an AI-enhanced acoustic inspection platform. This has helped the company improve his defect checking accuracy by 95% in just his first month and double his detection speed, which previously relied solely on workers. to ask questions. The tool also helped the company build a database for root cause analysis of defects.
- Meanwhile, a manufacturer with facilities to store high-value goods in the United States wanted a way to reduce the energy usage of the 30 industrial air conditioners that power its critical HVAC infrastructure. By utilizing an AI-based system that accurately monitors temperature and humidity changes and automatically adjusts in a timely manner, the facility has been able to reduce energy consumption by 30%.
A recent report by Accenture and Frontier Economics estimated that the accumulation of such case studies could add as much as $3.8 trillion to the value of manufacturing by 2035. But that financial forecast is not a predetermined conclusion.
Collaboration fuels AI’s innovation engine
Today, many organizations are still going all out when it comes to AI innovation. According to Gartner’s analysis, only about half of AI models can move from the pilot stage to production. Clearly, the road to success is still not easy. But with industry and academia working together to comprehensively promote and regulate the latest AI technologies, the potential is enormous.
While our minds may associate AI with technology hotspots like Silicon Valley, the most likely destination may be other emerging technology destinations. For example, Asia Pacific is the fastest growing AI market in the world.
Both manufacturing examples discussed above emerged from this growing field of AI innovation. These are powered by the research and development of his FPT Software, a global digital transformation and IT services company headquartered in Vietnam. FPT Software weaves AI through its work with clients, but advanced AI models and systems represent a whole new class of expertise and expertise beyond what a highly robust software engineering organization can offer alone. We also recognize that research is needed.
This is where AI collaboration comes into play. FPT Software accelerates its capabilities through a Center of Excellence approach. The company has partnered with several leading organizations to build AI Centers as regional hubs for AI research and development.

At its core is the Mila Institute, the world’s largest deep learning institution. Based in Quebec, Mila works closely with the FPT Software AI Center and its parent company, FPT Corporation, to develop a large-scale AI platform to power AI4Code, a subfield of AI that improves developer productivity. I am conducting a research project on language models. The partnership also aims to establish a comprehensive framework that advocates for responsible AI, thereby reducing AI risks and improving transparency, fairness, accountability and privacy in AI applications. increase. In addition, FPT Software AI Center has built core relationships with AI companies such as Landing AI to help companies advance the construction of data-centric AI inspections in real-world settings.
“We will work with the world’s top minds to seize the vast potential of AI and accelerate its practical application,” said Phong Nguyen, Chief AI Officer at FPT Software. “FPT Software and its partners are working towards a goal of global impact. Prioritizing responsible AI development is crucial to keep up with the rapid advances in technology.”
Through these partnerships, FPT Software AI Center focuses on creating and training new AI/ML models, experimenting with AI use cases, and developing new products to solve common problems in targeted industries. increase. For example, the center’s experts developed a quality control and predictive maintenance platform for manufacturers called I2 (Intelligent Inspection) that enhances his two use cases above based on supervised and unsupervised learning models. Developed.
This collaborative approach is one of the most effective ways to accelerate AI. The complexity of AI systems, the scarcity of AI and data science experts, and the need for large-scale data sharing to effectively train AI models has led more organizations to leverage AI today. It will be necessary to look for partners across corporate boundaries in the development of the ecosystem. .