Unlocking AI's Potential: Embracing Collaboration for Rapid Innovation

Good thoughts, an intro:  

Unlocking AI's Potential: Embracing Collaboration for Rapid Innovation

AI collaboration across corporate boundaries can greatly accelerate innovations in data science, AI model development, and applying AI to use cases in real world situations -- here are some examples of how some organizations are making it work. (SPONSORED)

With ChatGPT and other generative artificial intelligence technologies changing the face of the global AI landscape, many enterprises are in the process of either starting or extending their AI business initiatives. Either way, they'll need to tap into the right resources to maximize their AI investments. Because AI research and development takes cutting-edge acumen and digital infrastructure to develop, establishing effective collaborative relationships across businesses, governments, and academic institutions will be crucial.

Examining Today's AI Successes

Before examining how collaboration fuels AI innovation tomorrow, let's crack the code on what AI success already looks like today and how to meaningfully propel AI innovation into an extraordinary tomorrow.

Industry 4.0 -- digitization of the manufacturing sector -- offers some key AI use cases that are already in place. They include examples of predictive maintenance, energy reduction, increased production, and demand forecasting. Here are a couple of illustrations of what that looks like today:

Recently, a household appliance manufacturer in Vietnam leveraged an AI-enhanced acoustic inspection platform that, in just the first month, helped the company increase the accuracy of its defect checks by 95% and doubled the speed of detection that was previously reliant only on workers listening for problems. The tool also aided the company in building a database for defect root cause analysis.

Meantime, a manufacturer with a facility storing high-value goods in the US wanted a way to reduce the energy footprint of the 30 industrial air conditioners powering its substantial HVAC infrastructure. By utilizing an AI-based system that precisely monitors changes in temperature and humidity and automatically makes timely adjustments, the facility was able to slash energy consumption by 30%.

One recent report from Accenture and Frontier Economics estimates that the cumulation of case studies like these has the potential to add as much as $3.8 trillion to the value of manufacturing businesses by 2035. But that financial forecast isn't a foregone conclusion.

Collaboration Will Fuel AI's Innovation Engine

Many organizations today are still spinning their wheels when it comes to AI innovation. Gartner's analysis shows that only about half of AI models make it from the pilot stage to production. Clearly, the route to success is still far from straightforward. However, potential is massive thanks to collaboration between industry and academics to comprehensively drive and regulate the latest in AI technology.

While our minds may associate AI with tech hot spots like Silicon Valley, the most potential might come from other emerging tech destinations. Asia Pacific, for instance, stands as the fastest growing AI market in the world.

Both manufacturing examples described above came from this growing region of AI innovation. They were powered by research and development from FPT Software -- a Vietnam-headquartered global digital transformation and IT services company.  FPT Software weaves AI throughout its work with clients but also recognizes that advanced AI models and systems require a whole new class of expertise and research beyond what even a very robust software engineering organization can offer alone.

And this is where AI collaboration comes into the picture. FPT Software accelerates its capabilities through a center of excellence approach. The company built its AI Center as a regional hub for AI research and development in partnership with some key organizations.  .... '