Happy Friday! Let me think about future PLM moonshot. I want to talk about intersection of product lifecycle and AI. Have you heard about AI (artificial intelligence) recently? Grab few hours during coming weekend and do that. The AI is trending again. I’m saying again mostly for my friends who might remember AI development back 20-25 years ago.
However, spending into research around artificial intelligence and related fields is increasing. Few days ago, my attention was caught by aitrends article – Deep Learning Enterprise Software Spending to surpass $40B worldwide by 2024.
An interesting passage I captured from this article speaks about Deep learning as “enabling technology”:
Deep learning, which has emerged as one of the most active technology areas within the broader field of artificial intelligence (AI), is attracting an increasing level of attention from industries as diverse as advertising, finance, manufacturing, media, and healthcare. Deep learning is primarily an enabling technology, making areas like machine perception, big data analytics, and the Internet of Things (IoT) much stronger. The technology is especially well-suited for businesses that deal with large amounts of data.
Deep learning as well as intelligence is coming more and more in use cases that supporting other applications or processes. The sense of “hidden force” is interesting. Another article “The Next API is no AI” brings an interesting point about evolving of intelligence algorithms into future AI platforms:
….AI technologies could evolve into a platform, an infrastructure similar to the Internet, that would allow people themselves to decide the way they utilize AI or contribute to its design and development. Such an AI grid, like the Internet of Things², powering various experiences and applications in different environments and industries, being open for tinkerers and specialists alike, would significantly change the way we could understand AI or interact with intelligent systems in general. Human and machine intelligence would be intertwined in unseen ways.
It made me think about future intersection of PLM and AI platforms. Manufacturing is becoming more connected these days. The relationships between OEMs and suppliers, contractors, different product configurations, demand, global manufacturing, etc. All together is a potential grid of information and options that cannot be digested and optimized by a human mind. The dependency of products on software is growing too. A potential crisis in supply chain or software malfunctioning can damage products, delay production schedule or even put people lives at risk. Product information is too complex. Impact analysis is too complicated. Is there a potential to bring AI platforms to solve these problems in the future of manufacturing.
What is my conclusion? The complexity of product information, manufacturing processes and supply chain will be growing in the next 10 years. So, the demand for “intelligent” platforms capable to make analysis and help people to make decisions. Future of intertwined intelligence will come in the intersection of product lifecycle systems and AI platforms. It is a moonshot, but something worth thinking about. Remember, when Sergey Brin was talking about indexing the whole web back in 1995, people were laughing on him. Just my thoughts…
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Disclaimer: I’m co-founder and CEO of openBoM developing cloud based bill of materials and inventory management tool for manufacturing companies, hardware startups and supply chain.