Bio
Rony Kubat | Co-Founder & CTO | Tulip
Rony Kubat is the cofounder and CTO of Tulip Interfaces. He is a PhD graduate from MIT with a research focus on applied machine learning. He was the first employee at Bluefin (acquired by Twitter). Before graduate studies, Rony was a science and technology advisor for Hollywood film productions. Rony has been described by Wired Magazine as having a “steady low voice that could pacify a riot.” He is a playwright and is a member of the Junkyard Wars team, the Geeks (3rd Place, US Season three).
Abstract
Don’t get left behind waiting for AI/ML to mature
The digital transformation that includes AI/ML as a competitive advantage is the key to growth and scalability, yet the industry continues to see hesitance as manufacturers hold back implementing these technologies. For those whose core competency is executing in a physical world and extracting productivity from their workforce and machines, digital transformation can be overwhelming. IT and OT are still divided, and manufacturers continue to be on the fence regarding affordability, technological maturity and ease of execution.
Some of the enduring challenges for AI/ML implementation include:
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The need for multi-domain expertise is increasing - PAAS, infrastructure, edge computing, application expertise, data science and more. Hence the need for reliable and affordable system integrators, consultants which few can afford
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Digital transformation at its core is a human initiative and balancing automation with skilled human expertise and then introducing AI/ML into this is difficult to execute
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Most manufacturers wait for technology and practices to mature before adoption and very few exploit it as a competitive advantage
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Many are jaded about software adoption (ERP, MES, etc.) that has overpromised yet delivered underwhelming results.
However, the time is ripe to get decisive about how you can leverage AI/ML to drive innovation and productivity as you invest more in automation and deal with workforce transformation. The manufacturing scene is seeing a new level of interconnectedness and rapid technological developments as heavy AI/ML investments by AWS and MSFT targeting manufacturing start coming in.
Open source tools like node-red are widely adopted. Machine vendors are leveling up by building operation systems and applications to drive more productivity. Edge computing has become a mandatory need to connect the cloud to the physical world and innovative, next-gen application providers who can leverage it all on a no-code platform.
On top of that, we are right at the cusp of affordability even at the SMB level given that digital transformation, specifically AI/ML led, is one use case at a time. So if you are not investing in AI/ML transformation, your competitors surely are, and they will leave you behind.
In this presentation, we will illustrate why and how to successfully implement AI/ML as part of your digital transformation and turn them into competitive advantages through use cases. Key takeaways include:
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Overview of the current stage of digital transformation in manufacturing
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Why 2022 is the time to implement AI/ML as competitive advantages in your manufacturing processes
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How to implement AI/ML one use case at a time to ensure sticky adoption into your operations, and success stories from the shop floor.