I'm AI

No, I have not uploaded my mind to a supercomputer (yet). This is merely my brief wrap-up of last week’s I’m AI conference in Berlin, a cross-industry meeting of data science practitioners:

As I showed during my presentation, we are applying advanced analytics productively at Merck to make science faster – be it to find new molecules with desired properties, speed up the process development for a new drug, or supply life science researchers around the world with exactly the right lab equipment. But what about AI across the rest of the business spectrum?

I’m AI hosted a variety of interesting talks about how data science is applied at companies as different as DB Schenker (logistics), Swarovski (luxury goods) or Basler Versicherungen (insurance). My three takeaways from the conference were:

1.     Compared to where the industry stood even 2-3 years ago, many companies have transitioned from data science proofs-of-concept to productive solutions (e.g. Trumpf using sophisticated algorithms in their laser cutting machines)

2.     Deep learning is getting adopted for practical purposes much more broadly (e.g. Techniker Krankenkasse using machine learning to classify millions of scanned documents that they receive every year)

3.     The use cases are getting more creative. From classical “customer churn” or “credit rating” examples to very niche, industry-specific use cases (e.g. Swarovski using image recognition to match their own products with social media photos)

While I think that we are still at the very early stages in the development of AI, there’s no question that the community around these technologies is trending in a more productive direction. AI has permeated throughout industries and the benefits for consumers are still only scratching the surface. As we continue to refine and apply AI-driven solutions, the outcomes have potential to transform everything.