In one of the biggest AI events in the world, over 3,000 experts from research and industry showcased and discussed their latest work. Advances in machine learning are happening across the board, and integrating knowledge-based systems with graph-based deep learning promises breakthroughs.

Anchorage may not be the most well-connected location in the world. But as it turns out, when people and data are well-connected, location may follow. Anchorage was host to SIGKDD’s Conference on Knowledge Discovery and Data Mining in 2019 or KDD as it’s commonly known. The conference is organized by the Association for Computing Machinery (ACM)’s Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD).

KDD is one of the most well-known and popular events for data science and AI, attracting around 3.500 researchers in 2018 in London. Although the decision to host KDD 2019 in Anchorage caused some concerns, attendance did not really drop.

The 25th incarnation of KDD was a “who is who” in data science and AI. KDD was set up by people who have been into data science and AI before they were given their current monikers and attracted widespread attention.

KDD is a meeting point for research and industry. People who show their work in KDD often go through those revolving doors, with some of them wearing both hats at the same time. Case in point, the KDD applied data science invited speakers track, featuring data scientists from the likes of Airbnb, Alibaba, Amazon, Apple, Facebook, Google, NASA, LinkedIn, and Microsoft.

The goal was to invite highly influential speakers who have directly contributed to successful data mining applications in their respective fields. Looking at the topics picked by those speakers, as well as KDD proceedings, a theme started to emerge.

One of the things that seem to be top of mind for these people is pushing the limits of deep learning. This form of machine learning has achieved great accomplishments in the last few years. Many AI researchers believe deep learning on its own will never be much more than sophisticated pattern recognition: Great for facial recognition or language translation, but short of true intelligence.

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