AI By the Bay — 3 Days as 3 Ways to Understand AI
short URL: chief.sc/3days3ways
A good way to understand things, at least for me, as a community-minded engineer and scientist, is to discuss them with rigor, clarity, meaningful questions, and most importantly with those who already are far ahead in defining the field. I’ve done it with Scala By the Bay, Text By the Bay, and Data By the Bay, providing a context, building a community, and asking the questions shared by many.
The structure of a conference By the Bay is a vehicle to understand its topic better. For Scala By the Bay 2016, we had three tracks, called Functional Programming, Reactive Microservices, and Data Pipelines. These are the three facets of Scala use in industry, represented by such projects as Cats, Kafka, and Spark, among others.
Data By the Bay 2016 was the first Conference Matrix — we had verticals for application domains, such as Law, Government, Democracy, IoT, Life Sciences, and horizontals, meaning algoritrhms and software stacks applicable to all verticals, like Deep Learning and Apache Spark.
We are building the AI By the Bay conference sequence in the same way — the structure of the days itself, and their sequence, sheds light on what is AI, and how to make it work in your company. I believe this is the biggest question for this year, which follows the emergence year of AI (2016) with a breakout year. The slogan of this year is “Show me the Money”. We need to focus not on the machinery of Deep Learning per se, but on the use cases, and meta — patterns of the use cases.
We need to figure out AI classification. We need to see AI technologies through code, through indisputable use case — not a “synergy” or an “added value”, but really “stuff works or it doesn’t”, and we need to think about the future, as always. Except we need to think about it from the point of today, and the caveat is, those who build it today have a pretty good idea about tomorrow. Running developer meetups, I know from experience that you need to get to the meat of things, the code, really quickly. So we are building the first AI sequence in the way addressing all of the above points, step by step.
There are three days in ai.bythebay.io. Each can be thought of as a separate conference (that has a name and even a separate website if you need it), but they are best understood, and attended, together. At least those who benefit from all three would make your best AI partners and hires.
On Day One, hai.ai, we do a tour of AI with live coding and a dive into tech. We’ll have hands-on leaders to show what they use at work. Vitaly Gordon, the VP of Data Science and Engineering, Salesforce Einstein, will keynote with showing how Machine Learning is done at Salesforce, working with code. Hands-on leaders will follow.
On Day Two, self.driving.cars, we dig into a very specific AI-driven problem. A self-driving car either drives, or it doesn’t. The success criteria are very well-defined. We’ll have industry leaders and AI researchers working on this very specific problem, leading AI deployment in the real world with really high stakes.
On Day Three, ai.vision, we’ll take what we learned and ask deep questions about it. We’ll define AI — setting its context in Data Science, Machine Learning, Natural Language Processing, and Data Pipelines — as a decision-making and context-aware process. Stuart Russell will keynote on Human-Compatible AI, framing the ultimate mode of operation. We’ll ask the questions which are on the minds of those who advance it, not just hypothesize about it. We’ll have a panel of smart money VCs investing on AI — one, Bradford Cross, a DCVC founding partner, also a serial AI startup founder. And we’ll have an industry panel considering where we will be next.
I hope you can join us at The Pearl, on March 6–8, in the single track and on the roof, building the new AI community By the Bay.
