Iris Zarecki, Explorium Senior Partner Marketing, at AWS re:Invent
Last week at AWS re:Invent, it was exciting to see over 20,000 people coming together for an in-person event after a travel ban for almost 2 years. The event was full of great discussions about data and various artificial intelligence and machine learning topics. One of my favorite sessions was by Dr. Swami Sivasubramanian.
It was inspiring to hear Dr. Swami Sivasubramanian talk in his AI/ML keynote about how data is powering the ML revolution, and how customers are reinventing their business with data:
"Data is the underlying force that fuels the insights and the predictions that help you make better decisions and stimulate completely new innovations ... With such diverse data growing and spreading faster than most organizations can keep track of, having data and actually getting value out of this data is a challenging thing to do."
He spoke about the survival of the most informed, and explained that those who can put the data to work, to make more informed decisions, respond faster to the unexpected, and uncover new opportunities – are the ones who are going to thrive. Although harnessing the power of data is challenging, it is imperative to present and future business.
This ties right into our mission at Explorium because external data is an integral part of this equation. Adding #ExternalData to this mix is critical because it injects context and wider perspectives into business decisions. Enterprises should use external data to enrich their internal data and improve analytical and ML models that forecast demand, understand buyer behavior, improve conversion rates, assess risk, and detect fraud.
Getting the right external data is complicated and resource-intensive. Explorium solves this problem by brining together the world’s best external data and automatically discovering, connecting, and matching internal data with thousands of relevant external data signals.
I was also excited to get the amazing opportunity to speak at the #reInvent AI/ML Meetup, alongside a great bunch of #AWSCommunity Builders. I spoke about why the next big AI/ML accuracy
breakthrough will be about finding the right data.
In the past five years, AI and Machine Learning have come a long way, thanks to the commodification of algorithms and computing power. Prior to these advancements, building, deploying, and scaling predictive algorithms required the expertise of statisticians, data scientists, and PhDs. Now, even non-experts can leverage machine learning. With the increased access and use of AI and ML applications, the algorithms alone are no longer competitive. The key to upleveling machine learning model accuracy is the data used to train the models. The biggest challenge for the coming years is not going to be how we train and scale the models, but finding the best data to train them on. This will require us to rethink how we discover and access datasets.
So where will the next breakthrough come from? It will come from making relevant external data an integral part of every AI/ML project; allowing for surprising combinations of data sets; and enabling unknown signals.
This year’s AWS re:Invent was inspiring and insightful. See you in Vegas next year!