“Your AI is only as good as your data,” Thomas said. “That’s the fundamental problem. In organizations we work with, 80% of the projects get stopped or slowed down because the company has a data problem.”
From the article “Scaling the ladder: IBM leverages Watson tools and open source to bridge AI gaps” on SiliconAngle.
Any organization more than a few years old is going to have some data issues. The real world is messy and tends not to fit perfectly in databases.
IBM acquired open source software giant Red Hat to provide solutions that make data more accessible and interoperable.
“What Red Hat OpenShift is, it’s a liberator,” Thomas explained. “What that means is you can have the best data platform, the best AI, and you can run it on Google, Amazon Web Services, Azure, your own private cloud. You can get the best AI with Watson from IBM and run it in any of those places.”
Cleaner, better data informs smarter, more effective AI.
Organizations, like MarketChorus, who build machine learning algorithms to solve real-world problems have to be vigilant about the quality and inclusiveness of our training data.
Better data and better data scientists equal better AI. That’s the playbook IBM is clearly following as it pursues its AI initiatives, one step up the ladder at a time. “We are trying to inspire clients to give AI a shot,” Thomas said. “Go try things. Everybody will be successful with AI if they have this iterative mindset.”
The other lesson here is to look outside your organization and partner with, or acquire, companies that build technologies that remove your bottlenecks.
Lots of other thoughts to consider in the original article…
