Machine learning offers tremendous opportunities for businesses, but there is still a large divide between practical deployment for most companies and the success stories we’ve read about. Despite the promise of artificial intelligence being discussed and promoted by the internet giants like Facebook and Google or within academia, only a small percentage of enterprises have effectively implemented machine learning in their workflows. This may be due to barriers such as limited access to required skillsets, insufficient data or infrastructure, poorly designed pre-trained offerings, or unrealistic expectations due to overhype in the media. So how can enterprises find practical ways to deploy these innovations?
The AI World conference that’s taking place from December 11-13, 2017 in Boston, Massachusetts aims to help enterprise executives and business leaders address these issues. If you’re looking for an easily deployable and customizable deep learning solution that doesn’t require you to actually know how to build an algorithm from scratch, be sure to drop by the indico booth and chat with our team. We’d be happy to help you distinguish what’s hype and what’s not, learn how to effectively use deep learning to gain a competitive advantage, and increase efficiency while reducing costs.
Specifically, we’re working to lower the barriers to entry by requiring less data, time, and investment to integrate machine learning into your business. Our models are trained on a massive dataset we have developed and consists of hundreds of millions of examples. By incorporating a special technique called “transfer learning” into our offerings, teams can use much smaller sets of unstructured data to create customized models with less than 100 examples. This gives enterprises the ability to rapidly iterate to determine whether there’s any value in the results. Projects with worthwhile results can then be scaled and deployed with minimal engineering overhead and risk.
We’ll be at AI World on Monday and Tuesday, and our CEO, Tom Wilde, will also participate in the lightning panel session on Monday, December 11, 2017, at 6:45pm EST. If you want to get in touch before then, feel free to reach out to us at firstname.lastname@example.org!