How does artificial intelligence (AI) come into play on a day-to-day basis? In this episode of Making Data Simple, Jean-François Puget, distinguished engineer, machine learning and optimization, and Steve Moore, senior story strategist for Inside Machine Learning on Medium, join host Al Martin to
Machine learning has joined artificial intelligence (AI) as the hottest technology topics of 2018. We asked our expert influencers to share their thoughts on the state of the industry: where it's going, and how and why companies should be adopting machine learning and AI.
Machine learning is being used at the heart of next- generation methods for self-driving cars, facial recognition, fraud detection and much more. At IBM, we’re applying machine learning methods to SQL processing so databases can literally learn from experience.
Many companies are expected to pursue data management, advanced analytics and cognitive computing to stay competitive and drive revenue. Except for a handful of leaders such as LinkedIn, Netflix, Nordstrom, Target and Verizon, most companies are still struggling to close the gap between data
As the expression goes, "There’s no AI without IA." In other words, enthusiasm for AI has led many to jump in head first. But without a strong technology foundation, companies could be setting themselves up for obstacles.
The search function is a very powerful tool, assuming you have concrete keywords or concepts to find in your data. And that does not even take into account the size of the information you might be searching.
Join us 27 February at 1 PM ET for "Machine Learning Everywhere: Build Your Ladder to AI." Visit the event landing page to learn more about the event and register for a calendar reminder: ibm.com/mleverywhere
Today, unstructured information represents more than 90% of the information within organizations. This IDC case study estimates that the digital universe will grow 40 percent per year over the next decade and, by 2020 it will reach an astounding 44ZB or 44 trillion gigabytes.
Big Data and Analytics Hub spoke with IBM Distinguished Engineer John Thomas (@johnjaithomas) about some of the importance of tuning information architecture to make algorithms meet enterprise needs, as well as how machine learning can most effectively be applied in hybrid scenarios in 2018.
Big Data and Analytics Hub spoke with IBM Distinguished Engineer John Thomas (@johnjaithomas) about some of the importance of focusing on information architecture to make algorithms meet enterprise needs, as well as how machine learning can most effectively be applied in hybrid scenarios in 2018.
Kick off 2018 by exploring machine learning and what it can do for your business. The authors of Machine Learning for Dummies – Judith Hurwitz, and Daniel Kirsch – are here to help you. In this episode, Judith, Daniel and Al discuss the state of machine learning today, how to use it to advance your
Whether you want to build a bridge, explore the sea, or simply try to identify new markets, you will only be as good as the data you use. This means it must be complete, in context, trusted and easily accessible to drive insights.
It can be difficult to keep up with all the best podcast episodes during the year. That's why we've compiled the Top 10 podcasts of the year from the IBM Big Data & Analytics Hub Insights Podcast feed right here.