Recent news about a Microsoft AI investment led me to my latest forbes.com column covering the idea that it’s not always innovators that win. Fast followers can do a good job.
Social media has a lot of data. That means that everyone from government agencies to businesses to parents have a hard time mitigating risks and increasing the rewards of involvement. In my latest forbes.com article, I talk about how AI can help.
Last week I posted another Forbes article, this one focused on how artificial intelligence and machine learning can help companies in mobile marketing. The ad ecosystem is complex and there are a number of ways, from demographics to fraud protection, Where the advanced techniques can help. Check my articles page for a link.
My annual (I’ve done it twice now, so that now fits) has been posted. I review some of the key stories I covered in 2018 and make some basic predictions for what will happen in the near-term future. Hint: Aritifical intelligence and machine learning are still early in the adoption lifecycle, but cloud technologies mean faster adoption curves than in the past.
I’ve published another article in my Management AI series that’s a subset of my forbes.com column. This one is a high level introduction to natural language processing (NLP) and natural language generation (NLG).
My latest article on Forbes describes how different components of AI are beginning to work together to improve manufacturing.
I’m playing with alternating between the publishing page and blog entries and am not sure which I like better.
Which businesses really need a data scientist? https://bit.ly/2JInbhj
My focus on business intelligence the last few years, my long term interest in artificial intelligence and the growth of machine learning came together to drive the content for my latest Forbes article.
In my work with TIRIAS Research, I’m covering machine learning. As part of that, I am publishing articles on Forbes. One thing I’ve started this month, with two articles, is a thread on management AI. The purpose is to take specific parts of AI and machine learning that are often described very technically, and present them in a way that management can understand what they are and, more importantly, why they provide value to decision making.