I’ve written two articles this month about government policy towards AI. The first is about “Turning Point”, a book by a couple of leads at the Brookings Institution, and a nifty webinar interview with the authors. The second is about a report and webinar driven by the Bipartisan Policy Center. The book was excellent, the report not so much. Even with different results, it is important to note that folks in the Beltway are beginning to speak out on the issue.
Links to three new articles are over on my articles page. They are about broadband (on LinkedIn) and then a couple of AI related articles on Forbes.com.
I don’t think I’ll be publishing on Forbes as often. They just took away pay from less frequent posters. We didn’t make much money anyway, but I certainly wouldn’t make enough to justify trying to publish the number of articles I’d have to in order to make any money in the new method. The benefits don’t justify the time spent or the drop in quality that pumping out that many articles would create.
If I was a journalist full time, that might make sense, but I earn my money through content writing and marketing consulting. I’ll keep writing for Forbes, it’s fun; but perhaps not as often.
I have a couple of new articles on forbes.com that I’ve posted this month. One is on software to help lawyers analyze a case based on similar cases and another discusses the fun that is AI recreating the closeness between hardware and software that was around decades ago. Hardware companies are very involved in providing software to help developers use complex chipsets. Check my articles page or my forbes.com profile.
In a move joining the children of two famous early tech companies, Hewlett Packard Enterprise (HPE) announced they are going to acquire Cray Inc. It’s a smart move, but it brings a bit of nostalgia to my emotions. Read my latest Forbes.com article.
A wide range of AI tools are being applied to the retail experience. Computer vision hold a central place in that it helps track real world movements in stores. My latest Tech Target article discusses this.
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.
Cloudera held a pretty impressive web event this morning. It was a mini-conference, with keynotes, some breakout tracks and even a small vendor area. The event was called Cloudera Now, and the link is the registration one. I’ll update it if they change once it’s VOD.
The primary purpose was to present Cloudera as the company for data support in the rapidly growing field of Machine Learning (ML). Given the state of the industry, I’ll say it was a success.
As someone who has an MS focused on artificial intelligence (ancient times…) and has kept up with it, there were holes, but the presentations I watched did set the picture for people who are now hearing about it as a growing topic.
The cleanest overview was a keynote presentation by Tom Davenport, Professor of IT and Management, Babson College. That’s worth registering for those who want to get a well presented overview.
Right after that, he and Amy O’Conner, Big Data Evangelist at Cloudera, had a small session that was interesting. On the amusing side, I like how people are finally beginning to admit that, as Amy mentioned, that the data scientist might not be defined as just one person. I’ll make a fun “I told you so” comment by pointing to an article I published more than three years ago: The Myth of the Data Scientist.
After the keynotes, there were three session of presentations, each with three seminars from which to choose. The three I attended were just ok, as they all dove too quickly into the product pitches. Given the higher level context of the whole event, I would have liked them all to spent more time discussing the market and concepts far longer, and then had much briefer pitch towards the end of the presentations. In addition, they seem too addicted to the word “legacy,” without some of them really knowing what that meant or even, in one case, getting it right.
However, those were minor problems given what Cloudera attempted. For those business people interested in hearing about the growing intersection between data, analytics, and machine learning, go to Cloudera’s site and take some time to check out Cloudera Now.