The Quiet Rise of Machine Learning-Like IBM Watson Offers With Speed and Learned Analytics-Congress Needs Technology This To Make Better Laws & Collaborate

Here we go again and again and here’s a video that helps explain some of what machine learning is. It’s not easy to understand, but the main to pay attention to is the speed, use of speech recognition to make it simple and how queries made create are fast and stored, like cache. In other words when the same query is run again, it’s there as it has been already done, or when updating, adding new information goes quickly. This article explains on how many don’t see how it’s already working in other industries in different formats. Again, I ask don’t you think lawmakers would want this? In the presentation to the Congress I can only perhaps guess that being it was on Jeopardy, they only could see this as value for a game, but listen as that is not so.

They need some “Algo Men” on staff soon too, replace the lobbyists with these.

More Congressional Testimonies About Health IT–Members of Congress Could Entertain Getting an “Algo Man” on Staff As Wall Street and Health Insurers Have Them–Don’t Leave Home Without One

You might say I’m a little relentless on this topic and you guessed right as I am tired of seeing digital illiteracy in lawmaking as the US is getting their butts kicked all over the place when we have a very advanced business world and then when it comes to some procedures in laws, well here comes Fred Flintstone and Barney Rubble back behind the steering wheel. Let’s get some intelligent algorithms out there like every one else is doing. You can read the full article below and see what some other industries are doing too. I’m not a big fan of banks but when I look at this picture of Blankstein from Goldman during the testimonies and him trying to dig through the groves of paper they produced, what gives? Do you think he operates this way, not a chance. Why didn’t let him download into a format he could query and locate the information faster so he could answer? Duh? Do yourself a favor when you look at the picture and remember those were the folks that used this and other types of technologies to kick out butts and take our money in 2008. They couldn’t have done it without the algorithms.

IBM Watson Capabilities Being Pitched to Financial Industry-Congress Must Not Have Felt They Needed This So Further Behind We Fall With Effective Intelligent Lawmaking

The post below will give you a perfect example of digital illiteracy. What is this, “if we don’t understand it we are not going to fund” or “we don’t that intelligence”? This takes me back to not funding cloud services last year as the Senate didn’t fund it, but read below and you can see where one is ready to spend millions on a project that will go nowhere and someone thinks IT services grow on trees. I’m just one of many frustrated individuals out here who knows this stuff but hopefully sharing will enlighten many more. This is survival of our country at stake here and I want to survive and bring those up to a higher level so it happens.

Digital Illiteracy Is Killing Us With New Bill Wanting MD Medicare Compensation Put Online-No Clue on the Cost, Time and Truckloads of Errors to Audit and Correct

I apologize to my readers but I will continue on this effort until some progress gets made somehow so we don’t sink. Smart software could lead to a “Smart Congress”. BD

Machine Learning

The concept of machine learning was brought to the forefront for the general masses when IBM's Watson computer appeared on Jeopardy and wiped the floor with humanity. For those same masses, machine learning quickly faded from view as Watson moved out of the spotlight ... or so they may think.

Machine learning is slowly and quietly becoming democratized. Goodreads, for instance, recently purchased Discovereads.com, presumably to make use of its machine learning algorithms to make book recommendations.

To find out more about what's happening in this rapidly advancing field, I turned to Alasdair Allan, an author and senior research fellow in Astronomy at the University of Exeter. In an email interview, he talked about how machine learning is being used behind the scenes in everyday applications. He also discussed his current eSTAR intelligent robotic telescope network project and how that machine learning-based system could be used in other applications.