Turbotodd

Ruminations on tech, the digital media, and some golf thrown in for good measure.

Cray Cray and the PGA

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Happy Friday.

For golfers everywhere, it’s an especially special week (and weekend).

Normally, the PGA Championship is the last major championship of the year, played in the heat of the August sun.

This year, the tournament has been moved up to mid-May, and is being played at what they call the “peoples’ country club,” Bethpage Black.

Bethpage Black is the hardest of a number of golf courses open to the general public in Bethpage State Park in Long Island, New York.

It has also been home to a couple of U.S. Opens, one in 2002 and again in 2009…it was, in fact, the first public golf course to host a U.S. Open.

So, that’s the backstory. And while everyone is excited to hear about Tiger Woods play after winning the Masters this year, it was Brooks Koepka, three-time major and one-time PGA Championship winner who sunk putts from every which direction and every which length yesterday who took the lead at 7 under par.

Koepka is due back on the Black this PM, and while he has a couple of great players making chase, including Jordan Spieth who’s in today at a cumulative 5 under and Dustin Johnson (-4), it appears Koepka is in charge of his destiny this PM.

As for destiny, let’s jump over to some Friday PM tech news.

First up, for those of you who remember the hey day of supercomputing (whenever that was), you’ll remember Cray Inc.

Hewlett Packard Enterprise is taking Cray off the board for $1.30 billion, roughly $35 per share and a premium of 17.4 percent to Cray’s last close, according to Reuters.

At last count, Cray’s supercomputing systems can handle big data sets, converged modeling, simulations, AI, and analytics workloads.

If this news makes you ill, you might want to check into Health at Scale. TechCrunch is reporting that the AI healthcare startup has raised $16M in a Series A round.

The startup has founders with both medical and engineering backgrounds, and writes that it “wants to bring machine learning to bear on healthcare treatment options to produce outcomes with better results and less aftercare.”

The idea is to make treatment decisions more data-driven. While they aren’t sharing their data sources, they say they have information, from patients with a given condition, to doctors who treat that condition, to facilities where the treatment happens. By looking at a patient’s individual treatment needs and medical history, they believe they can do a better job of matching that person to the best doctor and hospital for the job. They say this will result in the fewest post-operative treatment requirements, whether that involves trips to the emergency room or time in a skilled nursing facility, all of which would end up adding significant additional cost.

Anything to improve the condition of the American healthcare system.

Written by turbotodd

May 17, 2019 at 12:41 pm

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