> We had hoped to build a pilot project in China, but recent policy changes here in the U.S. have made that unlikely.
Maybe running pilot projects in U.S. instead of China can solve the first issue he mentions?
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> We had hoped to build a pilot project in China, but recent policy changes here in the U.S. have made that unlikely.
Maybe running pilot projects in U.S. instead of China can solve the first issue he mentions?
Very interesting, I did not know that.
There’s an interesting use case for Facebook’s Machine Learning algorithms
Are there other great and insightful blogs from important personalities like this one? Maybe warren buffet's blog?
Earlier quoted context omitted.
Has Bill ever been good at predictions? No mention of smartphones or social media in The Road Ahead. Blindsided by how quickly the Internet developed, underestimated "bazaar" economies that enabled millions of people building both software and content. All the smart home stuff he was in love with has gone hardly anywhere. I think he's very smart and great at setting huge goals then hitting them, but I'm not sure he's…
His most famous prediction was one he helped make true. Microsoft's original mission statement was "A computer on every desk and in every home"
"[Warren Buffett] says his measure of success is, “Do the people you care about love you back?” I think that is about as good a metric as you will find." I love this.
The problem is that Warren Buffet doesn't care, as in love which is what he's implying, about 99.99% of the population. If he gives a large portion of the population diabetes (BerkshireHathaway own CocaCola stock) and uses the profits to buy his family aeroplanes, by this definition he is a success.
There's really no innovation needed for the latter. Just educate people and when that fails implement better controls, i.e. sugar taxes on sodas and food. Fundamentally the goal should be get rid of refined sugars in foods, especially high fructose corn syrup.
> The only problem where I don’t yet see a clear path forward yet is how to develop more efficient ways to recruit patients for clinical trials. Without a simple and reliable diagnostic for Alzheimer’s, it’s hard to find eligible people early enough in the disease’s progression who can participate in trials. There’s an interesting use case for Facebook’s Machine Learning algorithms