@Benshapiro and @Profgalloway don’t agree on much. But for this debate, they agreed to start with the same set of facts.
We brought Ben and Scott together to go head-to-head on some of the biggest questions facing Americans today. Because data doesn’t argue. They do.
Moderated by PBS @NewsHour's @GeoffRBennett, with Steve Ballmer running the Fact Desk, the debate puts a simple idea to the test: Can starting with #JustTheFacts create room for productive debate – and even common ground?
Watch the full debate: https://t.co/1wP2bTuCdS
Breaking News: President Trump’s new press secretary, Katie Zacharia, was fired after less than a week on the job, according to people familiar with the matter. https://t.co/IDuom8hTtW
Introducing the pre-launch, pre-stealth reveal of WatchfulEye. With Deep House.
You'll know more soon, pending agreement on what constitutes “more” and “soon.”
Introducing the pre-launch, pre-stealth reveal of WatchfulEye. With Deep House.
You'll know more soon, pending agreement on what constitutes “more” and “soon.”
(1/6) From @GoogleDeepmind’s AlphaGo to AlphaZero, we saw machines find moves that reached beyond what we’d imagined for them. No one taught them those strategies. They emerged from reinforcement learning: playing, failing, and trying again under a single binary task reward for success or failure. Inspired by them, we couldn’t help but wonder: what might a robot discover if we gave it that same freedom to learn?
That question led us to AlphaNIST. Starting tabula rasa, with that same binary reward plus only a simple control cost, a single policy solves all 20 @NIST assembly tasks at a 98.2% success rate in simulation. More surprising still, AlphaNIST can complete 10 different tasks in a row, receiving that reward only once, after all 10 are done.
Just as AlphaGo’s strategies surprised its creators, AlphaNIST discovered dexterous strategies we couldn’t have come up with ourselves.
Paper: https://t.co/HZBYgG7SWK
Website: https://t.co/VyUKiYFI2y