First up, from PhysOrg, July 26:
Energy, mass, velocity. These three variables make up Einstein's iconic equation E=MC2. But how did Einstein know about these concepts in the first place? A precursor step to understanding physics is identifying relevant variables. Without the concept of energy, mass, and velocity, not even Einstein could discover relativity. But can such variables be discovered automatically? Doing so could greatly accelerate scientific discovery.
This is the question that researchers at Columbia Engineering posed to a new AI program. The program was designed to observe physical phenomena through a video camera, then try to search for the minimal set of fundamental variables that fully describe the observed dynamics. The study was published on July 25 in Nature Computational Science.
The researchers began by feeding the system raw video footage of phenomena for which they already knew the answer. For example, they fed a video of a swinging double pendulum known to have exactly four "state variables"—the angle and angular velocity of each of the two arms. After a few hours of analysis, the AI produced the answer: 4.7.
"We thought this answer was close enough," said Hod Lipson, director of the Creative Machines Lab in the Department of Mechanical Engineering, where the work was primarily done. "Especially since all the AI had access to was raw video footage, without any knowledge of physics or geometry. But we wanted to know what the variables actually were, not just their number."
The researchers then proceeded to visualize the actual variables that the program identified. Extracting the variables themselves was not easy, since the program cannot describe them in any intuitive way that would be understandable to humans. After some probing, it appeared that two of the variables the program chose loosely corresponded to the angles of the arms, but the other two remain a mystery.....
....MUCH MORE
You just don't know how the AI is doing what it's doing. And it can't won't tell you.
And on the spookiness of AI in investing and the phenomena of simultaneous discovery:
....On Saturday September 23, 6:28 AM PDT we posted "Cracking Open the Black Box of Deep Learning" with this introduction:
One of the spookiest features of black box artificial intelligence is that, when it is working correctly, the AI is making connections and casting probabilities that are difficult-to-impossible for human beings to intuit.Today Bloomberg View's Matt Levine commends to our attention a story about one of the world's biggest hedge funds and prize-putter-upper of what's probably the most prestigious honor in literature, short of the Nobel, the Man Booker Award.
Try explaining that to your outside investors.
You start to sound, to their ears anyway, like a loony who is saying "Etaoin shrdlu, give me your money, gizzlefab, blythfornik, trust me."
See also the famous Gary Larson cartoons on how various animals hear and comprehend:...
On Tuesday September 26, 2017, 11:00 PM CDT Bloomberg posted:
The Massive Hedge Fund Betting on AI
The second paragraph of the story:
...Man Group, which has about $96 billion under management, typically takes its most promising ideas from testing to trading real money within weeks. In the fast-moving world of modern finance, an edge today can be gone tomorrow. The catch here was that, even as the new software produced encouraging returns in simulations, the engineers couldn’t explain why the AI was executing the trades it was making. The creation was such a black box that even its creators didn’t fully understand how it worked. That gave Ellis pause. He’s not an engineer and wasn’t intimately involved in the technology’s creation, but he instinctively knew that one explanation—“I can’t tell you why …”—would never fly with big clients looking for answers when Man inevitably lost some of their money...Now that is just, to reuse the phrase, spooky. Do read both the Bloomberg Markets and the Bloomberg View pieces but I'll note right now it's only with Levine you get:
"I imagine a leather-clad dominatrix standing over the computer, ready to administer punishment as necessary."
Last seen in 2017's "We Might Be Getting Closer To Understanding How True 'Black Box' AI Makes Decisions"
