- Electric car company Tesla in massive public pissing match with New York Times. Sounds like some fault on both sides to me. Fascinating how much data the Tesla is logging. I wonder how much is getting uploaded from the car remotely?
- NYT article on one of the main Chinese espionage operations stealing data from US companies. China is doing this on an absolutely massive scale. Computer security companies see it every single day. It's really quite outrageous and this article is a good primer.
Tuesday, February 19, 2013
Tuesday Links
Only two links today: couldn't find anything else of interest.
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4 comments:
" Sounds like some fault on both sides to me."
What did Tesla do wrong?
Unknown - well, at a minimum, Broder's explanation that he was driving round the parking lot looking for the supercharger, rather than deliberately trying to exhaust the battery, sounds pretty plausible, and Tesla publicly accused him of deliberate bad faith on that point without really being in a position to judge the question.
I think the plausibility of the explanation depends on how many laps of a 100 car lot is half a mile?
One or two, and it is plausible. Past that, it looks increasingly like an attempt to generate a story.
Gregor looks pretty unrealistic to me.
He's way too obsessed with cheap direct manufacturing labor.
Let's break that down:
"Cheap": Wage arbitrage may move jobs around, but it has little to do with labor productivity, which has relentlessly continued to increase regardless of wages or energy prices.
"direct": the guys on the floor who assemble the stuff are becoming less and less important, with or without "robots". Knowledge workers are a larger and larger proportion of the workforce even in oldline industrial companies, like GE and GM. The extent to which knowledge work can be made more efficient will determine the extent of future efficiency gains.
"manufacturing": goods production continues to increase in volume globally. In the OECD, it requires less labor to produce, and services are a larger and larger portion of the economy. Again, service productivity gains (and our ability to measure them) will determine reported economic growth.
That last deserves emphasis: it's much easier to measure the volume and quality of goods. How do we measure the increase in productivity and quality caused by Da Vinci robots? Are the statisticians in the BLS capturing reduced recovery times from closed surgery, or the reduced risk of side effects caused by higher quality lasers for cataract surgery?
I really don't think so.
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