A lot of academic work is being poured into machine learning. The idea is that computers can see what works, what doesn’t, and come up with new strategies. This is a complex problem; legions of PhDs have thrown their careers at it.
I think there is a simpler approach. Boredom and frustration. Today I was watching Widget deal with some sticks I gave her. She grabbed one in her mouth and ran towards her nest. For some inexplicable reason the 10cm long stick stopped suddenly when she attempted to enter the 3cm wide tunnel to her nesting box. Oh well, if you don’t succeed, try again. Which she did. Again, it didn’t work. After several more attempts she was clearly frustrated and changed her approach. She tried dragging the stick from one end. This worked a little better, but the stick got jammed at the first tight-radius turn. After several minutes of fighting the stick, she got bored and turned her attention to other matters.
This is behaviour one doesn’t see in most computers. They will quite happily execute an infinite loop until the Sun burns out. My proposal is that the computer should periodically stand back and do a self-evaluation. What percentage of the task has been completed? If this percentage is not changing (or even declining) over a significant period of time then there’s no point in grinding on. There are two options:
- Frustration. This technique isn’t working. Try another technique if one is available. Even one that in theory should be less effective might be better (due to a special case or some bug). An interesting and cheap source for other techniques might be previous versions of the offending code in the repository.
- Boredom. Nothing is happening. Alternatives have failed. Bail out and devote your attention to other things.
Some systems already have these concepts implemented to a certain extent. My Roomba understands the concept of frustration. I watched it get trapped under my desk the other day, ricocheting off the boundaries in a deterministic pattern like a ball in Arkanoid. After a short period it got frustrated at the constant wall-banging and switched to wall-following mode instead. It worked and it freed itself.
Benedict Evans: Ways to think about cars
First, the shift to electric reduces the mechanical complexity of cars a great deal. No transmission or internal combustion engine means far fewer moving parts. That may also change the sophistication and capital required to design and build cars, which, in turn, may change who can build them and how they get built. Gear boxes and premium sports transmissions turn into software in the same way that electromechanical calculating machines or cameras got turned into software.
.. Second, the rise of on-demand car services changes what it means to own a car and changes who buys them, and that in turn may also change what they look like. These models won’t work for everyone everywhere: there will be a point of equilibrium in each urban area where supply, demand and price stabilize at a sustainable level (after the price wars and sign-up bonuses are gone), and that point of equilibrium will look different in different places. The number of people who stop having a car (or using one) or who stop using public transport will vary, and won’t be universal, but will be substantial.
.. That in turn means that the cars get bought the way Hertz buys cars, or – critically – the way corporate PCs get bought. In this world what matters is ROI and a check-list of features, not flair, design, innovation or fit and finish.
.. That poses a challenge for Apple, and indeed Tesla. If the users are not the buyers, the retracting door handles or diamond-cut chamfers don’t matter.
.. From a technology point of view, what’s really happening is that we move road transport from circuit-switching (with manual switchboard operators) to packet-switching.
Do you trust Larry Page?
The problem for Page, though, is that he is not a strategy and business nerd. Page is, for lack of a better description, a change-the-world nerd, and it seems clear that he found the day-to-day business of managing a very profitable utility to be not only uninteresting but a distraction from what he truly wanted to do.
.. That, though, leads to a bigger question: why should all of these disparate ventures be a part of the same company at all?
.. That is actually an easy one to answer: Page and Brin can do whatever they want because of Google’s dual-class structure. From Google’s IPO letter:
.. As Page sees it, it all comes down to ambition – a commodity of which the world simply doesn’t have a large enough supply. In the midst of one of its periodic booms, Silicon Valley, still the epicentre of the tech business world, has become short-sighted, he says…
Page estimates that only about 50 investors are chasing the real breakthrough technologies that have the potential to make a material difference to the lives of most people on earth. If there is something holding these big ideas back, it is not a shortage of money or even the barrier of insurmountable technical hurdles. When breakthroughs of the type he has in mind are pursued, it is “not really being driven by any fundamental technical advance. It’s just being driven by people working on it and being ambitious,” he says. Not enough institutions – particularly governments – are thinking expansively enough about these issues: “We’re probably underinvested as a world in that.”
Henry David Thoreau’s Walden: Technophobia
We are in great haste to construct a magnetic telegraph from Maine to Texas, but Maine and Texas, it may be, have nothing important to communicate. Either is in such a predicament as the man who was earnest to be introduced to a distinguished deaf woman, but when he was presented, and one end of her ear trumpet was put into his hand, had nothing to say. As if the main object were to talk fast and not to talk sensibly.