I finished listening to Coach: Lessons on the Game of Life.
I finished listening to In The Plex: How Google Thinks, Works, and Shapes Our Lives.
Suspicious emails: unclaimed insurance bonds, diamond-encrusted safe deposit boxes, close friends marooned in a foreign country. They pop up in our inboxes, and standard procedure is to delete on sight. But what happens when you reply? Follow along as writer and comedian James Veitch narrates a hilarious, months-long exchange with a spammer who offered to cut him in on a hot deal.
And as a follow up, “The agony of trying to unsubscribe”.
There are, inevitably, miseries to come: an increasingly reactionary Supreme Court; an emboldened right-wing Congress; a President whose disdain for women and minorities, civil liberties and scientific fact, to say nothing of simple decency, has been repeatedly demonstrated. Trump is vulgarity unbounded, a knowledge-free national leader who will not only set markets tumbling but will strike fear into the hearts of the vulnerable, the weak, and, above all, the many varieties of Other whom he has so deeply insulted.
I finished listening to Sapiens: A Brief History of Humankind.
Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion,” and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.
Seasons of hope and despair
Accordingly, one can view artificial intelligence as a quest to find shortcuts: ways of tractably approximating the Bayesian ideal by sacrificing some optimality or generality while preserving enough to get high performance in the actual domains of interest.
Metaphorically, we can think of a probability as sand on a large sheet of paper. The paper is partitioned into areas of various sizes, each area corresponding to one possible world, with larger areas corresponding to simpler possible worlds. Imagine also a layer of sand of even thickness spread across the entire sheet: this is our prior probability distribution. Whenever an observation is made that rules out some possible worlds, we remove the sand from the corresponding areas of the paper and redistribute it evenly over the areas that remain in play. Thus, the total amount of sand on the sheet never changes, it just gets concentrated into fewer areas as observational evidence accumulates. This is a picture of learning in its purest form.
State of the art
One sympathizes with John McCarthy, who lamented: “As soon as it works, no one calls it AI anymore.”
The computer scientist Donald Knuth was struck that “AI has by now succeeded in doing essentially everything that requires ‘thinking’ but has failed to do most of what people and animals do ‘without thinking’—that, somehow, is much harder!” 60 Analyzing visual scenes, recognizing objects, or controlling a robot’s behavior as it interacts with a natural environment has proved challenging. Nevertheless, a fair amount of progress has been made and continues to be made, aided by steady improvements in hardware.
Now, it must be stressed that the demarcation between artificial intelligence and software in general is not sharp. Some of the applications listed above might be viewed more as generic software applications than as AI in particular—though this brings us back to McCarthy’s dictum that when something works it is no longer called AI.
The algorithm just does what it does; and unless it is a very special kind of algorithm, it does not care that we clasp our heads and gasp in dumbstruck horror at the absurd inappropriateness of its actions.
Opinions about the future of machine intelligence
For example, Nils Nilsson has spent a long and productive career working on problems in search, planning, knowledge representation, and robotics; he has authored textbooks in artificial intelligence; and he recently completed the most comprehensive history of the field written to date. 79 When asked about arrival dates for HLMI(“human-level machine intelligence”), he offered the following opinion: 80 10% chance: 2030 50% chance: 2050 90% chance: 2100
- Lacuna – an unfilled space or interval; a gap.
I finished reading Superintelligence: Paths, Dangers, Strategies.