The Wimshurst machine is one of the oldest and best known electrostatic machines, consisting of its iconic two counter rotating disks and two Leyden jars. Most often you see someone hand cranking it, producing sparks, though we’ve seen it used for much more, including for powering a smoke precipitator for cleaning up smoke and even for powering a laser.
It works through an interesting sequence of events. Most explanations attempt to cram it all into one picture, requiring some major mental gymnastics to visualize. This often means people give up, resigned to assume these work through some mythical mechanics that defy a mortal’s ability to understand.
My phone can now understand me but it’s still an idiot when it comes to understanding what I want. We have both the hardware capacity and the software capacity to solve this right now. What we lack is the social capacity.
We are currently in a dumb state of personal automation. I have Google Now enabled on my phone. Every single month Google Now reminds me of bills coming due that I have already paid. It doesn’t see me pay them, it just sees the email I received and the due date. A creature of habit, I pay my bills on the last day of the month even though that may be weeks early. This is the easiest thing in the world for a computer to learn. But it’s an open loop system and so no learning can happen.
Earlier this month [Cameron Coward] wrote an outstanding pair or articles on AI research that helped shed some light on this problem. The correct term for this level of personal automation is “weak AI”. What I want is Artificial General Intelligence (AGI) on a personal level. But that’s not going to happen, and I am the problem. Here’s why.
What I particularly like about the Van de Graaff (or VDG) is that it’s a combination of a few discrete scientific principles and some mechanically produced current, making it an interesting study. For example, did you know that its voltage is limited mostly by the diameter and curvature of the dome? That’s why a handheld one is harmless but you want to avoid getting zapped by one with a 15″ diameter dome. What follows is a journey through the workings of this interesting high voltage generator.
Last week we covered the past and current state of artificial intelligence — what modern AI looks like, the differences between weak and strong AI, AGI, and some of the philosophical ideas about what constitutes consciousness. Weak AI is already all around us, in the form of software dedicated to performing specific tasks intelligently. Strong AI is the ultimate goal, and a true strong AI would resemble what most of us have grown familiar with through popular fiction.
Artificial General Intelligence (AGI) is a modern goal many AI researchers are currently devoting their careers to in an effort to bridge that gap. While AGI wouldn’t necessarily possess any kind of consciousness, it would be able to handle any data-related task put before it. Of course, as humans, it’s in our nature to try to forecast the future, and that’s what we’ll be talking about in this article. What are some of our best guesses about what we can expect from AI in the future (near and far)? What possible ethical and practical concerns are there if a conscious AI were to be created? In this speculative future, should an AI have rights, or should it be feared?
We tend to think that there was a time in America when invention was a solo game. The picture of the lone entrepreneur struggling against the odds to invent the next big thing is an enduring theme, if a bit inaccurate and romanticized. Certainly many great inventions came from independent inventors, but the truth is that corporate R&D has been responsible for most of the innovations from the late nineteenth century onward. But sometimes these outfits are not soulless corporate giants. Some are founded by one inventive soul who drives the business to greatness by the power of imagination and marketing. Thomas Edison’s Menlo Park “Invention Factory” comes to mind as an example, but there was another prolific inventor and relentless promoter who contributed vastly to the early consumer electronics industry in the USA: Powel Crosley, Jr.
The concept of artificial intelligence dates back far before the advent of modern computers — even as far back as Greek mythology. Hephaestus, the Greek god of craftsmen and blacksmiths, was believed to have created automatons to work for him. Another mythological figure, Pygmalion, carved a statue of a beautiful woman from ivory, who he proceeded to fall in love with. Aphrodite then imbued the statue with life as a gift to Pygmalion, who then married the now living woman.
Pygmalion by Jean-Baptiste Regnault, 1786, Musée National du Château et des Trianons
Throughout history, myths and legends of artificial beings that were given intelligence were common. These varied from having simple supernatural origins (such as the Greek myths), to more scientifically-reasoned methods as the idea of alchemy increased in popularity. In fiction, particularly science fiction, artificial intelligence became more and more common beginning in the 19th century.
But, it wasn’t until mathematics, philosophy, and the scientific method advanced enough in the 19th and 20th centuries that artificial intelligence was taken seriously as an actual possibility. It was during this time that mathematicians such as George Boole, Bertrand Russel, and Alfred North Whitehead began presenting theories formalizing logical reasoning. With the development of digital computers in the second half of the 20th century, these concepts were put into practice, and AI research began in earnest.
Over the last 50 years, interest in AI development has waxed and waned with public interest and the successes and failures of the industry. Predictions made by researchers in the field, and by science fiction visionaries, have often fallen short of reality. Generally, this can be chalked up to computing limitations. But, a deeper problem of the understanding of what intelligence actually is has been a source a tremendous debate.
Despite these setbacks, AI research and development has continued. Currently, this research is being conducted by technology corporations who see the economic potential in such advancements, and by academics working at universities around the world. Where does that research currently stand, and what might we expect to see in the future? To answer that, we’ll first need to attempt to define what exactly constitutes artificial intelligence.
There are certain design guidelines for PCBs that don’t make a lot of sense, and practices that seem excessive and unnecessary. Often these are motivated by the black magic that is RF transmission. This is either an unfortunate and unintended consequence of electronic circuits, or a magical and useful feature of them, and a lot of design time goes into reducing or removing these effects or tuning them.
You’re wondering how important this is for your projects and whether you should worry about unintentional radiated emissions. On the Baddeley scale of importance:
Pffffft – You’re building a one-off project that uses battery power and a single microcontroller with a few GPIO. Basically all your Arduino projects and around-the-house fun.
Meh – You’re building a one-off that plugs into a wall or has an intentional radio on board — a run-of-the-mill IoT thingamajig. Or you’re selling a product that is battery powered but doesn’t intentionally transmit anything.
Yeeeaaaaahhhhhhh – You’re selling a product that is wall powered.
YES – You’re selling a product that is an intentional transmitter, or has a lot of fast signals, or is manufactured in large volumes.
