Mead is absolutely right that to keep progress going for the next 20-30 years we will need a different approach to engineering based on more sophisticated physics. The math for quantum physics is challenging but the "intuitive" concepts are even more challenging.
Here, you might want to read these few screens, to see how scientific discoveries hinge on what came before. This is related to quantum mechanics and to concepts that we now take for granted that Einstein himself initially disagreed with.
You won't notice any of these luminaries claiming that everything before was "wrong," if you take a read. It's all about refinement.
I buy it less now than I did on first read.
Leaving everything up to intuition, because somehow that makes it all more fun, simply leads to chaotic thinking. The result will be, a lot of loud noise from the clueless, and still the need for logical and incremental thought by those who actually produce anything of value.
Most advances in science are not the step changes the press like to dwell on. Most are imrovements, or let's say generalizations, of what came before. By FAR. You don't get there unless you know what came before.
Einstein did not invalidate Isaac Newton. He merely showed that Netwon's ideas were valid only at low speeds. The Bohr atom might have been simplistic, but just as it refined the atom models that came before it, in turn it leads to modern models, with weirder looking orbitals and subatomic particles.
"How many times has earlier science been later proven wrong?"
Wrong question. The better question is, how many times have those who didn't know the previous science ever made any useful discoveries? Very few, is my bet.
Right on! This is EXACTLY Carver's point.
Everyone thinks what was done in the past MUST without fail be used in defining the future. Wrong.
It is important as engineers and scientist that all things accepted as truth be continually questioned. Otherwise we risk discovering nothing new.
How many times has earlier science been later proven wrong? Do some of us really believe it has all been figured out CORRECTLY? I for one think not.
Interesting talk, but I'm not sure I buy it. There are only about a zillion different misconceptions the average joe labors under most of his life, which his own intuition says make a lot of sense. Sometimes, it just becomes imperative to "do the math." Or you're indeed never going to move forward. Is this arrogance or is this reality?
My favorite recent example of this is something called the Iris Engine. Look it up. Intuitively, if someone tells you that this Iris Engine has a lot more "working area" than a piston engine, and that this much greater "working area" translates to better efficiency, many people would be struck by the brilliance of the concept. Wow, how come "they" didn't think of this sooner?
Intuition is tricky. That conclusion is, of course, false. In a heat engine, Carnot cycle, efficiency is a function of the temperature difference between combustion and exhaust. That temperature difference, in an internal combustion engine, is governed entirely by the compression ratio, and *not at all* by the "working area."
Is this intuitive? I'm not sure. It is once you've done the math, of course. The real answer can be derived using the gas law (PV=nRT) and Boyle's law (P1V1=P2V2).
My thesis is, truly brilliant people, like Prof. Meade, not to mention Albert Einstein, may well be able to intuit a lot of concepts without having to do the math. I very much doubt most people have this luxury. And even these brilliant people spend most of their lives attempting to prove what their intuition might have suggested to them in an instant. Because even they usually get it wrong, at least partially.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.