None of the ideas on your blogs address how to "end the Turing madness" in a way that will still allow you to post on Slashdot.

I disagree but, just in case you missed it, read How to Solve the Parallel Programming Crisis.

The use of encryption is only intended to provide a way for legitimate remote users to gain supervised access to the system without having to hack into it. The real culprit behind bad security is software reliability. Attackers look for and try to exploit the defects in the software. Why is software defective? Because (it's the bugs, stupid!) the Turing/Von Neumann model of computing is inherently insecure and unreliable. Why? Because timing is not an essential part of the model. I predict that this decade will see the end of the Turing madness and that the future of computing is non-algorithmic. There is no alternative and the sooner, the better.

You're a physicist, I presume.

This is just more chicken feather voodoo physics from a bunch of crackpots and con artists within the physics community who are facing the prospect of seeing their funding reduced. This is complete BS in the not even wrong category. Physicists are completely clueless as to the nature of the universe. Under the assumption that everybody else is just as clueless as they are, they feel they can safely conjure BS as of thin air and sell it to a credulous public as bona fide science. But not everybody is stupid.

Here is a simple test that will prove that physicists like Joseph Lykken are clueless. Ask any physicist, what causes a body in relative inertial motion to remain in motion? I guarantee you will come face to face with either ignorance or outright superstition. If physicists don't even know what causes motion (their denials notwithstanding), how valid are their pronouncements about the birth and demise of the universe? Not very much, in my opinion.

True AI will appear on the world scene decades before these guys finish mapping anything and long before they even begin to understand what they have mapped. You could map a billion cortical columns but, unless you know what it is supposed to do and how it evolves during learning, you understand diddly squat. All you have is a gigantic map with no labels. The best way to understand the brain is by generating multiple hypotheses and principles that we think might lead to intelligence and writing algorithms to simulate biologically plausible models based on those principles. The principles are bound to be very few in number compared to the astronomical number of possible neural configurations that the brain can take during its lifetime or even while it is paying attention to some new patterns in its sensory space. Which of those configurations are we planning to map? The government is to be lauded for embarking on such grand projects but I think that, in this case, our tax money would be better served by taking a more sensible approach. Sorry.

He even calculated that the end of the world would come in 2030. He did by interpreting Biblical metaphors! And yet, with all that creationist (although Newton did not believe that the world was only a few thousand years old) religious baggage, he managed to be the father of modern physics. What have you done for yourself lately?

Anybody who thinks we are going to colonize the solar system, let alone the star systems beyond, with a bunch of cockamamie rockets is out to lunch. The idea that space propulsion is best done in a vehicle that moves forward by throwing things out the back is primitive to the extreme. Reactive propulsion precedes Newton and even Ptolemy. It's pathetic, really.

But do not let the preceding get you down because a new and fabulous era of space travel is about to be born. Soon, physicists will wake up from their stupor and realize that their understanding of motion is fundamentally flawed. We are on the verge of a breakthrough in physics that will make almost every current approach to energy production and transportation obsolete. It is based on a new analysis of the causality of motion. Essentially, Aristotle was right to insist that motion is caused. As a result, we are swimming in an immense lattice of energetic particles, an ocean of clean energy, lots and lots of free energy. Soon, we will understand enough about the lattice to exploit it for energy production and propulsion. Our future vehicles will move at tremendous speeds and negotiate right angle turns without slowing down and without incurring damages due to inertial effects. Floating sky cities impervious to earthquakes, tsunamis and bad weather, unlimited clean energy, earth to Mars in hours, New York to Beijing in minutes... That's the future of energy and travel. It will happen in your lifetime.

Physics: The Problem With Motion. You don't understand motion even if you think you do.

As far as I can tell, there are lots of other designs, many of them far superior to neural networks, especially for such basic things as representing knowledge.

A brain cannot use discrete time-sensitive information (signals) from the senses unless this information is organized hierarchically in memory. There is no way around using a hierarchy for the classification of knowledge and a spiking neural network is the best way to construct such a hierarchy. Using anything other than neurons (signal processors), dendrites (input list), axons (output list) and synapses (connectors) is a waste of effort.

The writing is on the wall. Machines will replace everybody, period. And I don't just mean the factory worker, the fry cook, the maid or the gardener. I mean, every effing body. Your PhD won't mean diddly squat. So all this silly talk about preserving jobs is pointless. Both capitalism and communism were wrong from the start because they base the economy on slave labor. Why do I say slave labor? Because unless you own land and the ability to make a living on your land, you are at the mercy of someone else. We, humans, are territorial animals and we should all be living on our own domains. Capitalism gives control of the land to a few and enslaves the rest. Communism takes the land away completely and enslaves everybody. The arrival of intelligent machines will destroy both.

We need a land based, jobless economy where the land is divided for an inheritance (not for a price) and where only individuals have the right to own intelligent robots, not the corporations. And since robots will make robots, robots will be dirt cheap or, at least, as cheap as the energy supply will allow. Politicians better stop promising us jobs (as if they were doing us a favor) because we don't want no stinking jobs. We, humans, are gods. We want synthetic intelligent servants to do our work for us, all of it. We just want to sit by the pool and enjoy our margaritas and delicacies and rule our own land. We're tired of being slaves to invisible masters.

Just as I thought. It's not the legal mafia that is at fault here. It's the intellectual property system that is the law of the land. We need a better system that rewards inventors and creators for their hard work but does not infringe on the right of the people to be free.

Geoffrey Hinton’s work in back propagation and deep learning are an incremental improvement over the overly simplistic neural networks of the 90s, but "real progress", not even close. His focus on Bayesian networks has failed to deliver just like the symbolic AI that preceded it

Your arguments are not based on facts. The truth is that Kurzweil likes Hawkins' approach and Hawkins' Hierarchical Temporal Memory is a Bayesian network. It was designed from the ground up to use Bayesian statistics for perceptual learning. I am not saying that Hawkins' work is worthless but that it is seriously handicapped by the Bayesian curse.

Lately Kurzweil has come around to see that symbolic and bayesian networks have been holding AI back for the past 50 years. He is now a proponent of using biologically inspired methods similar to Jeff Hawkins' approach of Hierarchical Temporal Memory.

I don't get this. Hawkins' Hierarchical Temporal Memory is a Bayesian network. Dileep George, the mathematician and Bayes fanatic who co-founded Numenta, made sure of that. The last I heard, the Bayesian Brain hypothesis is something that both Hawkins and Kurzweil believe to be the correct approach to AI. They are wrong because, as Turing Award winner Judea Pearl explained, people and animals are not probability thinkers but cause/effect thinkers. And this is coming from a man who spent an enormous amount of time and effort championing the Bayesian approach to AI.

Nope. It was printed by Steve Jobs' secret giant 3-D minimalist aluminum/glass printer. Even the imacs were printed.

LOL. You guys are funny.

Competent AI researchers at least notice that they do not have a clue how to model what they want to build, and as such have a change of success.

Oh, they have a clue alright. They are convinced that the brain uses Bayesian statistics for perceptual learning. They are wrong.

You have it all figured out (wrongly) and have none.

Nope. Why do you put words in my mouth in such a dishonest way? You got a pony in this race? I've only figured out a small part of it but I've been at it for a long time and, lately, I'm making progress by leaps and bounds. Keeps your ears and eyes open.