A chronicle of the things I find interesting or deeply important. Exploring generally 4 pillars of intense research. Dynamic Cognition (what every one else calls AI), Self Healing Infrastructures (how to build technological Utopia), Autonomous work routing and Action Oriented Workflow (sending work to the worker) and Supermortality (how to live...to arbitrarily long life spans by ending the disease of aging to death.)
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Podcast recordings on the brain and artificial intelligence and how we get there.
I had a great session with Wai Tsang , moderated by Ben Thomas talking about artificial intelligence, how we go about creating artificial minds. Building on the ideas I've expressed in this blog for several years regarding the importance of autonomics, emotion and the fractal process to building a multi dimensional learning dynamic cognition. The talk was done in two parts which you can take in below:
I think that the author misses truths that have been in place that show that collectivization is not a process that started with the internet but has been with us since we started inventing things.
It seems that Mr. Lanier is not properly defining the contexts under which different problems can benefit or suffer from collectivization. He speaks in general terms of the loss of the potential for creators to extract profit from their work but misses that this is and was true of human civilization since we first picked up a rock to use as a crude hammer. New things make old things obsolete and people MUST adapt to what is displaced (be it a former human performance of that task or use of an older product) so as to main…
I have found as more non formally trained people enter the coding space, the quality of code that results varies in an interesting way.
The formalities of learning to code in a structured course at University involve often strong focus on "correctness" and efficiency in the form of big O representations for the algorithms created.
Much less focus tends to be placed on what I'll call practical programming, which is the type of code that engineers (note I didn't use "programmers" on purpose) must learn to write.
Programmers are what Universities create, students that can take a defined development environment and within in write an algorithm for computing some sequence or traversing a tree or encoding and decoding a string. Efficiency and invariant rules are guiding development missions. Execution time for creating the solution is often a week or more depending on the professor and their style of teaching code and giving out problems. This type of coding is devo…
The zeitgeist of Science fiction is filled with stories that paint a dystopian tale of how human desires to build artificial intelligence can go wrong. From the programmed pathology of HAL in 2001 a space odyssey, to the immediately malevolent emergence of Skynet in The Terminator and later to the humans as energy stores for the advanced AI of the Matrix and today , to the rampage of "hosts" in the new HBO series Westworld.
These stories all have a common theme of probing what happens when our autonomous systems get a mind of their own to some degree and no longer obey their creators but how can we avoid these types of scenarios but still emerge generalized intelligence that will leverage their super intelligence with empathy and consideration the same that we expect from one another? This question is being answered in a way that is mostly hopeful that current methods used in machine learning and specifically deep learning will not emerge skynet or HAL.