James Gunn Throws Shade at Cavill’s Muscle Suit | Superman Suit Debate

Comment: They normally dont take these or put these on. Ive seen many materials replicated by tattoos. Id be surprised if they couldnt achieve any material look with muscles showing by using a spray paint like technique instead of fabric

Richard Hanania vs. Liron Shapira — AI Doom Debate

The problem is I don't think much can be done. Because I think there are likely beyond nuke superweapons similar to hypothetical hard nano that are easy to obtain for an asi. I also don't think an asi needs a large data center, that helps, but even one or a few entities qualitatively beyond Einstein as Einstein is beyond a monkey and with all the knowledge of humanity can likely obtain impossible to stop weapons. And I think this is attainable by even lone secret military labs, and such labs won't be stopped regardless of regulations or laws.

Comment on cool gundam ai music video from youtuber FantasyRemaster

 

Comment:  algorithms are getting faster and cheaper to run. But without copyright reform only small clips can likely be made even if it eventually becomes practical to remake the whole series. A full 1 for 1 full series remaster would likely need blessing of copyright owners. But currently the laws say ai gen is copyright free, which is also a problem on its own. We definitely need new laws to enable fair use and sharing of royalties while retaining some level of rights to those that modify and update content with ai tools

IS AGING PROGRAMMED? Aubrey de Grey vs. Yuri Deigin debate at Vitalist B...

comment: one thing is that parasites, diseases, germline mutations accumulate with age, fighting all of these is easiest by killing organism, that is in addition to increased evolvability. Also, the exceptions to the free radical theory of aging were explained away with the membrane pacemaker theory of aging, wherein membrane resilience determines rate of damage accumulation. Evolution determines membrane composition, during Calorie Restriction and similar interventions organism even alters membrane composition in a controlled manner increasing lifespan drastically.

In organisms like insects same genome different epigenetic regulation allows 10x--100x lifespan difference between queen and workers. But even here, it was believed queens of some species might be immortal, but for whatever reason it was found that sequential replacement with clones was easier for nature than actual immortality, the longest lasting queens last like 30 years ageless iirc, with extreme reproduction.

Poking holes in the AI doom argument — 83 stops where you could get off ...

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The issue is whether attaining godhood is possible. Even doom can be reversed.  Godhood means any and all goals trivially solved, god state is unique and convergent omniscience and perfect intelligence with all possible.  Now the idea is what happens in godstate, brain dead cause any orthogonal goal is solved?  Or the Luthor question suggestion takes place?(reference justice league animated series)

Why Different Neuron Parts Learn Differently?

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Ill give a comment regard this.  The apical section is said to have XOR functionality, iirc this means even context input will only activate during correct context, a mechanism may be needed to aid apical synapses gain an edge during darwinian synaptic competition given this.  Still even with this distinct mechanism it is likely coincident activity with neuron activation gives apical groups a further edge.

AI DEBATE: Runaway Superintelligence or Just a Normal Tool?

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Heres the thing fundamental assumptions are being taken into need for factories and permits, this assumes no radical superweapon can easily exist such as hard nano or reality warp.  Because if such are possible unregulated black op labs from govs will bypass any possible regulation.

Reaction to Predictive Coding: Biologically Plausible? Not So Fast!

Youtube comments in video regarding pattern completion, intelligence, brain function, and relation to prediction and function at neural and synaptic level:

"I will say in addition to the reverse signal issue, there is another issue with backpropagation.  That said some researchers have come with biological plausible implementations of backpropagation in recent years.  But the other issue I mention is that backpropagation learns too slowly.   Current ai experience millennia of training and still fail at basic tasks, despite the extreme slowness of the brain and scarcity of data the brain learns to perform even outside the bounds of training data within months or a few years.  It is said very gifted children can even know several languages musical instruments and decent math within a few years of birth.  Yet despite theoretically being able to do around 1000hz, neurons tend to operate well under 300hz, and vast majority of brain is usually silent from what i heard, there is sparse activation.

Regards Predictive coding, I agree with your assessment.  But I do believe that something similar is taking place through a Generative Adversarial Network (GAN) like turing learning mechanism via synaptic competition.   Synaptic competition is implemented via capture of proteins related to strengthening of synapses.   All the synapses that fire close to the time of neural activity, iirc, generate molecular tags that capture synapse strengthening proteins and all these synapses strengthen, while those that fail to do so weaken over time.    How does this cause a similar pattern completion comparison mechanism?  The input from sensory organs arrives in some synapses, while the signals from other neurons part of a larger pattern arrive at other synapses, normally given the sensory input is part of the larger pattern both signals match, but if there is noise there can be mismatch.  

But in essence it can be seen as surrounding pattern completing or trying to activate the neuron in case noise blocks sensory signal, thus a partial match appears complete.   This can be seen for example in language, when people speak, they sometimes omit small chunks of sentences unconsciously, but the receiver if they know the language never even becomes aware that the speech is missing tiny chunks, iirc.  It is also one of the things that makes learning a foreign language more difficult.

But if understood from gan turing learning perspective, surrounding neurons can be viewed as the counterfeit signals or fake signal generating networks trying to trick neuron whilst real sensory signals can be seen as the real thing.  And due to synaptic competition, the surrounding tissue gets better at faking, predicting, or completing the signal. (But what it does is merely connect the most related pattern detectors from nearby tissue to the neuron or pattern detector).    This is because the competition rewards successful completion or successful prediction at the synaptic level of the neuron."

Turing Learning Enables Machines to Learn Through Observation Alone

https://www.engineering.com/turing-learning-enables-machines-to-learn-through-observation-alone/

Select Comments on youtube video from another youtuber

 

Youtube Comments

"Regards intelligence it is simply the ability to recognize and complete patterns."

"what is a pattern? It is a structure in space or time whose composing elements relate to each other by rules or algorithmic processes. What is narrow vs general intelligence? Narrow can only handle a very narrow set of patterns, while general can handle a broad set of patterns. Superhuman performance is attainable at intellectual tasks such as arithmetic or chess, super intelligence is intelligence with superhuman performance at all intellectual tasks performable by humans and potentially at ones humans cannot perform."

For example a sequence is a pattern distributed in time, and prediction of a sequence is merely completion of the sequence or pattern completion.

Source video.