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Carlos E. Perez Profile picture
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27 Sep, 4 tweets, 1 min read
I don't know if there's a consensus of whether we have no idea how the brain works!
I think many people have failed to express what the brain does at Marr's computational level. You've got to begin with a hypothesis and then frame your evidence in support of the hypothesis. Anything less is stamp collecting.
What we know of the brain is what we know about butterflies if all we do is collect a lot of butterflies. This knowing is not the same as knowing how butterflies generate their wings.
As Feynman left in his blackboard before he died "What we cannot create, we do not understand."

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Carlos E. Perez Profile picture
27 Sep
In the context of general intelligence, there is no opposite to the notion of similarity. What we describe as dissimilar is also a kind of similarity.
That's because similarity hinges on a change of reference frame. It is what remains the same when a reference frame is changed.
Dissimilarity is what becomes different when some things remain the same. It's contextual and subordinate to the change in reference frames to determine similarity.
Read 6 tweets
Carlos E. Perez Profile picture
26 Sep
What is so frustrating about the FDA and CDC response to the pandemic is the lack of transparency of their decision-making process. If we are ever to evolve into a world of greater complexity, we need governance to be more transparent in their complex decision-making process.
What is preventing governance from creating a decision-making diagram that shows what information was available for every decision and the sequence of steps leading to the final decision?
As we become more dependent on automated decision-making algorithms, we cannot accept the state where decisions are in a black box and not explainable. If a car crashes without explanation, we should be able to review the decision process to discover the flaw.
Read 6 tweets
Carlos E. Perez Profile picture
23 Sep
Challenge: Describe in words why when you look in the mirror your left and right sides have flipped but not the top and bottom. But when you lie down horizontally, what side was on the bottom is now on the top. As if the top and bottoms have flipped.
This demonstrates that words can generate a paradox when there is none. Why is it that in one case the mirror flips horizontally and in another case, it flips vertically? How does the mirror know when and how to flip the image?
Words are instructions of imagination. It is like a magic trick when words distract you from the solution of the problem. Why does a mirror flip an image vertically or horizontally depending on a person's reference frame?
Read 17 tweets
Carlos E. Perez Profile picture
22 Sep
A key algorithm for general intelligence is a compensation mechanism for category error. This is because anything that learns must recognize that their habitual models of thought can be in error.
Planck remarked that science makes progress one funeral at a time. The problem with the human condition is that we are so devoted to the personal habits we invented for ourselves that we have difficulty letting them go.
Even more difficult, we embed in our language habits of thought. We are unable to break out of this jail because we cannot express new things with an old vocabulary.
Read 12 tweets
Carlos E. Perez Profile picture
22 Sep
The biggest effect of the global pandemic is that it disrupts how everyone frames their daily life. It breaks us out of our old habits and creates entirely new ones.
Modern humans are creatures of habit. At a very young age, we are introduced to routines that eventually become habitual. The most efficient of us learn the habits of success at a very early age. The rest of us just muddle our lives away.
The habits that we develop from childhood to the present are who we are. They are our own personal creations. This is why habits (which are all mental in nature) are something we have difficulty abandoning. They are what defines us.
Read 19 tweets
Carlos E. Perez Profile picture
21 Sep
SMH, seems like researchers don't know how to measure the generality of a large language model. Larger GPT-3 models are much better at discerning intent in zero-shot tasks. So I do find the paper described here as missing the target.
Generality implies greater creativity. Lying just happens to require creativity. I better measure would perhaps be a rewriting task. Smaller models don't have subspaces where rewriting even exists.
Another measure may be in joke generation. Larger models without a doubt come up with more unique jokes.
Read 4 tweets

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