Open thread, Apr. 03 - Apr. 09, 2017

Final version of thesis going out within 4 days. Getting back into a semi-regular schedule after PhD defense, death in the family, and convergence of job-search on a likely candidate in quick succession. Astrobiology writing likely to restart soon. Possible topics include:

• schools of thought in life origins research
• the nature of LUCA
• recent work on the evolution of potentiated smart animal lineages on Earth
• WTF are eukaryotes anyway
• the fallacies of the Fermi paradox/ 'great filter' concepts
• the fallacies of SETI as it is currently performed

I'm thinking on writing a post on doing 'lazy altruism', meaning 'something having a somewhat lasting effect that costs the actor only a small inconvenience, and is not specifically calculated to do the most amount of good - only the most amount per this exact effort."

Not sure I'm not too lazy to expand on it, though.

Tyler Cowen and Ezra Klein discuss things. Notably:

Ezra Klein: The rationality community.

Tyler Cowen: Well, tell me a little more what you mean. You mean Eliezer Yudkowsky?

Ezra Klein: Yeah, I mean Less Wrong, Slate Star Codex. Julia Galef, Robin Hanson. Sometimes Bryan Caplan is grouped in here. The community of people who are frontloading ideas like signaling, cognitive biases, etc.

Tyler Cowen: Well, I enjoy all those sources, and I read them. That’s obviously a kind of endorsement. But I would approve of them much more if they called themselves the irrationality community. Because it is just another kind of religion. A different set of ethoses. And there’s nothing wrong with that, but the notion that this is, like, the true, objective vantage point I find highly objectionable. And that pops up in some of those people more than others. But I think it needs to be realized it’s an extremely culturally specific way of viewing the world, and that’s one of the main things travel can teach you.

Our article about using nuclear submarines as refuges in case of a global catastrophe has been accepted for the Futures journal and its preprint is available online.

Abstract

Recently many methods for reducing the risk of human extinction have been suggested, including building refuges underground and in space. Here we will discuss the perspective of using military nuclear submarines or their derivatives to ensure the survival of a small portion of humanity who will be able to rebuild human civilization after a large catastrophe. We will show that it is a very cost-effective way to build refuges, and viable solutions exist for various budgets and timeframes. Nuclear submarines are surface independent, and could provide energy, oxygen, fresh water and perhaps even food for their inhabitants for years. They are able to withstand close nuclear explosions and radiation. They are able to maintain isolation from biological attacks and most known weapons. They already exist and need only small adaptation to be used as refuges. But building refuges is only “Plan B” of existential risk preparation; it is better to eliminate such risks than try to survive them.

Full text: http://www.sciencedirect.com/science/article/pii/S0016328716303494?np=y&npKey=6dcc6d35057e4c51bfd8d6933ab62c6d4a1604b5b71a40f060eb49dc7f42c9a1

Curious about if this is worth making into it's own weekly thread. Curious as to what's being worked on, in personal life, work life or just "cool stuff". I would like people to share, after all we happen to have similar fields of interest and similar fields we are trying to tackle.

Projects sub-thread:

• What are you working on this week (a few words or a serious breakdown)(if you have a list feel free to dump it here)?
• What do you want to be asked about next week? What do you expect to have done by then?
• Have you noticed anything odd or puzzling to share with us?
• Are you looking for someone with experience in a specific field to save you some search time?
• What would you describe are your biggest bottlenecks?

"Modafinil-Induced Changes in Functional Connectivity in the Cortex and Cerebellum of Healthy Elderly Subjects"

http://journal.frontiersin.org/article/10.3389/fnagi.2017.00085/full

"CEDs may also help to maintain optimal brain functioning or compensate for subtle and or subclinical deficits associated with brain aging or early-stage dementia."

"In the modafinil group, in the post-drug period, we found an increase of centrality that occurred bilaterally in the BA17, thereby suggesting an increase of the FC of the visual cortex with other brain regions due to drug action." FC analysis revealed connectivity increase within the cerebellar Crus I, Crus II areas, and VIIIa lobule, the right inferior frontal sulcus (IFS), and the left middle frontal gyrus (MFG)."

"These frontal areas are known to modulate attention levels and some core processes associated with executive functions, and, specifically, inhibitory control and working memory (WM). These functions depend on each other and co-activate frontal areas along with the posterior visual cortex to re-orient attention toward visual stimuli and also enhance cognitive efficiency.

Data on behavioral effects of modafinil administration in our study group are missing and, at this stage, we can only provide theoretical speculations for the functional correlates of the regional activations that we have found to be promoted by the drug."

I'm still mulling over the whole "rationalism as a religion". I've come to the conclusion that there are indeed two axioms that are shared by the rational-sphere that we-cannot-quite-prove, and whose variations produce different cultures.
I call them underlying reality and people are perfect.
"Underlying reality" (U): refers to the existence of a stratum of reality that is independent from our senses and our thoughts, whose configurations gives the notion of truth as correspondence.
"People are perfect" (P): instead refers to the truth of mental ideation that people might have, whether they are (or there's a subset that is) always right.
Here's a rough scheme:
U, P: religion. Our feelings reflect directly the inspiration of a higher source of truth.
U, not P: rationalism. We are imperfect hardware in a vast and mostly unknowable world.
not U, P: the most uncertain category. Perhaps magic? There's no fixed, underlying truth but our thoughts can influnce it.
not U, not P: postmodernism. Nothing is true and everything's debatable.

I might make this a little more precise in a proper post.

In "Strong AI Isn't Here Yet", Sarah Constantin writes that she believes AGI will require another major conceptual breakthrough in our understanding before it can be built, and it will not simply be scaled up or improved versions of the deep learning algorithms that already exist.

To argue this, she makes the case that current deep learning algorithms have no way to learn "concepts" and only operate on "percepts." She says:

I suspect that, similarly, we’d have to have understanding of how concepts work on an algorithmic level in order to train conceptual learning.

However, I feel that her argument was lacking in terms of tangible evidence for the claim that deep-learning algorithms do not learn any high-level concepts. It seems to be based on the observation that we currently do not know how to explicitly represent concepts in mathematical or algorithmic terms. But I think if we are to take this as a belief, we should try to predict how the world would look differently if deep-learning algorithms could learn concepts entirely on their own, without us understanding how.

So what kind of problems, if solved by neural networks, would surprise us if this belief was held? Well, to name a couple of experiments that surprise me, I would probably point out DCGAN and InfoGAN. In the former, they are able to extract visual "concepts" out of the generator network by taking the latent vectors of all the examples that share one kind of attribute of their choosing (in the paper they take "smiling" / "not smiling" and "glasses" / "no glasses") and averaging them. Then they are able to construct new images by doing vector arithmetic in the latent space using this vector and passing them through the generator, so you can take a picture of someone without glasses and add glasses to them without altering the rest of their face, for example. In the second paper, their network learns a secondary latent variable vector that extracts disentagled features from the data. Most surprisingly, their network seems to learn such concepts as "rotation" (among other things) from a data set of 2D faces, even though there is no way to express the concept of three dimensions in this network or have that encoded as prior knowledge somehow.

Just this morning in fact, OpenAI revealed that they had done a very large scale deep-learning experiment using multiplicative LSTMs on Amazon review data. What was more surprising than just the fact they had beaten the benchmark accuracy on sentiment analysis, was that they had done it in an unsupervised manner by using the LSTMs to predict the next character in a given sequence of characters. They discovered that a single neuron in the hidden layer of this LSTM seemed to extract the overall sentiment of the review, and was somehow using this knowledge to get better at predicting the sequence. I would find this very surprising if I believed it were unlikely or impossible for neural networks to extract high-level "concepts" out of data without explicitly encoding it into the network structure or the data.

What I'm getting at here is that we should be able to set benchmarks on certain well-defined problems and say "Any AI that solves this problem has done concept learning and does concept-level reasoning", and update based on what types of algorithms solve those problems. And when that list of problems gets smaller and smaller, we really need to watch out to see if we have redefined the meaning of "concept" or drawn to the tautological conclusion that the problem really didn't require concept level reasoning after all. I feel like that has already happened to a certain degree.

Problem to solve:

https://protokol2020.wordpress.com/2017/04/02/another-intermezzo-intermezzo-problem/

I have an idea about how to make rationality great again (bad joke, but I'm serious). The term "theoretical rationality" may be coined by me - idk, but the new meanings to "theoretical and applied rationality" are mine and include 1)optimisation 2)fast completion of goals and ideals 3)updating the list of desirable goals and ideals 4) repeat. Any comments?

Is there a place in the existential risk community for a respected body/group to evaluate peoples ideas and put them on a danger scale? Or dangerous given assumptions.

If this body could give normal machine learning a stamp of safety then people might not have to worry about death threats etc?

In some situations my thinking becomes much more structured, I throw out the syntax and the remaining words come in very clear hierarchy and kind of seem to echo shortly. It lasts, perhaps, less than a second.

Examples: "snake - nonvenomous (snake, snake) - dead, where's the head, somebody struck it with something, probably a stick, curse them, ought to collect it, where's vodka"; "snake - viper (viper, viper) - back off, where's camera, damn, it's gone, ought to GPS the place"; "orchid - Epipactis (...pactis) - why not something rarer, again this weed".

Has it been like that for you?

I'm wondering what people would think about adopting the term Future Super Intelligences or FSI, rather than AGI or SAGI.

This would cover more scenarios (e.g. uploads/radical augments) where the motivational systems of super powerful actors may not be what we are used to. It would also show that we are less worried about current tech than talking about AIs does, there is that moment when you have to explain you are not worried about backprop.

Are there any studies that determine whether regular coffein consumption has a net benefit? Or does the body produce enough additional receptors to counteract it?

Normal "introducing myself", normal I am of faith.