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Prometheus last won the day on February 22

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    Building statistical models for Raman spectroscopy.

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  1. If he was accessing other 'processes' then he was not dealing with Lamda. If he has been giving information out about Google's inner workings I'm not surprised he had to leave, I'm sure he violated many agreements he made when signing up with them. But given what he believed about the AI, he did the right thing. I don't know anything more about him than that.
  2. It's not an analogous situation for (at least) 2 reasons. Someone without any senses other than auditory are still not only 'trained' on words, as words only form part of our auditory experience. Nor does Lambda have any auditory inputs, including words. The text is fed into the model as tokens (not quite the same as words, but close). The human brain/body is a system known, in the most intimate sense, to produce consciousness. Hence, we are readily willing to extend the notion of consciousness to other people, notwithstanding edge cases such as brain-stem death. I suspect a human brought up truly only on a single sensory type would not develop far past birth (remembering the 5 senses model was put forward by Aristotle and far under-estimates the true number).
  3. If you skip the click bait videos and go to the actual publication (currently available in pre-print) you'll see exactly what lamda has been trained on: 1.56 trillion words. Just text, 90% of it English. Level 17 and level 32.
  4. The entire universe exposed to LaMDA is text. Is doesn't even have pictures to associate to those words, and has no sensory inputs . By claiming LaMDA, or any similar language model, has consciousness, is to claim that language alone is a sufficient condition for consciousness. Investigating the truth of that implicit claim gives us another avenue to explore.
  5. LaMDA is a language model designed for customer interaction. The google employee was a prompt engineer tasked with fine-tuning the model to be suitable for these interactions, because out of the box and unguided it could drift towards anything in its training corpus (i.g. it could favour language seen in erotica novels, which may not be what google want - depending on exactly what they're selling). Part of its training corpus would have included sci-fi books, some of which would include our imagined interactions with AI. It seems the engineer steered the AI towards these tendencies by asking leading questions.
  6. Dunno, but the PI of that nature paper is very active on twitter: he came up with the idea and would probably answer your question.
  7. Assembly theory posits that complex molecules found in large abundance are (almost surely) universal biosignatures. From their publication: https://www.nature.com/articles/s41467-021-23258-x At the moment it only has proof of concept with mass spectrometry, but it's a general theory of complexity so could work with other forms of spectroscopy. Interesting direction anyway.
  8. It was unknown whether the plants would germinate at all - the fact they did tells us that regolith did not interfere with the hormones necessary for this process. The plant they chose was the first one to have its genome sequenced, allowing them to look into the transcriptome to identify epigenetic changes due to the regolith, particularly what stress responses were triggered. They also compared regolith from 3 different lunar sites, allowing them to identify differences in morphology, transcriptomes etc between sites. Full paper here: https://www.nature.com/articles/s42003-022-03334-8
  9. Sounds like you're describing panpsychism. There's a philosopher called Philip Goff who articulates this view quite well.
  10. Some people have tried to develop methods of measuring consciousness in the most general sense. I think the most developed idea is integrated information theory put forward by a neurologist in 2004. It measures how integrated various systems in a whole are. Even if you accept this as a reasonable measure, to actually apply the test all possible combinations of connectivity are sought, so to 'measure' the consciousness of a worm with 300 synapses would currently take 10^9 years.
  11. So a matter of complexity? Fair enough. Thanks for answering so clearly - i ask this question a lot, not just here, and rarely get such a clear answer. Not any closer? There are some in the community who believe that current DNNs will be enough - it's just a matter of having a large enough network and suitable training regime. Yann Lecun is probably the most famous, the guy who invented CNNs. Then there are many who believe that symbolic representations need to be engineered directly into AI systems. Gary Marcus is probably the biggest advocate for this. Here's a 2 hour debate between them: There are a number of neuroscientists using AI as a model of the brain. There are some interesting papers that argue what some networks are doing is at least correlated with certain visual centres of the brain - this interview with a neuroscientist details some of that research - around 30 mins in, although the whole interview might be of interest to you: An interesting decision by Tesla was to use vision only based inputs - as opposed to competitors who use multi-modal inputs and combine visual with lidar and other data. Tesla did this because their series of networks were getting confused as the data streams sometimes gave apparently contradictory inputs - analogous to when humans get dizzy when their inner tells them one thing about motion and the eyes another thing. Things like that make me believe that current architecture are capturing some facets of whatever is going on in the brain, even if its still missing alot, so i think they do bring us closer.
  12. If you're going to ask someone to guess when fusion is going be reality, you'd still give more credence to engineers and physicists guess than some random people on the internet wouldn't you?
  13. This survey of researchers in the field gives a 50% chance of human level intelligence in ~40 years ago. It's probably the most robust estimate we're going to get.
  14. That'll explain why i didn't follow then.
  15. Not sure i follow with the DNA. We could still regard it as searching a solution space on geological timescales, optimising for replicability, What gives DNA its model - surely it is only shaped by natural selection? DNNs is a bit general, CNNs couldn't be a reinforcement agent could. All it needs is to be motivated in some sense to explore the input space and have some metric of its impact on the solution space. 1.) We have Generative Adversarial Networks where two or more networks cooperatively compete to improve some process, usually classification. There are aslo agents whose learning is nearly entirely with other AI - muzero was trained to play chess and other games by playing the existing best chess AI. 2.) There's a few ways AI currently learn, one way is supervised learning which requires a human to label some data - pointing to a picture and saying cat (maybe 3000 times but its the same idea). 3.) There are genetic algorithms, but i don't think that's what you mean. I don't see what, in principle, will stop us designing a robot able to build, perhaps imperfect, replicas of itself. Once it can, it is subject to evolution. Whether that's a desirable feature is another question. But here we're concerned with what a computer can and can't do, it doesn't necessarily need to replicate the functions of a human brain, just the behaviours. I'm interested, many people here seem to believe that there is nothing immaterial to the brain, no ghost in the machine, but still maintain that something other than a biological entity cannot be conscious . It seems to imply that substrate matters, that only biological substrates can manifest consciousness. If i'm interpreting that correctly, what is unique to the arrangement of atoms that manifest in the human that prevents it manifesting in other, inorganic, arrangements?
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