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Artificial Intelligence & Robotics

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https://techcrunch.com/2019/08/19/the-five-technical-challenges-cerebras-overcame-in-building-the-first-trillion-transistor-chip/

Great name for a company and a big leap in finding processing power that is faster than the current connector standards. Curious what the tests in the lab were like but I am sure those will come out soon enough too.

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https://arstechnica.com/science/2019/09/paper-leaks-showing-a-quantum-computer-doing-something-a-supercomputer-cant/

We dont really have a section for Quantum computing not like we really need it so I figure I'd put in this section. What's interesting here is how they went about claiming Quantum Supremacy and the fact that they used observation to achieve it. Now, in the comments section someone has posted that someone at Caltech said its a great feat and he was the one that coined the term but I suppose until its solving practical problems and doing all this theoretical testing it really won't amount to much in the end. 

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15 minutes ago, Mel81x said:

https://arstechnica.com/science/2019/09/paper-leaks-showing-a-quantum-computer-doing-something-a-supercomputer-cant/

We dont really have a section for Quantum computing not like we really need it so I figure I'd put in this section. What's interesting here is how they went about claiming Quantum Supremacy and the fact that they used observation to achieve it. Now, in the comments section someone has posted that someone at Caltech said its a great feat and he was the one that coined the term but I suppose until its solving practical problems and doing all this theoretical testing it really won't amount to much in the end. 

The whole quantum mechanics and computing stuff flies well over my head really... What would be practical uses and applications of an actual working full-fledged quantum computer (bar cyber security)? If I understand it correctly, it's advantage mainly lies at solving very specific extremely high level mathematical problems and simulating extremely complex systems that would require infinite time  or would be fundamentally impossible on "regular"computers? 

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On 25/09/2019 at 20:36, nudge said:

The whole quantum mechanics and computing stuff flies well over my head really... What would be practical uses and applications of an actual working full-fledged quantum computer (bar cyber security)? If I understand it correctly, it's advantage mainly lies at solving very specific extremely high level mathematical problems and simulating extremely complex systems that would require infinite time  or would be fundamentally impossible on "regular"computers? 

I think that's the biggest issue surrounding quantum computing right now. Well two big problems, the first being that it has no real-world applications that trump the user of a super-computer which suffices for what it does right now and isn't really something you'd even want quantum computing for. The second being the fact that qubits are highly unstable and to maintain something or create something for observation seems like its only practical use right now. The bigger problem with quantum computing as a science as well is the fact that its all just theoretical and while we'd like to think that most things around us warrant complexity of that nature they really don't just because of how we perceive them to bring some kind of stoical measurement into place. 

Long story short, your i3, i5, i7, AMD variant would beat the shit out of a quantum processor if you tried to use it for daily tasks which is why its where it is, in theoretical science space. 

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https://arstechnica.com/gadgets/2019/10/fieldbit-is-bringing-augmented-reality-to-industrial-plants/

I like this. One of the projects I work on involves providing field engineers with AR schematics of motherboards and other devices in server centers so when I saw this it makes complete sense that they'd take some of that tech and go onto the industrial floor. The ability to tell if something is reaching critical mass or not functioning properly, with good tech, is something that isn't really light years away. We have the sensors, we have the AR and its high time someone put it to good use. But, as the article suggests, this does introduce the probability of a less skilled engineer being present to not be able to diagnose a problem properly. However, if you don't put it out into the world you'll never make it better. 

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Scientists used stem cells from frogs (and evolutionary algorithms in supercomputers) to build first living programmable machines. This is fascinating stuff.

https://www.popularmechanics.com/technology/robots/a30514544/xenobot-programmable-organism/

Also the link to the original paper for more details: https://www.pnas.org/content/early/2020/01/07/1910837117

 

@Mel81x you might be interested in this if you haven't read it yet!

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5 hours ago, nudge said:

Scientists used stem cells from frogs (and evolutionary algorithms in supercomputers) to build first living programmable machines. This is fascinating stuff.

https://www.popularmechanics.com/technology/robots/a30514544/xenobot-programmable-organism/

Also the link to the original paper for more details: https://www.pnas.org/content/early/2020/01/07/1910837117

 

@Mel81x you might be interested in this if you haven't read it yet!

And you send this in a 10 days span when I've just watched Carpenter's The Thing and then the prequel as well. Scary stuff, very scary stuff.

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This is heartbreaking. VR helps a mother get some closure after losing her young daughter to an illness. 

 

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https://www.technologyreview.com/s/615189/what-ai-still-cant-do/

A good read about one of the limitations of AI currently and what is being done to overcome it. Also there's an interesting takeaway there that the same limitation also applies to human minds and how it has been causing (hehe) problems in scientific research for ages. 

@Mel81x 

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1 hour ago, nudge said:

https://www.technologyreview.com/s/615189/what-ai-still-cant-do/

A good read about one of the limitations of AI currently and what is being done to overcome it. Also there's an interesting takeaway there that the same limitation also applies to human minds and how it has been causing (hehe) problems in scientific research for ages. 

Excellent article which can spawn myriads of questions into how data and its usage in scenarios ultimately leads to a deeper understanding (even if its skewed to fit a purpose). I remember reading a Nassim Nicholas Taleb book called "Antifragile" that deals with how disorder creates scenarios of importance in situations where you'd least expect them to. This of course was backed by math and then by numbers but you then have to ask yourself how good the AI is ever going to be if it doesn't truly have all the data it needs to make that math work. Just because an equation works doesn't necessarily mean its being applied correctly. This is where that genius bastard Yoshua in Montreal made some serious inroads. His paper on neural networks and how they can be used to further learning by simply introducing metas into formulas as a way of testing learning is astounding (i'd recommend a read if you like formal languages and automata theory but it turns into a dull affair if you don't grasp that concept as hes not the kind of person who likes to do things which can be understood by people who dont have their fundamentals right). 

All said and done this is a part of AI that goes beyond what we think Machine Learning is going to be useful for. Just because a machine can churn out data based on what its given to produce results is still looking at the problem as a box versus a universe. I also think that statement about this being the last hurdle is ridiculous and the kind of thing you'd expect from someone at MIT or Columbia just because they themselves are victims of causality and trying to put it in a box with a limitation that math can solve when the reality is that there are way too many variables in play to truly say it will work without seeing everything (and that imo isn't happening for the next 100 years or maybe more just because of how much society and our living and understanding changes every day)

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1 hour ago, nudge said:

https://www.technologyreview.com/s/615434/ai-machine-learning-social-outcome-prediction-study/

@Mel81x not surprising but an interesting read nevertheless. Bad news for Rehoboam 😉

"Three sociologists at Princeton University asked hundreds of researchers to predict six life outcomes for children, parents, and households using nearly 13,000 data points on over 4,000 families."

If they think that's enough data they are sadly mistaken. Also, Rehoboam would have looked at the problem and said "thats okay i'll just change society to suit my needs" haha.

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Posted (edited)

@nudge figured you might find this interesting from the Director AI and how it works.

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21 minutes ago, Mel81x said:

@nudge figured you might find this interesting from the Director AI and how it works.

Fascinating. The idea of an omniscient director AI is very cool.  I also love how the Alien unlocks its behaviour trees based on the player's behaviourial patterns and then adjusts its own actions accordingly. Very neat.

Also I would poop my pants if I had to play it xD 

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Posted (edited)
23 minutes ago, nudge said:

Fascinating. The idea of an omniscient director AI is very cool.  I also love how the Alien unlocks its behaviour trees based on the player's behaviourial patterns and then adjusts its own actions accordingly. Very neat.

Also I would poop my pants if I had to play it xD 

I played it and loved it. I highly recommend it to anyone to either watch or play. It's in the upper echelons of survival-gaming imo. The way that thing shows up out of nowhere to make you run and hide is unreal.

I am trying to find the RE2:REMAKE cut video on how Mr. X teleports and goes searching for you as well. That's a bit more straightforward but what Capcom did to make him chase you through rooms is just unreal. Shame they didnt' bring it to the more recent RE3:REMAKE.

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Didn't know where else to put it, but this is quite an interesting little guide on how to read and analyse DNA on a computer using Python. https://biospace.xyz/posts/reading-dna-on-computers/

On a similar topic, I recently discovered Rosalind, a platform to learn bioinformatics, algorithms and programming through problem solving. Quite fun. http://rosalind.info/

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4 minutes ago, nudge said:

It is interesting but I don't know how much I buy into the casual linkage of data even if you use quantum computing to treat the data as conversations versus you know, actual data. The idea then that a chat-bot can actually diagnose (and with accuracy) symptoms and then offer a remedy course is definitely something worth looking into but I still think so much data is missing even in that sector as is pointed out when peer-reviews applauded the concept but said it could also go horribly wrong. 

What I do like about all this is how far we've come in analyzing data and more importantly how inflection points are gathered from information sources that are totally dissonant from each other. Used to be you'd be asked to create data repositories and they needed linkage but these days you dont even need that.

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https://techcrunch.com/2020/07/03/we-need-a-new-field-of-ai-to-combat-racial-bias/

@nudge and @Eco this is a good read for you'll as I know both of you'll are working with Python and learning data/security. If you're interested in reading the NIST publication its very good as well.

https://www.nist.gov/news-events/news/2019/12/nist-study-evaluates-effects-race-age-sex-face-recognition-software

Additionally, take a look at this and how algorithms started discriminating against women when they started running. 

https://slate.com/business/2018/10/amazon-artificial-intelligence-hiring-discrimination-women.html

I know this is probably not the place to post this but its all AI based and I suppose we can all take a learning away that the wrong data handling will eventually lead to some pretty undesirable results.

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Thanks for the links @Mel81x, will properly read it after all the racing today. 

I remember reading Karen Hao's interactive feature on MIT Technology Review that was related to the topic a while ago, there they had a predictive algorithm called COMPAS, which is used as a risk assessment tool in US courtrooms to decide whether the defendant should be released from jail before their trial or not. The feature had you tweak the algorithm based on certain scenarios to make it "fairer", in order to demonstrate the issues with it and the biases involved; that was an interesting experiment. 

https://www.technologyreview.com/2019/10/17/75285/ai-fairer-than-judge-criminal-risk-assessment-algorithm/

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1 hour ago, nudge said:

Thanks for the links @Mel81x, will properly read it after all the racing today. 

I remember reading Karen Hao's interactive feature on MIT Technology Review that was related to the topic a while ago, there they had a predictive algorithm called COMPAS, which is used as a risk assessment tool in US courtrooms to decide whether the defendant should be released from jail before their trial or not. The feature had you tweak the algorithm based on certain scenarios to make it "fairer", in order to demonstrate the issues with it and the biases involved; that was an interesting experiment. 

https://www.technologyreview.com/2019/10/17/75285/ai-fairer-than-judge-criminal-risk-assessment-algorithm/

I dont know how much I trust an algorithm that isn't given all the data it needs to make decisions like the one presented by Karen (sorry I spent 20 seconds laughing at the name and its connotation with what we're reading but moving on). The problem with the algorithm and its premise is that the system used for judging doesn't account for other factors like how the defendants got to the crime, were they in groups, etc and that is also a consideration for how the release/jailing system works. When it comes to the other issue of credit scores thats a far more clearer one. Someone who can't maintain the basic income for recovery over a period shouldn't be allowed credit but there also there aren't enough inflection points in the data to help make the decision. They account for things like inflation and market rates but the algorithms are mostly aligned towards risk avoidance rather than credit assignment so that might be a failure we need to consider.

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On 04/07/2020 at 08:13, Mel81x said:

https://techcrunch.com/2020/07/03/we-need-a-new-field-of-ai-to-combat-racial-bias/

@nudge and @Eco this is a good read for you'll as I know both of you'll are working with Python and learning data/security. If you're interested in reading the NIST publication its very good as well.

https://www.nist.gov/news-events/news/2019/12/nist-study-evaluates-effects-race-age-sex-face-recognition-software

Additionally, take a look at this and how algorithms started discriminating against women when they started running. 

https://slate.com/business/2018/10/amazon-artificial-intelligence-hiring-discrimination-women.html

I know this is probably not the place to post this but its all AI based and I suppose we can all take a learning away that the wrong data handling will eventually lead to some pretty undesirable results.

That was a good read. So in essence, what has been happening so far in many cases is that the AI didn't remove the bias, but rather automated it :4_joy:  

On a more serious note, when it comes to facial recognition, it seems like a combination of the quality (or lack thereof) of algorithm training data and physical properties of the universe. I think it's safe to assume that facial recognition is likely to be more accurate on people with lighter skin tones, because more reflected light means more data allowing the software to make a match more accurately, whereas it is more error-prone on people with darker skin? 

Also regarding Amazon, it's not surprising their recruitment AI tool turned out to be crap. I mean, even their regular internal search algorithm is fucking horrible when you are trying to find some product on their website! :4_joy:

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Posted (edited)

I was not sure if this belongs in here as I was tossing up putting it into Science & Environment forum which the BBC link I got it from classed it as the latter or post this in the space forum as NASA was mentioned so feel free @Eco to move it into the appropriate forum if you must.  :ay:

Quote.thumb.png.4f9accb0c91704ee33bf844a4160e6e7.png

Science & Environment

Robotic scientists will 'speed up discovery'

Scientists at the University of Liverpool have unveiled a robotic colleague that has been working non-stop in their lab throughout lockdown.

The £100,000 programmable researcher learns from its results to refine its experiments.

"It can work autonomously, so I can run experiments from home," explained Benjamin Burger, one of the developers.

Such technology could make scientific discovery "a thousand times faster", scientists say.

A new report by the Royal Society of Chemistry lays out a "post-Covid national research strategy", using robotics, artificial intelligence and advanced computing as part of a suite of technologies that "must be urgently embraced" to help socially distancing scientists continue their search for solutions to global challenges.

Robo-chemist

a.thumb.png.8c12fdf779a41d256fb995d1d14cfca6.png

The robotic scientist is currently embarking on a series of tests to find a catalyst that could speed up the reaction that takes place inside solar cells.

But it could, according to Prof Andy Cooper, the materials scientist who has put the robot to work in his lab, be used in the fight against Covid-19.

"We've had a lot of interest [in the robot] from labs that are doing Covid research," he told BBC News.

"Covid, climate change - there are lots of problems that really need international co-operation. So our vision is we might have robots like this all across the world connected by a centralised brain which can be anywhere. We haven't done that yet - this is the first example - but that's absolutely what we'd like to do."

Socially distant science

Today, in a world where scientists also need to limit their time in the lab and maintain social distance from each other, the robo-scientist has come into its own.

"It doesn't get bored, doesn't get tired, works around the clock and doesn't need holidays," Dr Burger joked.

On a more serious note, he said that the robot had transformed the speed at which he could carry out research. "It can easily go through thousands of samples," he said, "so it frees up my time to focus on innovation and new solutions."

Like robotics designed for research in Space, machines like this could also take on riskier experiments - in harsher laboratory environments or using more toxic substances.

That, according to Deirdre Black, head of research and innovation at the Royal Society of Chemistry, is why UK science needs to build new technologies into its infrastructure.

"This is about human beings harnessing all of these digital technologies so that they can go faster - discover and innovate faster and explore bigger and more complex problems, like decarbonisation, preventing and treating disease, and making our air cleaner," she told BBC News.

So does this mean that while many scientists have been in lockdown, the machines have come to take their jobs?

"Absolutely not," said Dr Black. "Science will always need people".

https://www.bbc.co.uk/news/science-environment-53029854

 

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On 06/07/2020 at 02:23, nudge said:

That was a good read. So in essence, what has been happening so far in many cases is that the AI didn't remove the bias, but rather automated it :4_joy:  

On a more serious note, when it comes to facial recognition, it seems like a combination of the quality (or lack thereof) of algorithm training data and physical properties of the universe. I think it's safe to assume that facial recognition is likely to be more accurate on people with lighter skin tones, because more reflected light means more data allowing the software to make a match more accurately, whereas it is more error-prone on people with darker skin? 

Also regarding Amazon, it's not surprising their recruitment AI tool turned out to be crap. I mean, even their regular internal search algorithm is fucking horrible when you are trying to find some product on their website! :4_joy:

I think the AI pushed the bias narrative because it figured it offered the most balancing. Hard to believe they didn't let it try and learn more to adapt to the way feedback may have corrected it? I mean if people can offer feedback to it then maybe it gets better which is the whole point of an AI anyways. 

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Thought this was quite an interesting read about the key impediments to building machines that understand meaning, what meaning would look like for artificial intelligence, and how far understanding is necessary for artificially intelligent machines to approach human-level abilities in language, perception, and reasoning. Nothing ground breaking, but a nice if somewhat philosophical discourse.

https://bdtechtalks.com/2020/07/13/ai-barrier-meaning-understanding/

@Mel81x @Eco

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@Mel81x, what are your thoughts on GPT-3? I spent a good chunk of my weekend exploring the available samples of its capabilities, and must say I find it very impressive for what it is... The bloody thing can write workable code, do machine translation, answer questions, one-shot learn novel words, write passable poetry, folk tales, generate news articles and pretty much anything else, in a much, much better, more human-like quality than its predecessor - which is of course not surprising, given the vast amount on data it was trained on (half a trillion words) and the number of parameters used that's even hard to comprehend (175 billion!!!), but nevertheless, the results are mind blowing; especially its ability to meta-learn, generalise to other tasks with barely any or none finetuning and solve tasks it has never encountered. One area where it impresses me in particular is the AI Dungeon "Dragon" model upgrade; the level of coherence in the world, story and dynamic characters generated by the GPT-3 are nothing short of amazing...

 

Also this is some next level Westworld inspired shite:

EdFmiTIUMAE2Shz?format=png&name=4096x409

I'm getting serious Dolores vibes here... Have you ever seen anything so full of splendor? xD 

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9 hours ago, nudge said:

@Mel81x, what are your thoughts on GPT-3? I spent a good chunk of my weekend exploring the available samples of its capabilities, and must say I find it very impressive for what it is... The bloody thing can write workable code, do machine translation, answer questions, one-shot learn novel words, write passable poetry, folk tales, generate news articles and pretty much anything else, in a much, much better, more human-like quality than its predecessor - which is of course not surprising, given the vast amount on data it was trained on (half a trillion words) and the number of parameters used that's even hard to comprehend (175 billion!!!), but nevertheless, the results are mind blowing; especially its ability to meta-learn, generalise to other tasks with barely any or none finetuning and solve tasks it has never encountered. One area where it impresses me in particular is the AI Dungeon "Dragon" model upgrade; the level of coherence in the world, story and dynamic characters generated by the GPT-3 are nothing short of amazing...

 

Also this is some next level Westworld inspired shite:

EdFmiTIUMAE2Shz?format=png&name=4096x409

I'm getting serious Dolores vibes here... Have you ever seen anything so full of splendor? xD 

I get HAL vibes from it and I also get the feeling it thinks I am in its way and would put me in a box and suffocate me till it finds a more subservient entity to do its bidding haha.

Putting all that aside I think its wonderful what the folks at OpenAI are achieving and more importantly the parts where it is able to do machine language translations on its own with some time and not so complex issues. The demos were very simple and the big push for NLP style questions but its working to a certain degree and it will only get better. As developers we may be out of work pretty soon if this keeps up but I figure the market has been shifting for years now and we're at a stage where you really can build something on the internet with no knowledge of computer languages or the platform you're building it on (some website builders do this today anyways). The next logical step here isn't pondering our existence but telling it jokes and seeing how it comprehends them in the context of the joke being told and then we should be both worried and very excited.

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Quote.thumb.png.e0c1adc12b5ee4661abc91ee9c1ce945.png

GettyImages_1187502812-c-a429b4f.jpg?web

Could the internet become conscious?

An old belief system called ‘panpsychism’ suggests that something resembling a mind or consciousness exists in all physical things. In recent years, researchers such as neuroscientist Christof Koch have tried to update these ideas, saying that if there are enough connections between elements – like synapses in the brain – then consciousness may naturally start to form.

The average human brain has 86 billion neurons, with some 100 trillion connections between them – does this mean that if something else has the same number of connections, it will also become conscious? Some believe so.

Like our brains, the internet is a massively connected entity, made up of computers, mobile devices and the ‘Internet of Things’ (IoT) – smart, networked objects including household appliances, wearable gadgets, vehicles and even entire factories. According to one estimate, the number of internet-connected devices will reach 125 billion worldwide by 2030. So the connectivity of the internet seems to be fast approaching that of our brain.

But how would we know if the internet had become conscious? An internet that’s as connected as the brain might process information as quickly as we do, but that doesn’t mean it’s going to ‘wake up’ or become self-aware. There are big differences between the two systems: our sense of consciousness is created by brains that have evolved over millions of years, whereas the internet is a human-designed network that’s been around for a few decades.

Ultimately, consciousness is still such a poorly understood subject that we won’t have a definitive answer to your question until we figure out how to measure consciousness in the first place.

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