Advanced Concepts Team

Like it! Can you do an initial assessment on space applications Jojo?

anybody wanna try? surprising to me

not for space but the air breathing battery still is a nice concept - would make robots more "human" if they have to breath :-)

"Neuroscience UCLA neurophysicists have found that space-mapping neurons in the brain react differently to virtual reality than they do to real-world environments. Their findings could be significant for people who use virtual reality for gaming, military, commercial, scientific or other purposes." I wonder if we are doing it wrong with the airplane pilot simulators...

Another Appathon with the aim to allow access to vast amounts of 'space data' and then play around.. In other words, a neural network's guy wet dream, so Paul, what are you waiting for?

I'm not really an app developer :P But I'll think about it

pretty impressive stuff!

LSTMs: that was also the first thing in the paper that caught my attention! :) I hadn't seen them in the wild in years... My oversight most likely. The paper seems to be getting ~100 citations a year. Someone's using them.

There are a few papers on them. Though you have to be lucky to get them to work. The backprop is horrendous.

Awarded videos of fluid motion presented at the APS DVD meeting. Very cool stuff. #0084 is done with the setup I used for my master thesis.

New technology demonstration of laser communication link to offer high-speed near real time delivery of data from space... Oh, that's us... :)

Let an AI build up your web page for just 96$ per year!

Amazing! Not even coding jobs are safe from AI anymore! AI programming will be the last bastion in the struggle against automation. Get ready :)

Let an AI develop your magic tricks! (The one with the smart phone is actually neat)

They published it in Frontiers of Psychology...?

Quantum Computing and Machine Learning in the same sentence. The association started to be put forward by Google and NASA playing with D-WAVE computers. Meanwhile in the academic media, https://journals.aps.org/prx/pdf/10.1103/PhysRevX.4.031002

With the aid of short infrared laser pulses, researchers have succeeded for the first time in making a ceramic superconducting at room temperature - albeit for only a few millionths of a microsecond.

where real power sits ...

love this one ... it seems to take physicist to explain to the AI crowd what they are actually doing ... Deep learning is a broad set of techniques that uses multiple layers of representation to automatically learn relevant features directly from structured data. Recently, such techniques have yielded record-breaking results on a diverse set of difficult machine learning tasks in computer vision, speech recognition, and natural language processing. Despite the enormous success of deep learning, relatively little is understood theoretically about why these techniques are so successful at feature learning and compression. Here, we show that deep learning is intimately related to one of the most important and successful techniques in theoretical physics, the renormalization group (RG). RG is an iterative coarse-graining scheme that allows for the extraction of relevant features (i.e. operators) as a physical system is examined at different length scales. We construct an exact mapping from the variational renormalization group, first introduced by Kadanoff, and deep learning architectures based on Restricted Boltzmann Machines (RBMs). We illustrate these ideas using the nearest-neighbor Ising Model in one and two-dimensions. Our results suggests that deep learning algorithms may be employing a generalized RG-like scheme to learn relevant features from data.

I'm sure Leo will love it. Yet another argument not to have a facebook account or a smartphone.

Ditched? I never had either! But then on the other hand a recent Dilbert summarised me pretty well...

so you also don't have a mobile phone? I thought I knew only one person of my age who does not have one yet ... congratulations

In essence, the idea involves building a skeleton structure, wrapping it with elastic materials and then start filling it with concrete. A technique first tried in the 60's but now evaluated again with renewed interest as low-cost option for housing.

sort of reminds me of this thing: https://www.youtube.com/watch?v=Vb1pdvvoVoQ

In the space industry, concurrent design is frequently implemented as requirements are frequently not set but developed along the design process. In many cases this is due to the interconnection between (sub)systems. In the industry however, this is hardly done, but it is becoming more relevant as lead times and innovation speed needs to increase. There is a webinar tomorrow 10 december from Agile on this topic regarding the semiconductor industry

missed it ... did anybody attend?

Other possible study: get a textbook example of an image of a pen, evolve it just enough so NN can't recognize it anymore, while minimizing the distance between the original and evolved images. EDIT: Its been done already: http://cs.nyu.edu/~zaremba/docs/understanding.pdf

Of course, you can't really use them to extrapolate. The unknown unknown is always the trickiest :P They should just make another class "random bullshit", really and dump all of this stuff in there. I think there's a potential paper right there

"Over the past few months, the European Space Agency's Rosetta space probe closely examined the type of comet that some scientists theorized could have brought water to our planet 4 billion years ago. It found water, but the wrong kind."