Group items tagged

Big data analytic systems are reputed to be capable of finding a needle in a universe of haystacks without having to know what a needle looks like. The very best ways to sort large databases of unstructured text is to use a technique called Latent Dirichlet allocation (LDA). Unfortunately, LDA is also inaccurate enough at some tasks that the results of any topic model created with it are essentially meaningless, according to Luis Amaral, a physicist whose specialty is the mathematical analysis of complex systems and networks in the real world and one of the senior researchers on the multidisciplinary team from Northwestern University that wrote the paper. Even for an easy case, big data analysis is proving to be far more complicated than many of the companies selling analysis software want people to believe.

Most of those companies are using outdated algorithms like this LDA and just apply them like retards on those huge datasets. Of course they're going to come out with bad solutions. No amount of data can make up for bad algorithms.

The first complete theory of how plasmons produce "hot carriers" has been developed by researchers in the US. The new model could help make this process of producing carriers more efficient, which would be good news for enhancing solar-energy conversion in photovoltaic devices.

I did not read the paper but what is further down written in the article, does not give much hope that this actually gives much more insight than what we had nor that it could be used in any way to improve current PV cells soon: e.g. "To fully exploit these carriers for such applications, researchers need to understand the physical processes behind plasmon-induced hot-carrier generation. Nordlander's team has now developed a simple model that describes how plasmons produce hot carriers in spherical silver nanoparticles and nanoshells. The model describes the conduction electrons in the metal as free particles and then analyses how plasmons excite hot carriers using Fermi's golden rule - a way to calculate how a quantum system transitions from one state into another following a perturbation. The model allows the researchers to calculate how many hot carriers are produced as a function of the light frequency used to excite the metal, as well as the rate at which they are produced. The spectral profile obtained is, to all intents and purposes, the "plasmonic spectrum" of the material. Particle size and hot-carrier lifetimes "Our analyses reveal that particle size and hot-carrier lifetimes are central for determining both the production rate and the energies of the hot carriers," says Nordlander. "Larger particles and shorter lifetimes produce more carriers with lower energies and smaller particles produce fewer carriers, but with higher energies."

Nature paper showing a new photo-bioelectrochemical cell with a new photon-driven biocatalytic fuel cell method achieving electrical power generation from solar energy.

do you have the pdf?

This is the biggest breakthrough in game AI (and one of the biggest in AI in general) since Deep Blue beat Kasparov in chess: For the first time, a human professional player was defeated in the game of Go. The approach was a combination of tree search and deep neural networks. Very proud of a former colleague on the team at Google Deepmind!

Funny enough, facebook also had a very similar paper around the same time.

Simulating the economic state of the Galaxy after the resistance has blown up the Death Stars. See the paper here: http://arxiv.org/pdf/1511.09054.pdf

Love this type of friday afternoon research questions. There is also a now famous scene in the movie Clerks discussing the loss of independent contractors lives as the Death Star was being build.. https://www.youtube.com/watch?v=iQdDRrcAOjA

That analysis is quite crappy and is easily demolished in the video's comments.

Research in active-matter systems is a growing field in biology. It consists in using theoretical statistical physics in living systems such as molecule colonies to deduce macroscopic properties. The aim and hope is to understand how cells divide, take shape and move on these systems. Being a crossing field between physics and biology "The pot of gold is at the interface but you have to push both fields to their limits." one can read

Maybe we should discuss about this active matter one of these days? "These are the hallmarks of systems that physicists call active matter, which have become a major subject of research in the past few years. Examples abound in the natural world - among them the leaderless but coherent flocking of birds and the flowing, structure-forming cytoskeletons of cells. They are increasingly being made in the laboratory: investigators have synthesized active matter using both biological building blocks such as microtubules, and synthetic components including micrometre-scale, light-sensitive plastic 'swimmers' that form structures when someone turns on a lamp. Production of peer-reviewed papers with 'active matter' in the title or abstract has increased from less than 10 per year a decade ago to almost 70 last year, and several international workshops have been held on the topic in the past year."

I posted the same thing on 23/02/2016, with arxiv version of the paper instead.

uhhhh, Jai got scooped on Diigo :D

since double posted, maybe double interesting and we should have a closer look? anybody?

Paper: https://arxiv.org/abs/1806.02404

After a series of rapid developments, the researchers claim their fluid can now hold 250 watt-hours of energy per kilogram, which is double the the energy capacity of Tesla's Powerwall batteries, according to the NBC.

Interesting research. Bit hyped in the article though. The actual paper says the promising stuff is in the 83-160Wh range. So maybe not double Tesla's Powerwall batteries?

What happens if you strap NSGA-II to optimize the usage of your abstract data structures?

How many people to we actually need put on that ship?

We should invite these people to the AF special issue

sounds really interesting. their simulations don't account for biological issues (mutation, migration, selection, drift, founder effect) though, so the numbers are very low. this paper (https://ac.els-cdn.com/S0094576513004669/1-s2.0-S0094576513004669-main.pdf?_tid=6bec2a5c-f05f-4024-b4de-af78ab06fd42&acdnat=1531827379_d4f0be1b193873890d6e5b4574e82f2e) takes those effects and their implications on genetic composition of populations into account, but the numbers are enormous. do you have an idea why they (marin and beluffi) wouldn't put those effects into the simulations?

It is an old one, but it was mentioned in some discussion ... Mainly based on this paper https://arxiv.org/abs/astro-ph/0102126

The Sun's gradual brightening will seriously compromise the Earth's biosphere within ~ 1E9 years. If Earth's orbit migrates outward, however, the biosphere could remain intact over the entire main-sequence lifetime of the Sun. In this paper, we explore the feasibility of engineering such a migration over a long time period. (via Nina)

"Over the past couple of decades, the research literature has filled up with endless new nature-based metaphors for algorithms. You can find algorithms based on the behaviour of cuckoos, bees, bats, cats, wolves, galaxy formation and black holes. (...) All researchers have been doing is wasting time on developing new approaches that are probably little better than existing ones. And the language of each metaphor then invades the literature, distracting people from using the already sufficiently expressive terminology of mathematics and, above all, working together to find the best way forward." The golden era of fireworks-like algorithm is about to end

Lies, lies, all lies. They will never go away. Papers need to be published.

"By extension, GCMs are not fit for the purpose of justifying political policies to fundamentally alter world social, economic and energy systems. It is this application of climate model results that fuels the vociferousness of the debate surrounding climate models."

but you know wo these global warming policy foundation is, do you? they are the main advocacy group for climate change deniers in the UK, nothing scientific to start with; fine to post here reasonable scientific papers criticising global climate models but please not this shit

Prediction-based method for encouraging reinforcement learning agents to explore their environments through curiosity (reward for unfamiliar states). Learns some games without any extrinsic reward!

Fun failure case: agent gets stuck in front of TV.

Not read this article but on a related note: Curiosity and various metrics for it have been explored for some time in robotics (outside of RL) as a framework for exploring (partially) unfamiliar environments. I came across some papers on this topic applied to UAVs when prep'ing for a PhD app. This one (http://www.cim.mcgill.ca/~yogesh/publications/crv2014.pdf) comes to mind - which used a topic modelling approach.

This has attracted a lot of attention in the DL community lately. Article: https://lilianweng.github.io/lil-log/2017/09/28/anatomize-deep-learning-with-information-theory.html Paper: https://arxiv.org/pdf/1703.00810.pdf

Genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning. For paper see: https://arxiv.org/pdf/1712.06567.pdf

Interesting pointers in this one! I would like to explore neuroevolution as well, although it seems extremely resource-demanding?

Not necessarily, I think it can be made to be much faster hybridizing it with backprop and Taylor maps. Its one ideas in the closet we still have not explored (Differential Intelligence: accelerating neuroevolution).

"Just as Pierre de Fermat scribbled his famous last theorem in the margins, professional scientists, academics and citizen scientists can annotate equations, figures and ideas and also write in the margins." Interesting way of analyzing research in the 21st century

The Nature paper this article is reviewing (behind their paywall) https://www.nature.com/articles/s41563-018-0075-8