Tagged: Technology

Biomimicry & Algorithms

What is programming and what are algorithms? Can we foster an interest in them for anyone who finds programming to be a black box? Can biomimicry help? These are the questions I’m playing around with these days. Can reference to nature take courses in logical thinking beyond typical lessons in sequences, If/Else statements and loops? . I watched The Secret Rules Of Modern Living: Algorithms(trailer) and The Code (trailer) on Netflix over the weekend, still have to finish the code, and I kept thinking ‘wow this is brilliant! I can do this!’ I also got to know about an online course on Teaching Physical Computing with Raspberry Pi through my sponsor TIES and going through it has been very interesting (Raspberry Pi is a mini, cheap computer, not a literal raspberry pie :D, inside joke!),. It led me to Scratch which helps young people learn programming.

Next, I have been thinking; Do I want to teach programming or algorithm development. The answer seems to be easy, because a way to keep someone engaged is to have results and programming is what gives algorithms an outcome. Yet, algorithms can be developed without any computer, while programs need to be written on a computer of some sort in a language (considering analog here as well). Also, it seems to me creating a lesson is different than what I want to do, which is produce a software/piece of a machine. For example, a biomimicry lesson could be similar to an exercise on learning about birds and nesting to come up with the algorithm they use. Instead of an abstract lesson, I want to deliver something students can touch and use hopefully without much outside help. That is not to say, my deliverable cannot involve students going out and experiencing nature while working on/with my product. However, my product needs to be a software and/or a hardware that is attractive, engaging by using nature’s life lessons to teach programming/algorithms to the user.

I can see how nature is brilliant for my task; it has millions of algorithms to teach and we have been learning them for quite a while in the computer science world. My goal is to bring those lessons  to the general public. At the end of The Secret Rules Of Modern Living: Algorithms movie, narrator Marcus du Sautoy mentions how our world wouldn’t function without the power of algorithms and I think that’s absolutely true! As we rely on them greatly, how can we increase everyone’s interest in them?

http://unanimous.ai/watch-50-people-think-as-one/

Human Swarm

This blog is based on this paper: “Crowds vs Swarms, a Comparison of Intelligence” by Louis Rosenberg, David Baltaxe, and Niccolo Pescetelli.

Recently, I went for a conference organized by Daniel Palmer and Marc Kirschenbaum of John Carroll University on Blended Intelligence. I thought it appropriate to talk about one of the talks. How do we get intelligence from a crowd of people, surveys, interviews? How does nature get intelligence from its beings? Authors claim nature does not aggregate independent samples but works on a closed real-time loop with continuous feedback. Hence, can we have a human swarm similar to a flock of birds or a school of fish and does it result in better intelligence? That is exactly what the authors put to test with their software UNU. UNU works by having a group of knowledgable individuals about a specific topic to come together virtually and decided on an answer for a given question. Each user has a magnet which he/she can use to pull the puck toward their desired answer.

What of the results? Check this article on how it predicted the Kentucky Derby, or read their paper on its prediction for the 2016 Super Bowl; a human swarm of 20 people outperformed (68% correctly) a crowd of 469 football fans (47% correctly). If this doesn’t impress you, well the swarm outperformed 98% of independent individuals in the study. Now, could this be a reason to pool our intelligence in order to tackle more challenging questions facing us in the future? Could this help in finding solutions to climate change that is affecting us more every day.

Do you want to try it? All you need is to sign up, verify your email, and you’ll be in your way to create you first UNU human swarm, or you can just enter one of their open UNUs. Finally check out their tutorial: https://youtu.be/TkAoRUHs5F0

 

Brains, Brains, Brains…

“If the brain were so simple we could understand it, we would be so simple we couldn’t.” Lyall Watson

Summer time! For me it means working on bio-inspired algorithms, one in particular I’ve been spending some time on is Artificial Neural Networking (ANN). This had me asking my sister (who is working on her PhD in neuroscience) about how synapses, pathways, etc. work. This post will be on how ANN was inspired and some of the materials I found interesting on it. Let’s start with the obsession with neural network and why it matters? Machines do complicated mathematical calculations in a matter of seconds, yet they have difficulty performing some easy tasks such as recognizing faces, understanding and speaking in local languages, passing theTurning test. OK, let’s compare machines to our brain: A single transistor in your home computer is quite fast; only limited by speed of light and the physical distance to propagate a signal. A signal(Ions) in the neuron, on the other hand, propagates on a fraction of the speed (Flake, 1999). This begs the question, which is better? A good comparison can be found here. One main fact is that our brain makes use of a massive parallelism; it’s this massive interaction between axons and dendrites that contribute to how our brain works. Many argue that the comparison to computers is not very useful as they work differently from each other. Can we make a digital reconstruction of human brain? I follow Blue Brain project for this. Hence, as you can guess ANN algorithm is a simple imitation of how our neurons work. It works by feed forward and back propagations to learn patterns. Originally proposed as McCulloch-Putts neuron in the 1940s and 1980s by invention of Hopfield-Tank feedback neuron network. The 1960s had an good optimistic start on neural networks with the work of Frank Rosenblatt’s perceptron (a pattern classification device). However, by 1969 there was a decline in this research and publication of Perceptrons by Marvin Minsky and Seymour Papert caused it to almost die off. Minsky and Papert showed how a single perceptron was insufficient with any learning algorithm by giving it mathematical proofs. It took a while and many independent works till the value of Neural Networking came to light again. One main contribution is the two-volume book titled Parallel Distributed Processing by James L. McClelland and David E. Rumelhart and their collaborators. In this work, they changed the proposed unit step function proposed to a smooth sigmoid function and added a backward error signal propagation using weights of some hidden neurons called back propagation (Flake, 1999). Reading through chapter 20 of Parallel Distributed Processing written by F. Crick and C. Asanuma, I read about physiology and anatomy of the cerebral cortex. It shows different neural profiles.

Screen Shot 2016-07-24 at 11.35.30 AM(McClelland, 1989)

It talks about different layers in the cortex such as the superficial, upper, middle, and deep layer, axons, synapses, neurotransmitters. The more I read, the more I come to appreciate the complexity of our brain and wonder about the simplicity of Artificial Neural Network algorithms, and can’t help but feel amazed by what Blue Brain Project is aiming to do.

Like a house-cat exploring its environment, lets dive into narrow unexplored places…

Books:

Flake, G. W. The computational beauty of nature, 1999

McClelland, J. L. Rumelhart, D. E. Parallel distributed processing, Volume 2. Psychological and biological models, 1989

Biomimicry Within Digital Arts and Technology

Biomimicry is a tool/discipline that can be used in many fields ranging from industrial design, architecture, engineering, math, and even computer science. Being from a graphic design background and practicing digital painting, I find myself struggling to find exactly where biomimicry fits within the digital aesthetics realm. Can a designer/artist practice digital arts in a biomimetic way, or are the digital arts just a good tool to perform and carry out biomimetic thinking within a digital space? Surely when you are 3D modeling a biomimetic building or product on your computer, you are aiding in the biomimetic design process, but the 3D modeling process itself isn’t the thing that is biomimetic, is it? Biomimicry, in root words terms, is the act of mimicking life. How literally should we take this? Is virtual reality a sort of biomimicry because it does just that; mimics life? Maybe it’s just a useful tool to aid in the design process. These are some of the things I hope to figure out in my studies, but I’m finding as I dig deeper that when approaching biomimicry with a digital aesthetics lens, that it’s not just about the design process and appearance, but also about how using digital tools can help learn or experience something in the natural world. It is possible that, like art, digital aesthetics is particularly useful to inspire, evoke emotions, and increase understanding using the natural world as a muse. Continue reading

Abstracting and Adapting

Hello Readers,

Thank you for continuing to follow us, the biomimicry fellows, as we continue to probe the depths of nature’s solution manual in search of sustainability. I find it a little ironic that I had the privilege to kick off the school year and now I will be closing out the first semester for the new biomimicry fellows. Over the last fifteen weeks we have been endeavoring to discover more about this thing we call biomimicry. I’d like to take a second to share a few of my thoughts that have been shaped this semester. Continue reading