Visual art & randomness, music composed by AI, Astrology and DS

Hello there

This will be an interesting meetup bringing algorithmic visual art, music using MAX, an interesting high level analysis of astrological aspects, and more original classical and techno music produced by the musicquant python library (proprietary).

If time allows, we will also feature a cello/violin player interpreting a composition 100% created by a proprietary AI that is composing classical music.

The event will be streamed live, via this link (http://livestream.com/LivestreamPublic/algorithmicartcompositionmeetup).

Also, please help us by filling out the form here (http://bit.ly/1ILofKI), to better learn about the audience and plan future meetups.

Thank you.

These are the speakers:

Nikki Mehle: Random systems and visual arts

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Nikki is a painter from Youngstown, Ohio currently pursuing her Master of Fine Arts degree at Hunter College. Her work is an exploration of possibilities and the idea of infinity, expressed through the systematic and algorithmic combinations of geometric forms and patterns.

The geometric structure of patterns act as a modified grid, inside which basic aleatoric systems (such as dice rolling) are used to determine certain formal features, for instance the colors and orientation of shapes. Using aleatoric systems produces the visual effect of rhythm and pattern, without an exact repetition. This kind of rhythm and structure can be seen in nature on both micro and macro scales.

Her presentation will include an overview of her work as well as a brief history of algorithmic painting and her influences.

Nikki is starting to explore the use of Python (SciPy) in collaboration with the Quadrivium meetup organizer, to expand the range of possibilities in algorithmic visual art by using normal, weibull, and other statistical distributions in addition to simple uniform distributions.

Mick Sussman: The Rosenberg algorithm for automated music generation

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Mick is the creator of The Rosenberg Algorithm, a Max-MSP program that automatically generates music based on a compositional method he devised. The algorithm makes hundreds of musical choices based on a set of random processes that trigger compositional variables and synthesizer settings, and then create loops of melodic and percussive phrases that evolve over time.

Mick is a journalist by profession, a news editor at The New York Times, but music has been his lifelong passion. He played in a high school rock band and studied classical piano, and while attending Oberlin College took music history and theory courses at the school’s conservatory.

With his eclectic taste in music, he became interested in rhythmic intricacy, mesmeric loops, random processes and microtonal scales. Wanting to experiment with these ideas, in the early 2000s he began making electronic music. He developed a laborious method of splicing samples into evolving phrases. Last year, he decided to automate and elaborate on his compositional method using Max. The algorithm has steadily grown in complexity over the months, and it has churned out about 10 hours of music, which you can check out here (https://soundcloud.com/sussmm).

At the Meetup, The Rosenberg Algorithm will create new music, and Mick will give a demonstration of how it works and talk about the musical and technological issues it raises.

Rebecca Gordon: Interesting findings in astrology using exploratory data analysis

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Rebecca is a life-time astrologer, author, and founder of the My Path Astrology (http://www.mypathastrology.com/rebecca-gordon/) School in New York. She has practiced astrology for the last fifteen years while hosting international retreats, local year round classes and weekend workshops in New York. Rebecca's mentors in astrology have been her mother Marjean Gordon and the world renowned Susan Miller of astrologyzone.com.

Rebecca is very tech savvy, a data geek at heart, and she will show an interesting preliminary research done with python code and large datasets of people by profession pulled from Wikipedia. Correlation? Causation? Let's find out.

Luis M. Sanchez: AI for music composition

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Luis M. is a former Wall Street Quant, with backgrounds in engineering, programming, and finance and who specialized in Monte Carlo simulations, bayesian statistics and time-series analysis applied to financial models in the credit space for hedge funds and investment banks.

Luis will show an update to his last presentation at the meetup group: Machine learning code that is the basis of an artificial intelligence that is creating original songs in many styles including classical, jazz, and even techno. If time allows, a human performer will interpret a couple of solos for cello, which were entirely composed by machine code.

Luis was recently featured among a group of elite Data Scientists interviewed for The Data Science Handbook (http://www.thedatasciencehandbook.com/), a must have book for aspiring Data Scientists.

Here (http://apple.co/1I7SAO1) you can listen to one of Luis 'machine learning' techno songs in Apple's iTunes radio. You can find a classical piece here (http://bit.ly/18PTqVU), and for his financial related work, you can Google "PyData and Bonds" or search Google Scholar.