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FOUNDER LIFE

Nell Watson's Founder Life Book

The Psychological Journey of Accomplishing Hard Things.

Founder Life explores the psychology and philosophy of entrepreneurship. Learn techniques to help find meaning behind the madness of this thrilling and terrifying rollercoaster ride. Gain self-mastery at the most trying of times, with tips on how to keep your hair on – without losing your shirt.

It examines the internal and external forces that lead a certain percentage of the population to choose entrepreneurial activities, whereas others are content to live in comfort, but without taking personal command of their industry.

The target audience is mostly young entrepreneurs, or people who might consider choosing to take an entrepreneurial lifestyle as a vehicle for personal and societal improvement.

The book provides an analysis of the special role of a founder/entrepreneur in our society and discusses the drives and attitudes that influence entrepreneurs as they work their vocational craft to fight for – and achieve – what seems impossible.

 

STATUS:

Final Draft complete. Under ongoing review, editing, and polishing in preparation for release in 2022.

 

CourseBOOKS

Understanding Convolutional Neural Networks (O'Reilly Media)

Convolutional neural networks (CNNs) enable very powerful deep learning based techniques for processing, generating, and sensemaking of visual information.  This course offers an in-depth examination of CNNs, their fundamental processes, their applications, and their role in visualization and image enhancement. 

  • Discover the connections between CNNs and the biological principles of vision

  • Understand the advantages and trade-offs of various CNN architectures

  • Survey the history and evolution of CNN's on-going development

  • Learn to apply the latest GAN, style transfer, and semantic segmentation techniques

  • Explore CNN applications, visualization, and image enhancement


book Contributions



Patents (Granted, active)

A method of generating three dimensional body data of a subject is described. The method includes capturing one or more images of the subject using a digital imaging device and generating three dimensional body data of the subject based on the one or more images.

These core technologies, built on machine learning and deep learning techniques, enabled the Poikos/QuantaCorp body measurement platform, which I co-founded.


PROVISIONAL PATENTS

  • US63/107,144

We construct a Restricted Boltzmann Machine using the principle of maximum entropy and Shannon entropy as the cost function in the optimization problem. We demonstrate that the problem of optimization of entropy in RBM can be described as the Inverse Ising problem and that the optimal values of coefficients for the RBM are identical to the parameters in the Hamiltonian of the Ising model. We also show that real physical variables, such as magnetization and susceptibility, obtained using our RBM are in good correspondence to results from analytical or numerical methods.

These results suggest that RBM neural networks using the principle of maximum entropy can be applied to modeling physical systems which can be described by discrete states, including fundamental quantum physics such as topological systems, and biological systems such as the correlated spiking of neurons.

An original quantum machine learning technology which can be applied to optimizing a wide number of physical, biological, and artificial intelligence systems, as well as modelling complex interactions between them.


Editor roles