Resources to Learn Generative AI
The most important thing that you can do, if you are an AI professional, is to get deeper into generative AI.
We urge you to consider our course, Top Ten Terms in Statistical Mechanics, because it is all that – and so much more. To enroll, go to the Academy page, and use the links there to go to the Themesis Thinkific website.
But … if you’re trying to put together your own generative AI curriculum, based on YouTubes, tech posts and classic papers, we offer you some resources:
Book
The book-in-progress, Statistical Mechanics, Neural Networks, and Artificial Intelligence, has useful chapters giving you essential background on statistical mechanics. Statistical mechanics is an important element in generative AI. It’s also the hardest for most people to learn.
These chapters, and the Précis, are the easiest-to-read chapters in the world. The equations are kept to the bare minimum, and are expressed as simply as possible. Lots of figures, lots of explanatory text.
You can access the Précis and select chapters from the book HERE.
Career
If you are career-changing, we offer you this set of Career Resources. It’s a series of web pages; one leads to the next to the next. Each page gives you a specific guidance-step.
Over time, we may develop this into a career-transition short course. For now, please visit Career Resources.
We also give you the best coaching that we can offer on the Themesis, Inc. YouTube channel, on the AI Career Ronin playlist.
Writing
We’ve summarized some key points – this is the first of what we intend to be a content-series (and potential short course) on Writing.
Ages upon ages ago, we did a full series of YouTubes on writing your professional-style paper. These were published on the Alianna J. Maren YouTube channel.
Here’s the “Writing an Effective Research Paper” playlist:
Publications – Journal
- Maren, A.J. (2021). The 2-D Cluster Variation Method: Topography Illustrations and Their Enthalpy Parameter Correlations. Entropy, 23 (3), 319. doi:10.3390/e23030319. Available online at: https://doi.org/10.3390/e23030319. (Accessed Nov. 30, 2021.) Full text.
- Maren, A.J. (2016) The Cluster Variation Method: A Primer for Neuroscientists. Brain Sciences, 6(4), 44. doi:10.3390/brainsci6040044 pdf
Publications – arXiv/White Paper
- Maren, A.J. (2019). Derivation of the variational Bayes equations. THM TR2019-001v4 (ajm). arXiv:1906.08804v4 [cs.NE] 30 Jul 2019. abstract; pdf.
- Maren, A.J. (2019). Free energy minimization using the 2-D cluster variation method: Initial code verification and validation. THM TR2018-001v2(ajm), arXiv:1801.08113v2 [cs.NE] 25 Jun 2019. abstract; pdf.
YouTube Channel
The Themesis YouTube channel:
https://www.youtube.com/channel/UCludJusDnoVeQMx1IHwjdbg
GitHub
Themesis GitHub: https://github.com/Themesis1