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To: Frank Sully who wrote (109400)	2/27/2022 8:09:47 PM
From: Frank Sully	Respond to of 110581

Re: Introduction FWIW, I got hit by the fifteen minute post editing SI limit again so didn’t get the machine learning videos embedded in time. Here is that section of my post with embedded videos Deep Learning Modern AI is based on Deep Learning algorithms. Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. Deep Learning Algorithms for AI The first one-hour video explains how this works. Amazingly, it is just least squares minimization of the neural network loss function using multi-dimensional Newton Raphson (gradient descent). See second one half hour video. Who thought Calculus would come in handy? 1. MIT Introduction to Deep Learning 2. Gradient Descent, Step-by-Step Math Issues: Optimizing With Multiple Peaks Or Valleys A problem with gradient descent optimization is that it can find minima of functions as well as maxima of functions. Worse, there can be multiple peaks and valleys, so more properly gradient descent finds local extrema. One is interested in machine learning, e.g., in global minima. This makes the problem considerably more difficult. This is particularly true since loss functions for deep learning neural networks can have millions or even billions of parameters. Another problem has to do with the size of the data sets used to train deep learning neural networks, which can be huge. Since gradient descent is an iterative process, it becomes prohibitively time-consuming to evaluate the loss function at each and every data point, even with high-performance AI chips. This leads to stochastic gradient descent: the loss function is evaluated at a relatively small random sample of the data at each iterative step. 3. Stochastic Gradient Descent: Any comments/discussion? Slainte! (Irish for “Cheers!”) Frank “Sully”

To: Frank Sully who wrote (109400)	2/27/2022 8:21:08 PM
From: Frank Sully	1 Recommendation Recommended By Mister D Read Replies (1) \| Respond to of 110581

Re: Introduction (Continued) Unfortunately, I realized that that darned fifteen minute SI post editing limit ended up deleting another embedded video. Here is the complete affected section: Back to the NVIDIA introduction Header, I also included substantial discussion of NVIDIA’s Deep neural network AI models for autonomous driving and their current and upcoming implementations, e.g.: Ride in NVIDIA's Self-Driving Car ( seven and a half minute video) CEO Jensen Huang recently said in an interview: <<< VB: What is your confidence level in the automotive division and how we are moving forward with self-driving cars? Do you feel like we are getting back on track after the pandemic? Huang: I am certain that we will have autonomous vehicles all over the world. They all have their operating domains. And some of that is just within the boundaries of a very large warehouse. They call them AMRs, autonomous moving robots. You could have them inside walled factories, and so they could be moving goods and inventory around. You could be delivering goods across the last mile, like Neuro and others. All these great companies that are doing last-mile delivery. All of those applications are very doable, so long as you don’t over promise. And I think there will be thousands an thousands of applications of autonomous vehicles, and it’s a sure thing. This year is going to be the inflection year for us on autonomous driving. This will be a big year for us. And then next year, it’ll be even bigger next year. And in 2025, that’s when we deploy our own for software where we do revenue sharing with the car companies. And so if the license was $10,000, we shared 50-50. If it’s a subscription base of $1,000 or $100 a month, we share 50-50. I think I’m pretty certain now that autonomous vehicles will be one of our largest businesses. >>> Comments/discussion? Slainte! (Irish for “Cheers!”) Frank “Sully”