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Tong Family

Podcast

OK, if you aren’t using Apple Podcast, Spotify or any of the others, you can listen to all my podcasts in this view. Just click on the latest at the top. Or if you want to listen to any of the previous podcasts, there’s a link for each below. Have fun! This is using the JetPack big version player with all the subscribe buttons and showing the latest Podcast.

Youtube Channel

Here is the video cast from the Video Podcast channel (thanks to a special Smash Balloon, YouTube Feed plugin which you can embed with a shortcode

Rich Tong

The Excellent Adventures of Tong with co-hosts Paul and Deon. Covering current tech news and analysis. As well as regular updates on all things Apple, Smart Home, Smart Everyday Carry, Hime Theater, Linux, Startups, Robotics and Artificial Intelligence

Rich Tong
Alex Tong's Thesis the last half excerpt
Alex Tong's Thesis Defense Excerpt - Screen Recording 2021 08 25 at 12 34 44 PM
This is another sort of nerdy side note. If anyone is still watching, this section is just to give intuition on the basics of the hardware. There are lots of assumptions about GPUs and CPUs that I wanted to make sure people understood. But the basics are that CPUs are tuned for lots of branches and different workflows, while GPUs are tuned for lots of the same things like matric math. And because they are so fast, most of the job of the computer folks is "feeding the beast". That is caching the most frequently used information so they don't have to wait. There are some errors I think in the levels of the CPU and GPU performance particularly in the cache performance as it is not very clear how this works and the results of course vary depending on the models of processors, so these are all approximations. Put in comments better sources. I have all the sources listed in a spreadsheet that is part of this. We are happy to send this to anyone who wants the source data. I'll fix these errors in later editions (as I'm obsessive that way). Also, I'm quite proud of the HDR mix, using the latest OBS settings, producing in HDR in Final Cut Pro, and adjusting the video scope levels helps. The audio is a little hot and I'm sorry about that, I'll turn it down next time, I stoo much time in the red. My Scarlett needs to about 1 O'clock and it works. See https://tongfamily.com/2024/03/08/pod-rt3-ai-hardware-introduction/ for details and https://podcasters.spotify.com/pod/show/richt/episodes/RT3--AI-Hardware-Introduction-e2gr9ad for the podcast version Chapters: 00:00 AI Hardware Introduction 00:42 Computer Engineering in Two Slides 05:40 It's 165 Years to a Disk Access?!! 14:12 Intel Architecture CPU 17:03 What's all this about NVidia 25:24 And now for something completely Different, Apple 29:45 Introduction summary 2024-03 -08. Shot as UHD HEVC HDR PQ 10 bit using OBS Studio and Final Cut Pro © 2024. Iron Snow Technologies, LLC . All Rights Reserved.
RT3. AI Hardware Introduction
OK, we are not experts nor PhDs so most of this is probably not technically correct, but the math is so complicated and the concepts so complicated, that we thought it would be good to just get some intuition on what is happening. So this is a quick talk that summarizes readings from so many different sources about the history of AI from the 1950s all the way to January 2024 or so. It is really hard to keep up but much harder without some intuition about what is happening. We cover expert systems, the emergence of neural networks, Convolution Neural Networks, and Recurrent Neural Networks. The Attention is All You Need paper led to Transformers and then finally some intuition on how such a simple idea, that is training on things can lead to emergent and unexpected behaviors, and finally, some intuition on how Generative images work. Also I apology is that there is a lot of brushing over, over the section on embeddings is not quite right, particularly for visual transformers, we will correct that, but the concept of embeddings is still important there, just not quite correctly explained. Sorry! Chapters: 00:00 AI History 09:07 Neural Networks Weights 11:18 Convolutional Neural Networks (CNNs) 16:07 Recurrent Neural Networks (RNNs) 17:57 Embedding Vectors are the key! 23:25 Attention is all you need Transformers 27:36 But it's too Simple! Emergence is surprising 33:04 What emerges inside a Transformer? 43:01 One Model to Rule Them All 47:54 Works for Image generation too
DT6. AI Intro and Intuitions 2024-03-07
Ok, you heard it from us first, this is a summary of all the many things that happened in the AI moment of 2023. It's a huge list, but we go through 8 diamonds that are in the blizzard of Artificial Intelligence and machine learning work that has happened, plus some predictions for the future! Of course, all of these are random opinions for entertainment only. It's not like either of us knows the future or has any deep information, but surfing the Internet makes it easy to learn what others are thinking. And some errata and apologies. Sorry, it was too much to go in and Reddit this, so what you hear is what you get. But, 1. Of course we know that Andrej Karpathy's name isn't literally "St. Andrew", but having just spent a holiday in Scotland (what a place), it seemed like a small inside joke for us. Apologies Mr. Karpathy, please keep the insight coming. 2. There are some terminology and "slang" I didn't get quite right. whats, one abbreviation we had was a vLLM for a Visual LLM (mainly because it doesn't fit on the slide). But to be clear (and apologies to the vLLM team), is an LLM inference and service that uses PagedAttention (hence the v is for virtual not visual) and focuses on which keys and values to store in the attention buffer, we update the slides to say viLLM to distinguish, but not here. https://blog.vllm.ai/2023/06/20/vllm.html Chapters: 00:00 - Introduction 01:13 - In a Nutshell: 8 Diamonds 05:59 - Diamond 1: LLM as an OS 14:52 - D2: It's raining LLMs! 34:21 - D3: LLM Refinements 1:08:13 - D4: Training Magic Show 1:24:59 - D5: Programming LLMs 1:31:28 - D6: Hardware Advances 1:35:09 - D7: Safety, safety, safety 1:36:39 - D8: Customers and Industry
DT5. Eight AI Diamonds, big insights from last year and 2024 predictions (2024-02-15)
Yes that's right after a five-month hiatus where I've been busy figuring out all things AI and a bunch of new startup ideas, this Christmas break, I'm finally back at it, so here is a quick tour of the new setup. I think the sound is much nicer and also I'm getting a handle on SDR to HDR conversion, so if you are on YouTube, you should see things in their full 4K HDR glory. And if you are audio only, you can check it out on Spotify or right here on the page and it should also be up on Apple and other places.
RT5. Testing, testing, 1, 2, 3. 2024-01-01
Happy Birthday France! And a quick catchup on podcasting, the audio level seems better, there is less "breathing" but there is some clipping of the sound, so not all the way tuned. I also hear clicking as it comes in and out, this could be related to the Shure microphone to the Sony camera to the Elgato S60+ Show notes at https://tongfamily.com/2023/07/14/pt6-ai-geeks-and-happy-birthday-france/
PT6. AI Geeks and a new Camera. 2023-07-14
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