Explained: The conspiracy to make AI seem harder than it is! By Gustav Söderström

2023 may be a year that people still speak about 100 years from now, the year computers passed the Turing test! You know what these things can do, but do you actually understand how they can do it? How is it that we have services like Chat GPT that can write entire novels, and services like Stable Diffusion and Midjourney that can create amazing images or even music from just a text description or even white noise?

Straight from the halls of Spotify, this is an academic/educational talk from an internal executive offsite that we’re sharing with the world. The premise of this talk is that AI is made to seem harder to understand than it actually is, and that after this presentation, you will feel like you understand how all of what’s now happening is possible - even if you don't work in tech and you don’t know a lot of math.

00:00:00 — Intro
00:04:01 — What is an LLM?
00:20:09 — What about creativity?
00:24:00 — How do you steer it?
00:34:26 — Why did no one see it coming?
00:39:00 — Everything is a vector!
00:57:44 — What is a neural network?
01:05:53 — Intelligence is compression!
01:15:12 — Diffusion Models - Generating images, video, and music
01:21:10 — Conditioning on text

Sources used to build the talk:

• www.mdpi.com/2076-3417/11/21/10267
• openai.com/blog/chatgpt?ref=assemblyai.com
• blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/
• www.researchgate.net/figure/Perceptron-neuron-with-three-input-variables-with-a-single-output-0-or-1-The-inputs-are_fig1_338989845
• www.researchgate.net/figure/Schema-of-Autoencoder-architecture_fig1_338995559
• www.this-person-does-not-exist.com/en
• developer.nvidia.com/blog/improving-diffusion-models-as-an-alternative-to-gans-part-1/

There are great resources available, for anyone interested in digging deeper.