Presentation I gave at the Dagster Community Meeting on the 21st of September, 2021 on how to use Dagster for machine learning purposes, with an explanation on why we chose that instead of Airflow.
Google's NotebookLM is making the rounds on the internet (at least in my bubble). It's a new AI tool that Google pitches as a "personalized research assistant" but has evolved to be much more than that, including... a podcast generator.
Moved by my curiosity on everything AI related, I decided to give it a try by creating a LoRa adapter on the FLUX.1 model by Black Forest Labs to generate pictures of myself that never happened.
On Monday, June 10, 2024 at their annual World Wide Developer Conference (WWDC) Apple announced "Apple Intelligence", their own flavour of AI integration into their operating systems.
Emphasis should probably go into integration, as the experience that was demoed at WWDC felt like every feature we are used to on our devices was augmented in a way or another by AI. AI is also able to orchestrate those features and use multiple apps and functionalities to achieve what the user wanted.
As someone who has a love/hate relationship with Siri, this is only good news, Siri will become way more powerful and able to understand what you want to do.
This post is not going to be an overview of Apple Intelligence from the users perspective though (for which I suggest the excellent blog post from Simon Willison Thoughts on the WWDC 2024 keynote on Apple Intelligence) but will explore key concepts such as the Semantic Index, App Intents Toolbox, and foundational model adaptations utilized by Apple.