Outside Lands is Silicon Valley’s hottest music festival.
But something huge just happened.
Artists, musicians, and engineers from all over the world are here to show what’s possible at the cutting edge of AI and music
Live tweeting the demos from the @OutsideLLMs hackathon🧵:
1/ Spacial Gen
Digital concert experiences
Artist deploys an AR experience through an NFT and the listener is guided to a geofenced experience area https://t.co/Amv1suM24ctwitter.com/i/web/status/1…
Ever seen a cool event on a website but couldn’t find the calendar invites?
This chrome extension automatically scrapes events on any website and adds them to your calendar. Way more convenient than adding them manually https://t.co/WLfAJCZgsPtwitter.com/i/web/status/1…
The #NobelPrize in economics was just awarded to 3 top economists. #EconTwitter seems to be over it, but the data science/ML community is totally missing out!
Here's why Data Scientists should start paying attention and what they can take away 🧵
The prize was awarded to David Card, @metrics52, and Guido Imbens for their monumental contributions to statistical methodology and causal inference.
They used and developed strategies that were a true paradigm shift bridging the gap between data and causation in economics
One part of the prize went to David Card from UC Berkeley.
Card is most well-known for his famous minimum wage study that paradoxically revealed that an increase in the minimum wage did *not* reduce employment. How?
The study applied a strategy called Difference in Differences
Big tech teams win because they have the best ML Ops. These teams
- Deploy models at 10x speed
- Spend more time on data science, less on engineering
- Reuse rather than rebuild features
How do they do it? An architecture called a Feature Store. Here's how it works
🧵 1/n
In almost every ML/data science project, your team will spend 90-95% of the time building data cleaning scripts and pipelines
Data scientists rarely get to put their skills to work because they spend most of their time outside of modeling
Enter: The Feature Store
This specialized architecture has:
- Registry to lookup/reuse previously built features
- Feature lineages
- Batch+stream transformation pipelines
- Offline store for historical lookups (training)
- Online store for low-latency lookups (live inferences)