Fudge Sunday - Dig Your Own SQLby Jay Cuthrell
This week we take a look back a year of podcasts episodes from a16z relating to data science and references to artificial intelligence and machine learning. Specifically, we’ll focus on the episodes worth downloading to your podcasting app that are evergreen and worth more than a single listen alone.
Since the last issue: 20 minutes of me talking
Last week I spoke in my capacity as a team member at Faction about the topic of multi-cloud data services patterns within gaming and healthcare, convergence, and the world of AR / VR in our future.
Sunday morning and we’re waking up
Let’s start with the big beats before we look at some of the podcast content from those that make big bets.
Where do we start?
Catching up on the entire catalog of a16z podcasts would take quite a time investment. For perspective – the catalog is already several years deep and the episode numbers are in the hundreds and Episode 636 was posted in July 2021.
For this issue, three podcasts episodes will be examined from 2020 and a list of key podcast episodes from pre-2020 will be shared at the end.
When I was going for my undergrad degree in engineering I remember a quad conversation with a peer that opened my mind in the early 1990s. Like many conversations started in those days, we were discussing majors as one does.
At the time, I was enamored with the possibilities of materials science and engineering such as room temperature superconductors. My perspectives were quite limited.
My infectious enthusiasm aide, my peer indicated a deeper desire to be one of the problem solvers of the next generation. So, I asked what that meant.
What that meant was a dual major. The dual majors would be physics and philosophy.
When this combination was explained to me, my mind was altered.
Emoji didn’t exist then but I probably looked like this: 🤔🤯
With this buildup in mind, listen to a superb opening metasummary from Sonal Chokshi followed by a deep discussion by Peter Wang and Martin Casado.
As recovering physicists, Peter and Martin cover everything from SQL to data warehouses to Python to business data analytics to Hadoop and the growing data science debates around everything from organizational approaches to development tools. Also, stay for the Moses metaphors – so many Moses metaphors. 🤓
Where do we begin?
Next, let’s look at some of two key data related debates coming from a year ago as we look ahead to the future.
This podcast episode is one of the recently transcribed as blog post that a16z has introduced recently. Of note, Ali Ghodsi, CEO and co-founder of Databricks goes into a deeper conversation with on tools with Martin Casado.
This white paper describes a unified data analytics platform solution, for accelerated data driven innovations powered by Databricks, Faction, and Dell Technologies.
Again, this podcast episode is one of the recently transcribed as blog post that a16z has introduced recently. As I’ve said before, Sonal and her a16z team are absolutely amazing.
This podcast episode is one of my favorite for a long drive. Why? It’s equally entertaining and informative.
You’ll get a relational vs. retrieval perspective from a Fivetran event that includes executive perspectives like those of Snowflake, Noteable, and dbt Labs.
While the conversation is only around a half hour, the discussion on use cases, tooling, APIs, SQL, and other access patterns are covered in a depth you rarely find in panels with this many participants.
Again, there are hundreds of a16z podcasts episodes.
However, if you are interested in the topics covered in this issue of my newsletter and want to listen to the prior conversations that might have influenced them (and my newsletter), enjoy these podcast episodes a well.
- The History and Future of Machine Learning
- Deep Learning for the Life Sciences
- Automation + Work, Human + Machine
- Ancient Dreams of Technology, Gods & Robots
One last Techmeme Quote Tweet for the road…
Tip of the hat to those that opine on the timelines for eventual displacement (or at least partnering via augmentation) of the C Suite by sufficiently advanced AI. https://t.co/WfKMzt5BEc
Nvidia says part of its April keynote was led by a virtual replica of CEO Jensen Huang, created by scanning Huang and then training an AI to mimic his gestures (@lorenzofb / VICE)
✍️ 🤓 Edit on Github 🐙 ✍️
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