288: You Might Be Able to Retrain Notebook LM Hosts to be Less Annoyed, But Not Your Cloud Pod Hosts

Welcome to episode 288 of The Cloud Pod – where the forecast is always cloudy! Justin, Ryan, and Jonathan are your hosts as we make our way through this week’s cloud and AI news, including back to Vertex AI, Project Digits, Notebook LM, and some major improvements to AI image generation. 

Titles we almost went with this week:

• Digits… I’ll show you 5 digits…
• The only digit the AWS local zone in New York shows me is the middle one
• Keep one eye open near Mercedes with Agentic AI

A big thanks to this week’s sponsor:

We’re sponsorless! Want to get your brand, company, or service in front of a very enthusiastic group of cloud news seekers? You’ve come to the right place! Send us an email or hit us up on our slack channel for more info. 

General News

01:59 Nvidia announces $3,000 personal AI supercomputer called Digits

• If you don’t want to hand over all your money to the cloud providers, you will be able to hand over $3,000 dollars to Nvidia… for a computer that is probably going to be obsolete in <12 months. That’s fun! 
• The new personal AI supercomputer, called Project Digits, will launch in May. 
• The heart of Digits is the new GB10 Grace Blackwell Superchip, which packs enough processing power to run sophisticated AI models, while being compact enough to fit on a desk and run from a standard power outlet.
• Digits can handle AI models with up to 200 billion parameters, and looks very similar to a Mac Mini. 
• “AI will be mainstream in every application for every industry. With Project Digits, the Grace Blackwell Superchip comes to millions of developers,” Nvidia CEO Jensen Huang said in a press release. “Placing an AI supercomputer on the desks of every data scientist, AI researcher, and student empowers them to engage and shape the age of AI.”
• The Digits system comes with 128gb of unified coherent memory and up to 4tb of NVME storage.  For even more demanding apps, two digit systems can be linked together to handle models with 405b parameters. 
• The GB10 chip delivers up to 1 petaflop of AI performance, meaning it can perform 1 quadrillion AI calculations per second. 
• Suppose you plunk down the money for Digits. In that case, you will also get access to Nvidia’s AI software library, including development kits, orchestration tools and pre-trained models available through the Nvidia NGC catalog. 
• The system runs on a Linux-based NVidia NGC catalog, and supports popular frameworks like PyTorch, Python and Jupyter notebooks. 

09:25 Jonathan – ““The Blackwell is pretty recent, it’s the one that had a lot of problems with yield. And I kind of suspect that they’re sort