Welcome to episode 308 of The Cloud Pod – where the forecast is always cloudy! Justin and Matt are on hand and ready to bring you an action packed episode. Unfortunately, this one is also lullaby free. Apologies. This week we’re talking about Databricks and Lakebridge, Cedar Analysis, Amazon Q, Google’s little hiccup, and updates to SQL – plus so much more! Thanks for joining us.

• KV Phone Home: When Your Key-Value Store Goes AWOL
• When Your Coreless Service Finds Its Core Problem
• Oracle’s Vanity Fair: Pretty URLs for Pretty Penny
• From Warehouse to Lakehouse: Your Free Ticket to Cloud Town
• 1⃣Databricks Uno: Because One is the Loneliest Number
• Free as in Beer, Smart as in Data Science
• Cedar Analysis: Because Your Authorization Policies Wood Never Lie
• Cedar Analysis: Teaching Old Policies New Proofs
• Amazon Q Finally Learns to Talk to Other Apps
• Tomorrow: Visual Studio’s Predictive Edit Revolution
• The Ghost of Edits Future: AI Haunts Your Code Before You Write It
• IAM What IAM: Google’s Identity Crisis Breaks the Internet
• Permission Denied: The Day Google Forgot Who Everyone Was
• 403 Forbidden: When Google’s Bouncer Called in Sick
• AWS Brings the Heat to Fusion Research
• Larry’s Cloud Nine: Oracle Stock Soars on Forecast Raise
• OCI You Later: Oracle Bets Big on Cloud Growth
• Oracle’s Crystal Ball Shows 40% Cloud Growth Ahead
• Meta Scales Up Its AI Ambitions with $14 Billion Investment
• From FAIR to Scale: Meta’s $14 Billion AI Makeover
• Congratulations Databricks one, you are now the new low code solution.
• AWS burns power to figure out how power works

02:12 Zuckerberg makes Meta’s biggest bet on AI, $14 billion Scale AI deal

• Meta is finalizing a $14 billion investment for a 49% stake in Scale AI, with CEO Alexandr Wang joining to lead a new AI research lab at Meta.
• This follows similar moves by Google and Microsoft acquiring AI talent through investments rather than direct acquisitions to avoid regulatory scrutiny.
• Scale AI specializes in data labeling and annotation services critical for training AI models, serving major clients including OpenAI, Google, Microsoft, and Meta.
• The company’s expertise covers approximately 70% of all AI models being built, providing Meta with valuable intelligence on competitor approaches to model development.
• The deal reflects Meta’s struggles with its Llama AI models, particularly the underwhelming reception of Llama 4 and delays in releasing the more powerful “Behemoth” model due to concerns about competitiveness with OpenAI and DeepSeek. Meta recently reorganized its GenAI unit into two divisions following these setbacks.
• Wang brings both technical AI expertise and business acumen, having built Scale AI from a 2016 startup to a $14 billion valuation. His experience includes defense contracts and the recent Defense Llama collaboration with Meta for national security applications.
• For cloud providers and dev...