Links Justin Sends 3/21

Happy Friday!

With the record-setting acquisition of Wiz this week, a bunch of people have been asking me, "What is multicloud and how does it impact AI?"

Luckily, ChatGPT can distill my engineering mind into something a bit more palatable. Here’s a practical, easy-to-follow breakdown:

What is Multi-Cloud?

Multi-cloud refers to using multiple cloud service providers (like AWS, Google Cloud, and Microsoft Azure) simultaneously, rather than relying on just one. Companies use a multi-cloud approach to optimize performance, reduce risks, and leverage the unique strengths of each provider.

Let’s Explore a Hypothetical Example:

Imagine there's a company called FlamingoByte 🦩, a fast-growing AI-powered app that provides real-time recommendations for trendy vacation destinations.

• Google Cloud for AI Analytics:
  FlamingoByte uses Google Cloud because of its advanced AI tools and analytics capabilities. This allows the app to quickly analyze massive amounts of social media data, user preferences, and travel trends to provide accurate, personalized recommendations.

• AWS for Reliable App Infrastructure:
  To ensure their app never crashes during peak travel seasons, FlamingoByte relies on Amazon Web Services' dependable infrastructure. AWS handles heavy traffic effortlessly, providing users with a smooth, uninterrupted experience.

• Microsoft Azure for Secure User Management:
  For managing sensitive user information securely—like payment details and personal profiles—FlamingoByte trusts Azure, known for its robust security and reliable identity management solutions.

Why Would FlamingoByte Use Multi-Cloud?

• Risk Reduction: If one cloud provider experiences issues, FlamingoByte isn’t completely offline. Users might lose AI-driven recommendations temporarily if Google Cloud experiences trouble, but they'd still be able to log in securely (thanks to Azure) and access the app infrastructure (on AWS).

• Optimized Performance: Using different clouds allows FlamingoByte to select the best features from each provider, rather than settling for one provider’s average solutions.

• Cost Management and Flexibility: Multi-cloud strategies help companies avoid being stuck with a single vendor’s pricing, giving them more negotiating power and flexibility in their overall tech budget.

How Does This Impact AI?

Multi-cloud environments amplify AI capabilities by allowing businesses like FlamingoByte to:

• Access specialized AI tools and infrastructure tailored to their specific needs.

• Scale quickly and seamlessly without performance bottlenecks.

• Maintain AI services reliably, ensuring users always have access to intelligent features without interruption.

In short, multi-cloud strategies aren't just smart—they’re becoming essential, especially as businesses increasingly rely on AI-driven applications to stay competitive.

Now on to the links you’ve came here for 👇️ 

🛠️ OpenTools Beta Launch: Easy way for developers to equip their LLM Workflows and Agents with Tools

🔥 🛰️ FireSat Launch: Google and SpaceX launch the first of 50 FireSat Satellites into orbit — an initiative leveraging AI to detect and track wildfires

🐾 Baidu ERNIE 4.5 & X1: On par performance with DeepSeek R1 at a fraction of the cost + a multimodal model that competes with OpenAI’s GPT 4o

🔒️ Wiz Acquired for 32B: Google acquired the cloud security company Wiz to boost their AI cloud security for multicloud environments.

💰️ NJEDA AI Investment: $500 million NJ AI program seems to be more tailored towards attracting large corporates to invest in AI within the state.

🤯 Asus GX10: I love the attention companies are giving to local AI development — I have not seen this many developer focused machines come out in a while! This new Asus launch is super promising on paper to compete with some of the Mac Mini clusters and AMD AI HX clusters we are seeing for developers training and post training models.

-Justin

aka the guy with great AI links

Co-founder & Head of Technology @ BetterFutureLabs

[email protected] | LinkedIn