Cloud Computing

You’ve probably felt the frustration that arises when a project fails to meet established deadlines. And perhaps you’ve also encountered scenarios where project staff or computing have been reallocated to higher priority projects. It can be super challenging to get projects done on time with this kind of uncertainty.  That’s especially true for Site Reliability […]

September was a whirlwind of innovation for Google Cloud databases. From groundbreaking announcements to product updates and inspiring customer stories, we’ve got it all. So grab your favorite fall beverage and let’s dive into the latest from Google Cloud databases. Key announcements Oracle Database is now generally available on Google Cloud. Customers can now run

We chat with Deedy Das, a Principal at Menlo Ventures, who began his career as a software engineer at Facebook and Google. He then dipped a toe in the startup world, spending time at the company now know as Glean. More recently he started a career as a venture capitalist, investing in AI and Infra

Prompt design and engineering stands out as one of the most approachable methods to drive meaningful output from a Large Language Model (LLM). ​​However, prompting large language models can feel like navigating a complex maze. You must experiment with various combinations of instructions and examples to achieve the desired output. Moreover, even if you find

Masked self-attention is the key building block that allows LLMs to learn rich relationships and patterns between the words of a sentence. Let’s build it together from scratch.

As the number of applications and services hosted on Google Kubernetes Engine (GKE) continues to grow, so does the demand for private IPv4 addresses (RFC 1918). For many large organizations, the RFC1918 address space is becoming increasingly scarce, leading to IP address exhaustion challenges that impact their application scale. IPv6 solves this exact address exhaustion

With the addition of vector search earlier this year, Memorystore for Redis emerged as an ideal platform for gen AI use cases such as Retrieval Augmented Generation (RAG), recommendation systems, semantic search, and more. Why? Because of its ultra-low latency vector search. Just a single Memorystore for Redis instance can perform vector search at single-digit