Skip to content
HomeInsights

Insights

Ideas for building
better software.

Engineering perspectives on architecture, product development, AI, and the everyday decisions behind useful software.

From the engineering desk

Browse practical articles or follow the latest technology updates.

Subscribe via RSS →

Curated links from external sources — not 360Softy original articles.

ExternalCloud
Google Cloud Blog

Introducing new session management tools with native, granular controls

Google Cloud session management provides flexible options for setting up session controls based on your organization’s security policy needs. To help you improve your security posture and mitigate credential theft and account takeover (ATO) risks, we have rolled out a 16-hour default session length for Google Cloud customers. We’ve now completed extending this security standard to all customers who had not already self-configured session lengths, but today’s cloud environments require even more

Security & Identity
Google Cloud BlogRead original
ExternalAI
NVIDIA Technical Blog

Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each

How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model? Nemotron 3.5 Lightning illustrates the... How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model? Nemotron 3.5 Lightning illustrates the answer: It uses a Mixture-of-Experts (MoE) architecture that selects only a subset of its parameters for each token. There are two dominant model architectures: Dense model and MoE. How

NVIDIA Technical BlogRead original
ExternalSoftware Engineering
DZone

KV Cache vs Prompt Cache: What's the Difference, and How Are They Related?

This article was originally published on my blog. For the latest version and future updates, please visit the original post: https://jaketao.com/language/en/kv-cache-vs-prompt-cache/. Every time a large language model generates a token, it draws on the content that came before it. If it had to compute everything from scratch at every step, responses would be much slower. When building an agent, the same set of system prompts, tool definitions, and conversation history is used over and over again

Let’s start with a conversation

Tell us what you’re working on.

An idea, a challenge, or a system that needs to work better. We’ll help you understand the next step.