Cloud Computing
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3 secrets to deploying LLMs on cloud platforms
Let’s not make the same mistakes we did 10 years ago. It is possible to deploy large language models in the cloud more cost-effectively and with less risk.
Better application networking and security with CAKES
How the CAKES stack, centered on Kubernetes, addresses API, networking, security, and compliance challenges while speeding up delivery and lowering costs.
The cloud is benefiting IT, but not business
A recent study shows that the cloud benefits the IT department more than other business areas. That’s not enough to make it a success.
Six key takeaways from Google Cloud Next ’24
Generative AI was the dominant theme at Google Cloud Next ’24, as Google rolled out new chips, software updates for AI workloads, updates to LLMs, and generative AI-based assistants for its machine learning platform Vertex AI.
Google unveils open source projects for generative AI
Google introduced an LLM inference engine, a library of reference diffusion models, and TPU optimizations for transformer models at Google Cloud Next ’24.
Google updates Vertex AI with new LLM capabilities, agent builder feature
Other updates include grounding applications and virtual agents in Google Search via Vertex AI and Vertex AI agent builder.
Google adds Gemini to databases to aid faster code development, migration
Gemini's availability across Google Cloud database offerings is expected to help developers code and migrate faster than Duet AI, which was integrated last year.
Google’s Gemini Cloud Assist helps manage cloud apps
AI-powered assistant for Google Cloud can help design, deploy, and configure apps, troubleshoot issues, and optimize performance and costs.
Gemini Code Assist debuts at Google Cloud Next 24
Formerly Duet AI for Developers, Gemini Code Assist taps Google’s most powerful generative AI model for code completion, code generation, and code chat.
ESG tools for cloud computing can be a distraction
ESG scores can be a helpful tool in the pursuit of sustainability. But they won’t look deep into your architecture to see if poor design is wasting money and energy.
Choosing the right GPU for AI, machine learning, and more
Hardware requirements vary for machine learning and other compute-intensive workloads. Get to know these GPU specs and Nvidia GPU models.
Rapid B2B integrations with Ballerina and Choreo
How WSO2’s Ballerina language and Choreo platform can be used to quickly develop, test, and deploy partner-specific EDI processing modules.
AI advancements are fueling cloud infrastructure spending
It’s no surprise that AI will be a gold mine for cloud providers. However, if vendors and customers move too far in the wrong direction, we’ll waste business value for years.
Using Neo4j’s graph database for AI in Azure
New techniques make graph databases a powerful tool for grounding large language models in private data.
GitHub Actions update tightens security
Automated CI/CD platform update adds Azure private networking for improved security and GPU-hosted runners for machine learning.
There's more to cloud architecture than GPUs
Many systems architects already see too much focus on processors for generative AI systems and not enough attention on other vital components.
Redis vs. the trillion-dollar cabals
The Redis license change hurts no one except AWS and other cloud giants. If they gave back a little, they wouldn’t need watered-down forks.
