Updates and recent posts about Vertex AI..

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@rafidbottler gave 🐾 to Artificial Intelligence vs Machine Learning: What's the Difference? , 2 days, 19 hours ago.

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@anjali5 shared a link, 3 days, 15 hours ago

How to Fix Developer Productivity at 50+ Engineers

You ship a feature. It works. A week later, someone asks why it's not in staging yet, and you realize it's behind an infrastructure request that's still in review. The ticket isn't urgent enough to escalate. It's also not small enough to ignore. So it waits.

That's what a developer productivity problem feels like at 50 engineers.

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@laura_garcia shared a post, 3 days, 15 hours ago

Software Developer, RELIANOID

AI Reliability Engineering: The New Era of SRE

🤖 As AI becomes part of critical business operations, reliability is no longer just an infrastructure concern. From latency and model drift to observability and trust, AI workloads introduce a new set of challenges for modern SRE teams. In our latest article, we look at how reliability engineering i..

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@pluto_native started using tool Terraform , 6 days, 9 hours ago.

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@pluto_native started using tool Kubernetes , 6 days, 9 hours ago.

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@pluto_native started using tool Google Cloud Platform , 6 days, 9 hours ago.

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@pluto_native started using tool Amazon Web Services , 6 days, 9 hours ago.

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@eon01 shared a link, 6 days, 14 hours ago

Founder, FAUN.dev

A curated list of free AI models, APIs, and tools you can use without paying a cent.

Running AI shouldn't require a credit card. This list curates genuinely free models — open-weight models you can self-host, free API tiers from major providers, and tools to run everything locally.

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@eon01 added a new tool Unsloth , 6 days, 19 hours ago.

Course

@eon01 published a course, 6 days, 19 hours ago

Founder, FAUN.dev

Local AI Engineering with Ollama

#LangCha... #Unsloth #Fine-tu... #Ollama #MCP

Run, understand, customize, fine-tune, and build agentic apps on your own hardware

Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.