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@laura_garcia shared a post, 10 months, 3 weeks ago

Software Developer, RELIANOID

🌐 What is Border Gateway Protocol (BGP)?

BGP is the backbone of the internet — and it’s powering RELIANOID’s advanced routing strategy. In our latest blog, we cover: ✅ eBGP for datacenter & edge connectivity ✅ iBGP for intra-datacenter load balancing ✅ How to build global clusters without GTM, GSLB, or DNSLB ✅ Real-world BGP use cases & se..

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@anjali shared a link, 10 months, 3 weeks ago

Customer Marketing Manager, Last9

How to Get Logs from Docker Containers

Learn how to access, filter, and monitor Docker container logs, plus tips for structured logging, rotation, and production-ready setups.

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@anjali shared a link, 10 months, 3 weeks ago

Customer Marketing Manager, Last9

Improve Consistency Across Signals with OTel Semantic Conventions

Correlate logs, metrics, and traces faster by using consistent field names and schemas with OpenTelemetry semantic conventions.

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@anjali shared a link, 10 months, 3 weeks ago

Customer Marketing Manager, Last9

How Replicas Work in Kubernetes

Understand how Kubernetes uses replicas to ensure your application stays available, handles traffic spikes, and recovers from pod failures automatically.

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@arshadmas shared a post, 10 months, 3 weeks ago

Product Marketer, manageengine

GCP monitoring: A comprehensive guide into maximizing cloud performance

#Google ... #gcp mon... #google ...

Keeping mission-critical workloads healthy on Google Cloud Platform (GCP) isn’t optional—it’s your job. As organizations increasingly move to GCP for its elasticity and scalability, the complexity of managing cloud-native and hybrid environments grows. For ITOps and CloudOps professionals, the chall..

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@anjali shared a link, 10 months, 3 weeks ago

Customer Marketing Manager, Last9

Instrument LangChain and LangGraph Apps with OpenTelemetry

Understand how to trace, monitor, and debug LangChain and LangGraph apps using OpenTelemetry, down to chains, tools, tokens, and state flows.

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@faun shared a link, 10 months, 3 weeks ago

FAUN.dev()

I’m Losing All Trust in the AI Industry

AI bigwigs promiseAGIin a quick 1-5 years, but the revolving door at labs like OpenAI screams wishful thinking. As AI hustles to serve up habit-forming products, the priority on user engagement echoes the well-troddensocial mediaplaybook. Who needs productivity, anyway? Cash fuels AI's joyride, with.. read more

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@faun shared a link, 10 months, 3 weeks ago

FAUN.dev()

EU businesses push for freedom from AI rules and competition

Mistral's"AI for Citizens" isn't just about tech; it's about shaking up public services for the better. Meanwhile, in the EU, a plot twist—50 European firms holler for halting the AI Act, all in the name of staying competitive. They argue speed matters more than red tape. But hey, watchdogs eye them.. read more

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@faun shared a link, 10 months, 3 weeks ago

FAUN.dev()

Gemma 3n Introduces Novel Techniques for Enhanced Mobile AI Inference

Gemma 3nshakes up mobile AI with a two-punch combo:Per-Layer Embeddingsthat axe RAM usage andMatFormerthat sends performance into overdrive with elastic inference and nesting.KV cache sharingcranks up the speed of streaming responses, though it taps out at multilingual audio processing for clips up .. read more

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@faun shared a link, 10 months, 3 weeks ago

FAUN.dev()

From Noise to Structure: Building a Flow Matching Model from Scratch

Train a petite neural net to align velocity flows between distributions. DeployFlow Matching lossfor the job. Harness the precision of theAdamoptimizer to keep it sharp... read more

Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.