Join us

ContentUpdates and recent posts about Gemini 3..
Link
@faun shared a link, 1 year ago
FAUN.dev()

How we optimized LLM use for cost, quality, and safety to facilitate writing postmortems

Postmortem Optimization:Slashing LLM costs while preserving quality and safety. Who said AI can’t spruce up even the most mind-numbing tasks?.. read more  

Link
@faun shared a link, 1 year ago
FAUN.dev()

OpenAI to help UAE develop one of world's biggest data centers

OpenAI plans to help develop amassivenew data center in the United Arab Emirates that may eventually be one of the largest in the world, Bloomberg News reported on Friday. The ChatGPT maker is expected to be one of the primary anchor tenants for a5-gigawattdata center campus in Abu Dhabi, the report.. read more  

Link
@faun shared a link, 1 year ago
FAUN.dev()

9 Months Later, Microsoft Finally Fixes Linux Dual-Booting Bug

Microsoftjust dropped the KB5058385 patch and—hallelujah—it solves the nine-month Secure Boot nightmare. But hold your cheers, Linux dual-booters. You're still stuck in no-man's land... read more  

9 Months Later, Microsoft Finally Fixes Linux Dual-Booting Bug
Link
@faun shared a link, 1 year ago
FAUN.dev()

From manual fixes to automatic upgrades — building the Codemod Platform at Lyft

Lyft's Codemod Platformturns chaos into calm. It converts disruptive updates into a few quick fixes, slashing manual review time for over 100 frontend microservices. Adoption rates rocketed by up to30% in two weeks. They wieldjscodeshiftlike a wizard's wand—transforming multiple languages and integr.. read more  

From manual fixes to automatic upgrades — building the Codemod Platform at Lyft
Link
@faun shared a link, 1 year ago
FAUN.dev()

How to enhance your application resiliency using Amazon Q Developer

Amazon Qbehaves like a tech-savvy wizard, dialing up app resilience with style. It champions Multi-AZ deployments, elastic scaling, and caching to strengthen AWS fortresses. With a talent forreal-time failure analysisand savvy DR strategies, it transforms basic setups into systems that laugh in the .. read more  

How to enhance your application resiliency using Amazon Q Developer
Link
@faun shared a link, 1 year ago
FAUN.dev()

CI/CD Implementation for Azure Sentinel Using Terraform

Azure Sentineldeployment now tightens security through CI/CD usingTerraformandAzure DevOps. Say goodbye to those clunky manual setups. Hello, sleek automation... read more  

CI/CD Implementation for Azure Sentinel Using Terraform
Link
@faun shared a link, 1 year ago
FAUN.dev()

Demonstrably Secure Software Supply Chains with Nix

Nixshatters the myth that security demands clunky, air-gapped setups. It's a wizard at crafting reproducible, secure builds without dragging down speed or flexibility. Regulators can rest easy with Nix's "source closure" magic trick: full offline rebuilds and rock-solid supply chain integrity, all w.. read more  

Demonstrably Secure Software Supply Chains with Nix
Link
@faun shared a link, 1 year ago
FAUN.dev()

Zero-Touch Bare Metal at Scale

Mapping hardware to Linux device names? Chaos. EnterSystemD: its magic cleans up the network interface mess. Storage naming, though? Serial numbers rule the roost. With the sharp combo ofRedfish HTTP APIandPixiecore, they revamped server setup. Price tag? A jaw-droppingunder $1 for 50 servers. Thank.. read more  

Zero-Touch Bare Metal at Scale
Link
@faun shared a link, 1 year ago
FAUN.dev()

Linux Foundation debuts Cybersecurity Skills Framework to address enterprise talent gaps

Linux Foundationdrops aglobal Cybersecurity Skills Frameworkto battle the talent drought. It links skills to heavyweights likeDoD Directive 8140... read more  

Linux Foundation debuts Cybersecurity Skills Framework to address enterprise talent gaps
Link
@faun shared a link, 1 year ago
FAUN.dev()

Why Even Stateless AKS Clusters Might Need Backup

Backing up those “stateless”AKS clustersisn’t just nerdy paranoia. Config drift, compliance headaches, and meddling hands make it a real necessity. In the DevOps trenches, clusters often wander off script from Git. Here, automated AKS backups ride in like heroes—capturing real-time snapshots, stream.. 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.