Gemini 3 - Google’s third-generation frontier AI model family

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@tairascott shared a post, 2 weeks, 1 day ago

AI Expert and Consultant, Trigma

How Do Large Language Models (LLMs) Work? An In-Depth Look

Discover how Large Language Models work through a clear and human centered explanation. Learn about training, reasoning, and real world applications including Agentic AI development and LLM powered solutions from Trigma.

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@laura_garcia shared a post, 2 weeks, 1 day ago

Software Developer, RELIANOID

🔐 RELIANOID at Gartner IAM Summit 2025 | Dec 8–10, Grapevine, TX

We’re heading to the Gartner Identity & Access Management Summit to showcase how RELIANOID’s intelligent proxy and ADC platforms empower modern IAM: enhancing Zero Trust enforcement, adaptive access, and hybrid/multi-cloud security. Join us to explore AI-driven automation, ITDR, and identity governa..

Gartner Identity and Access Management Summit 2025 relianoid

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@varbear shared a link, 2 weeks, 2 days ago

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Confessions of a Software Developer: No More Self-Censorship

A mid-career dev hits pause after ten years in the game -realizing core skills likepolymorphism, SQL, and automated testingnever quite clicked. Leadership roles, shipping products, mentoring junior devs - none of it filled those gaps. They'd been writingC#/.NETfor a while too. Not out of love, just .. read more

Confessions of a Software Developer: No More Self-Censorship

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@varbear shared a link, 2 weeks, 2 days ago

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Building a Blockchain in Go: From 'Hello, Block' to 10,000 TPS

A new Go tutorial shows how to build a lean, fast blockchain - clocking ~10,000 TPS - without the usual bloat. It covers the full stack:P2P networking,custom consensus, and properstate management. No unbounded mempools. No missing snapshots. Just a chain that actually runs, benchmarked on real machi.. read more

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@varbear shared a link, 2 weeks, 2 days ago

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Inside the GitHub Infrastructure Powering North Korea’s Contagious Interview npm Attacks

The Socket Threat Research Team has been following North Korea’s Contagious Interview operation as it targets blockchain and Web3 developers through fake job interviews. The campaign has added at least197 malicious npm packagesand over31,000 downloadssince last report, showcasing the adaptability of.. read more

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@varbear shared a link, 2 weeks, 2 days ago

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Before You Push: Implementing Quality Gates in Your Software Project

This post discusses best practices for automated testing in software engineering, including unit tests and integration tests for databases, APIs, and emulators. It also covers end-to-end tests using tools like Cypress, Appium, Postman, and more. Additionally, it highlights the importance of environm.. read more

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@varbear shared a link, 2 weeks, 2 days ago

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How to Get Developers in Your Team to Contribute to Your Test Automation

A fresh blog post dives into how to get devs pulling their weight ontest automation- not as extra credit, but as part of shipping code. The playbook: tie automation work straight to thedefinition of done, clear up who owns what, and stop pretending delivery pressure is a mystery. The big idea? Most .. read more

How to Get Developers in Your Team to Contribute to Your Test Automation

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@varbear shared a link, 2 weeks, 2 days ago

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Partitions, Sharding, and Split-for-Heat in DynamoDB

DynamoDB starts to grumble when a single partition gets hit with more than 1,000WCU. To dodge throttling, writes need to fan out across shards. Recommended move: start with10 logical shards. WatchCloudWatch metrics. DialNup or down. Letburstandadaptive capacitybuy you breathing room - untilSplit-for.. read more

Partitions, Sharding, and Split-for-Heat in DynamoDB

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@varbear shared a link, 2 weeks, 2 days ago

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Building Mac Farm: Running 2000+ iOS Pipelines Daily

At Trendyol, they runover 2,000 iOSpipelines daily across130 Mac machines, executing50,000+ unit testsand10,000+ UI testsfor their iOS apps. The team initiated a mobile CI transformation to address the challenges of scale and performance as their team grew and AI usage increased. They built a macOS .. read more

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@kaptain shared a link, 2 weeks, 2 days ago

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In-place Pod resizing in Kubernetes: How it works and how to use it

Kubernetes 1.33 and 1.34 takein-place Pod resource updatesfrom beta to battle-ready. You can now tweak CPU and memory on the fly - no Pod restarts needed. It's on by default. What’s new: memory downsizing with guardrails, kubelet metrics that actually tell you what’s going on, and smarter retries th.. read more

In-place Pod resizing in Kubernetes: How it works and how to use it

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.