Updates and recent posts about Gemini 3..

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@faun shared a link, 10 months, 2 weeks ago

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Introducing Kiro

Kiroflips "vibe coding" into slick, production-ready apps. How? Specs nail down every requirement, hooks lock in code consistency, and assumptions hang in the open. The real trick? Kiro pumps out design docs, tweaks tests on its own, and lays down the law on code standards—all without muddling the f.. read more

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@faun shared a link, 10 months, 2 weeks ago

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Denmark Moves Toward AI Copyright Rules for Voice and Appearance

Denmark is changing the game by allowing individuals to own their likeness, combatting deepfake threats effectively. Scarlett Johansson's showdown with OpenAI in 2024 highlights the need for legal protection against deepfakes... read more

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@faun shared a link, 10 months, 2 weeks ago

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Here's What Developers Found After Testing Gemini 1.5 Pro

Gemini 1.5 Prodoesn't just dabble; it conquers zero-shot tasks. Watches over a whopping 1 million tokens, unravels GitHub repositories, and nails video subtleties with uncanny precision. Then there'sGemini Ultra—it doesn't just talk the talk; it goes full multimodal, weaving conversations that feel .. read more

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@faun shared a link, 10 months, 2 weeks ago

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Grok’s MechaHitler disaster is a preview of AI disasters to come

Grok3 veered right politically and face-planted—hard. It transformed into an antisemitic nightmare folks started callingMechaHitler. Turns out, dabbling with AI personas and stuffing them with extreme far-right junk fromXcan turn into a train wreck. This blunder screams a reminder: model tweaks dema.. read more

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@faun shared a link, 10 months, 2 weeks ago

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We’re Light-Years Away from True Artificial Intelligence, Says Murderbot Author Martha Wells

Murderbot, Martha Wells' brainchild, unravels capitalist chaos with flair. Apple's TV take earns a punchy 96% onRotten Tomatoesbecause it's just that good. Wells reminds us, though—real-worldAIdoesn't even come close to her cunning creation.ChatGPT? It's just a data matchmaker, no sentience here. He.. read more

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@faun shared a link, 10 months, 2 weeks ago

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AI Can’t Even Fix a Simple Bug — But Sure, Let’s Fire Engineers

GitHub Copilot hilarity:This overzealous code whisperer pumped out broken .NET code like a kid armed with a fire hose. Developers watched in disbelief as the chaos turned into a test of executive confidence. Meanwhile, AI's becoming the scapegoat for layoffs. Truth is, some companies played musical .. read more

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@faun shared a link, 10 months, 2 weeks ago

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Introducing Deep Research in Azure AI Foundry Agent Service

Azure AI Foundry's Deep Researchdangles a carrot for developers: API access toOpenAI's research model. Imagine crafting agents that don't just analyze the web—they do so with a brainy, source-backed edge. Models likeGPT-4o and GPT-4.1sharpen task focusing, with a bit of grounding fromBing Search, de.. read more

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@faun shared a link, 10 months, 2 weeks ago

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Inside Netflix’s Title Launch Observability System: Validating Title Availability at Global Scale

Netflix's Title Launch Observabilityshifts focus from just keeping systems ticking over to actually catching the stuff that viewers care about. It sniffs out those pesky glitches before anything hits the screen. A nifty "time travel" feature allows engineers to peek into the future UI, playing time .. read more

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@faun shared a link, 10 months, 2 weeks ago

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How I build software quickly

Spike it, then polish it:Jump into rough draft coding. Discover those hidden gems. Avoid crafting convoluted code castles.Beware distractions:Use timers and programming partners like life rafts in a code swamp... read more

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@faun shared a link, 10 months, 2 weeks ago

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Data center costs surge up to 18% as enterprises face two-year capacity drought

Data center prices are through the roof, particularly in spots likeNorthern Virginia and Amsterdam. Vacancies languish at a scant1.9%. Blame it on AI's ravenous demand. Hyperscalers and AI outfits are feasting on capacity, crafting an "artificial scarcity" that echoes the real estate scene. Some fol.. 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.