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@laura_garcia shared a post, 1 year, 2 months ago
Software Developer, RELIANOID

🚀 Moving from Alteon to a Modern Load Balancer: Why and How? 🚀

As Alteon load balancers become obsolete, organizations are moving to more advanced, cloud-native solutions. One great option is the RELIANOID load balancer, designed to handle modern, high-traffic environments with superior flexibility, scalability, and security. Here’s how to make the switch: 1️⃣ ..

kb Alteon configuration migration
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

Breaking Down Splunk Costs for SREs and DevOps Teams

Explore Splunk's pricing and how it impacts SREs and DevOps teams. Learn how to manage costs while maintaining performance.

splunk
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@laura_garcia shared a post, 1 year, 2 months ago
Software Developer, RELIANOID

🚀 A Busy April Ahead for RELIANOID!

April is shaping up to be an exciting and action-packed month for us at RELIANOID! Our team will be making a big effort to attend multiple key industry events, connecting with experts, partners, and clients to discuss the latest in cybersecurity, networking, and ADC solutions. Want to know where to ..

Recap Events April
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9

Reliability vs Availability: A Simple Breakdown

Reliability and availability are crucial concepts in DevOps. Here's a simple breakdown to help you understand their key differences and importance.

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@faun shared a link, 1 year, 2 months ago
FAUN.dev()

Horseless intelligence

Prompt engineeringis where the magic really hits the road. Phrases like "think step-by-step" will crank the gears inLLMs. Sure, they fumble now and then, but these aren't crystal balls—they're your best strategic gadgets... read more  

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@faun shared a link, 1 year, 2 months ago
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Improving Recommendation Systems & Search in the Age of LLMs

Semantic IDsandmultimodal embeddingsshake up recommendation systems by wrestling the cold-start conundrum and taming those unruly long-tail items. Armed with transformer wizardry and bold variational autoencoders, they rev up user preference predictions like nobody's business. EnterM3CSR. It flexes .. read more  

Improving Recommendation Systems & Search in the Age of LLMs
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@faun shared a link, 1 year, 2 months ago
FAUN.dev()

The 500 Million Worker Problem

India'sdemographic dividendteeters on the edge asAI's fast climbmenaces both high-end IT gigs and low-end services, tossing economic perks into disarray. Those shinyAI subscriptions? They outpace India's newbie engineers in cost, speed, and accuracy, upending an age-old growth strategy. Yet, while I.. read more  

The 500 Million Worker Problem
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@faun shared a link, 1 year, 2 months ago
FAUN.dev()

Open source devs are fighting AI crawlers with cleverness and vengeance

AI web-crawlers: the tireless digital vermin scuttling past robots.txt files to unleash DDoS chaos on open-source projects.Developers aren’t taking it lying down. Armed with inventive weapons like theAnubischallenge and tools likeNepenthes, along with Cloudflare’s mysteriousAI Labyrinth, they repel .. read more  

Open source devs are fighting AI crawlers with cleverness and vengeance
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@faun shared a link, 1 year, 2 months ago
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There is no Vibe Engineering

"Vibe Coding," a phrase birthed by Andrej Karpathy, turns coding into an AI-driven joyride, hands-free from the codebase. Perfect playground for prototypes, though calling it production-ready is like trusting a paper airplane for transatlantic travel. The real grind—crafting systems that scale and f.. read more  

There is no Vibe Engineering
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@faun shared a link, 1 year, 2 months ago
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The Next AI Battleground: Why China's Manus Could Leapfrog Western Agent Technology

Manus AIboasts it can marry "mind" and "hand" for tasks beyond ChatGPT's chatty limitations. They're flirting with AGI's elusive shadow. Across the Pacific,DeepSeekrattles tech stocks, a sharp reminder of the cutthroat AI tug-of-war between the US and China. Manus might just tip the balance in this .. read more  

The Next AI Battleground: Why China's Manus Could Leapfrog Western Agent Technology
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.