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@faun shared a link, 1 year, 1 month ago

FAUN.dev()

JFrog’s Journey with AWS Graviton

JFrog’s leap toAWS Gravitonunleashed some wizardry: slashing compute costs by20%, slicing CPU usage by another20%, and shaving network latency by10%. But here’s the kicker—carbon footprint plummeted by60%. That’s efficiency with an eco-twist. They juggled feature flags and multi-architecture support.. read more

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@faun shared a link, 1 year, 1 month ago

FAUN.dev()

37signals on-prem migration to save millions, abandon AWS

37signalsplans to chop its cloud bill from a hefty$3.2Mto under$1Ma year by dumping AWS for its own gear, with some help from swift Dell and Pure Storage systems. Oh, andAWStossed in a $250K fee waiver to nudge that transition along... read more

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@faun shared a link, 1 year, 1 month ago

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Taking a Look at Database Disk, Memory, and Concurrency Management

Databasesdance between block and file-level access. They cleverly use memory like a magician with a hidden pocket, smoothing over sluggish disk interactions. Logs? They’re the secret sauce for slick crash recovery.Concurrency controlin the mad circus of transactions? Locks. They're the backstage cre.. read more

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@faun shared a link, 1 year, 1 month ago

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Google debuts an updated Gemini 2.5 Pro AI model ahead of I/O

Gemini 2.5 Pro Preview (I/O edition)is here, flexing its muscles in code editing and web app creation. This newcomer muscles its way to the top of theWebDev Arena Leaderboard. As if that wasn't enough, it scores a jaw-dropping84.8%on VideoMME for video analysis. And guess what? The price tag hasn’t .. read more

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@faun shared a link, 1 year, 1 month ago

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Claude’s AI research mode now runs for up to 45 minutes before delivering reports

Anthropic's Claude just supercharged its Research feature, cranking out reports from hundreds of sources in a blazing 45 minutes.But stay sharp—AI has a knack for inventing phantom sources... read more

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@faun shared a link, 1 year, 1 month ago

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AI predicted the next pope. Did it get it right?

A.I. algorithm incorrectly predicted Italian Cardinal Parolin as next pope; new model analyzes voting trends and predicts U.S. Cardinal Prevost as a compromise candidate. Model may improve with inclusion of more political and geographical data, but current analysis offers insights into potential pap.. read more

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@faun shared a link, 1 year, 1 month ago

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Stop overbuilding evals

Over-engineering smothers momentum. Get it to prod yesterday. Imperfection? Own it. Tweak with real folks in the wild. Feature flags and sanity checks? Priceless. Theory's just noise until reality weighs in... read more

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@faun shared a link, 1 year, 1 month ago

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Most AI spending driven by FOMO, not ROI, CEOs tell IBM

Only25%of AI projects actually deliver returns on investment. Yet,61%of CEOs are ready to double down and scale their AI agents. Surprisingly,64%jumped in headfirst, investing before the payoff even showed its face... read more

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@faun shared a link, 1 year, 1 month ago

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Researchers Fine-Tune LLM for Reasoning with Only 1,000 Examples

Meet the"Wait" token trick—a clever nudge that sharpens a model's reasoning. It mirrors OpenAI's o1-preview magic using only 1,000 examples. And guess what? Not a speck of reinforcement learning in sight... read more

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@faun shared a link, 1 year, 1 month ago

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3: Think Deeper, Act Faster

Qwen3sets itself apart with its dazzlingHybrid modes. Flip between deep thought and rapid-fire replies. A magician capable of juggling complexity and speed. Themassive 235B modelthrows elbows with the high rollers in AI town. Meanwhile, the nimble30B MoE variantdazzles with its frugality, flexing st.. read more

Levelop is an interview preparation platform designed specifically for working software engineers (typically with 2–6 years of experience) who want to land jobs at top-tier tech companies.

Instead of just handing you endless lists of problems or passive videos to watch, Levelop uses an active, AI-guided approach to help you build the right mental models for tough technical interviews.

Here is how it works:

Two Specialized AI Mentors: * Orion (Coding AI): Instead of just telling you that your code is wrong, Orion steps in when your code fails, maps out where your knowledge gap is, and guides you to fix it yourself.

Aurora (System Design AI): Rather than making you watch a 40-minute video, Aurora has a live conversation with you to explain foundational system design concepts before you even start drawing on the canvas.

Sprint-Based Practice: You practice in structured loops called "sprints," which combine both Data Structures & Algorithms (DSA) and system design problems.

Actionable Feedback Loop: At the end of every sprint, you receive a detailed report. It scores your technical skills, gives you a behavioral profile, and ranks the exact weaknesses you need to focus on during your next sprint.

In short, it is a smart, interactive practice arena that focuses on actively fixing your specific weaknesses rather than just tracking how many hours you spend studying.