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@faun shared a link, 11 months, 1 week ago
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A visual introduction to vector embeddings

OpenAI's text-embedding-ada-002often gets a peculiar itch at dimension 196—vectors peaking awkwardly there. Entertext-embedding-3-small, swooping in to smooth out the distribution. Now, ontosimilarity metrics. For unit vectors, the dot product is your fast friend. It's interchangeable with cosine si.. read more  

A visual introduction to vector embeddings
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@faun shared a link, 11 months, 1 week ago
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AI agents have access to key data across the enterprise

82% of organizations have AI agents on deck; a mere 44% bother with security policies.That leaves a lot of open doors. A staggering 96% of tech pros are side-eyeing these agents as ticking time bombs, yet 98% plan to unleash more. It's like setting out catnip for hackers. These agents wield power wi.. read more  

AI agents have access to key data across the enterprise
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@faun shared a link, 11 months, 1 week ago
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AI didn’t kill Stack Overflow

Stack Overflow once buzzed with collective brainpower. But then, it got too wrapped up in reputation points, a full-on leaderboard obsession. This detour dimmed its shine. It turns out, platforms flourish on real teamwork, not just gamified dick measuring contests. As AI sweeps through the coding wo.. read more  

AI didn’t kill Stack Overflow
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@faun shared a link, 11 months, 1 week ago
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Gaining Strategic Clarity in AI

AI Opportunity Treewelds cutting-edge tech to raw business value. Meanwhile, theAI System Blueprintknits tech tightly to stakeholder priorities. Lean models? They fuse teams, squash doubt, and thrust AI into action with exhilarating speed... read more  

Gaining Strategic Clarity in AI
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@faun shared a link, 11 months, 1 week ago
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New AI innovations that are redefining the future for software companies

Azure AI Foundrygives developers the power to masterfully control AI agent workflows and streamline decision-making through a single API and SDK.Agentic DevOpselevates AI agents beyond mere coding assistants, morphing GitHub Copilot into a formidable dev partner eager to wrestle with code reviews an.. read more  

New AI innovations that are redefining the future for software companies
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@faun shared a link, 11 months, 1 week ago
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Building MCP Servers Like a Pro (With a Little Help from yfinance and LLMs)

Hook LLMs to real-time stock data with MCP + yfinance—see how to build, test, and deploy smarter with help from LLMs... read more  

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@faun shared a link, 11 months, 1 week ago
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LLM Optimization: LoRA and QLoRA

Learn how LoRA and QLoRA make it possible to fine-tune huge language models on modest hardware. Discover the adapter approach for scaling LLMs to new tasks—and why quantization is the next step in efficient model training... read more  

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@faun shared a link, 11 months, 1 week ago
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Linear Programming for Fun and Profit

Modal’s "resource solver" hacks cloud volatility. It taps into thesimplex algorithmto snag cheap GPUs. Scale-ups? Lightning-fast. Savings? In the millions... read more  

Linear Programming for Fun and Profit
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@faun shared a link, 11 months, 1 week ago
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Rust is Officially in the Linux Kernel

Rust struts into Linux 6.15with the flashy entrance of theNOVA DRM driver.No subtlety here; it's gunning for Nvidia's crown and promising a jetpack for those next-gen RTX beasts. Meanwhile,Fornjot CADwhispers sweet nothings to tinkerers: model anything your Rusty heart desires, straight from code to.. read more  

Rust is Officially in the Linux Kernel
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@faun shared a link, 11 months, 1 week ago
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GitHub MCP Exploited: Accessing private repositories via MCP

Invariantplayed detective and unearthed a gaping hole in GitHub MCP. This flaw lets sneaky attackers hijack agents using malicious GitHub issues, spilling private repo secrets all over the public domain. Fortify your agent systems: clamp down on access and deployInvariant Guardrailsalong withMCP-sca.. read more  

GitHub MCP Exploited: Accessing private repositories via MCP
NanoClaw is an open-source personal AI agent designed to run locally on your machine while remaining small enough to fully understand and audit. Built as a lightweight alternative to larger agent frameworks, the system runs as a single Node.js process with roughly 3,900 lines of code spread across about 15 source files.

The agent integrates with messaging platforms such as WhatsApp and Telegram, allowing users to interact with their AI assistant directly through familiar chat applications. Each conversation group operates independently and maintains its own memory and execution environment.

A core design principle of NanoClaw is security through isolation. Every agent session runs inside its own container using Docker or Apple Container, ensuring that the agent can only access files and resources that are explicitly mounted. This approach relies on operating system–level sandboxing rather than application-level permission checks.

The architecture is intentionally simple: a single orchestrator process manages message queues, schedules tasks, launches containerized agents, and stores state in SQLite. Additional functionality can be added through a modular skills system, allowing users to extend capabilities without increasing the complexity of the core codebase.

By combining a minimal architecture with container-based isolation and messaging integration, NanoClaw aims to provide a transparent, customizable personal AI agent that users can run and control entirely on their own infrastructure.