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@faun shared a link, 11 months, 3 weeks ago
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From Zero to Hero: Build your first voice agent with Voice Live API

TheVoice Live APIditches the clutter of juggling models. One API call, and voilà—real-time,natural-sounding bots. It’s harnessed over WebSocket, keeping everything sharp and efficient... read more  

From Zero to Hero: Build your first voice agent with Voice Live API
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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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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, 3 weeks 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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Using AI to outsmart AI-driven phishing scams

Phishing scamsare growing craftier, employing AI likeFraudGPTto weave through filters and masquerade as real emails, boosting scam rates by70%. AI can unveil sneaky phishing patterns humans miss, but it loves a good panic. It often cries wolf with false alarms and needs a babysitter to adjust to eve.. read more  

Using AI to outsmart AI-driven phishing scams
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@faun shared a link, 11 months, 3 weeks 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, 3 weeks 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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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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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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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
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.