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AI Sample Efficiency Is Why Humans Still Learn Faster · Hanh D. Brown

AI Sample Efficiency Is Why Humans Still Learn Faster. We treat these models as glittering minds. The real engine is invisible: a massive black hole of data at the center, a millionfold more than a person ever sees. ai-2026 sample-efficiency ai-training-data scaling-laws ai-jobs You have probably pictured these models as glittering minds. Quick, fluent, a …

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5 Must-Read Resources for Mastering Small Language Models

  Contents# Introduction# The Architecture and Codebase# The Strategy and Agentic Workflows# The Ecosystem Overview# Where to Go From Here # Introduction  The narrative around generative AI is shifting in 2026. While massive frontier models keep grabbing headlines, the reality of enterprise AI deployment looks very different. Cost constraints, latency limits, and strict data privacy requirements have pushed engineering teams away …

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The Smooth Exponential Explains the Whole AI Moment · Hanh D. Brown

The Smooth Exponential Explains the Whole AI Moment. For years it looks like nothing. Then the curve turns and the whole world feels late. The smooth exponential is the lens that holds the calm and the urgency at once. ai-2026 smooth-exponential ai-job-loss ai-moats ai-risk For a long time the change looks like nothing to you. …

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Backpropagation Explained for Beginners (Part 2): There Has to Be a Better Way

Welcome back! our journey of understanding backpropagation in detail. Let’s briefly recall what we covered in Part 1 so far. ContentsA Quick RecapDo We Really Have to Repeat This?The Chain Rule to the RescueFollowing the Dependency PathPartial Derivatives vs. the Chain RuleApplying the Chain Rule to Our Neural NetworkStep 1: ∂L/∂y^partial L/partialhat{y}Step 2: ∂y^/∂a1partialhat{y}/partial a_1Step …

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Vibe Coding and Agentic Engineering Are Not the Same Job · Hanh D. Brown

Vibe Coding and Agentic Engineering Are Not the Same Job. For a year the code came back broken. Then it came back clean. The floor opened for everyone, and a quieter job appeared: keeping the bar while the machine moves fast. ai-2026 vibe-coding agentic-engineering jagged-intelligence verifiability Something changed in how software gets built. For years …

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7 Steps to Building and Deploying Your First Autonomous Agent

  Contents# Introduction# Step 1: Deciding What Your Agent Actually Needs to Do (and What It Shouldn’t)# Step 2: Picking Your Model and Framework# Step 3: Setting Up the Project# Step 4: Building the Core Agent Loop# Step 5: Giving It Memory and a Second Tool# Step 6: Adding Guardrails Before You Trust It# Step 7: Deploying It Somewhere Real# Wrapping Up # Introduction  Most …

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3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

Developers and customers building production AI agents need higher token efficiency, lower latency, and more reliable performance. Our Flash series of models is built to meet the sweet spot of efficiency and quality to enable scaling agentic workflows. Building on Gemini 3.5 Flash, we’re introducing new Gemini models: 3.6 Flash: Our workhorse model that delivers …

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Tabular LLMs: An Introduction to the Foundation Models That Predict Your Spreadsheet

model predicts the missing column of any table, zero-shot, the way a language model completes text. On the main community benchmark, every single-model entry above the best tuned gradient-boosted tree is now one of these. This post explains what they are, verifies the strongest one with unrestricted open weights on my own hardware, and maps …

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5 Key Concepts Behind Agentic AI Every Engineer Must Understand

  Contents# Introduction# 1. Tool Use and the Model Context Protocol# 2. Memory and Context Engineering# 3. Planning and Reasoning Loops# 4. Multi-Agent Orchestration# 5. Evaluation, Observability, and Guardrails# Wrapping Up # Introduction  If you ask a chatbot to find you a hotel in London, it will give you a list of names and let you do the rest. If you ask an …

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Google commits $40M to the Genesis Mission

Scientists today face challenges of extraordinary scale and complexity. From shaping and simulating the intricate dynamics of fusion plasma, to exploring the vast search space of new materials, to making sense of the exabytes of data pouring out of the world’s most advanced experimental facilities. The demands on modern research are unprecedented. Frontier AI can …

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