#skill distillation
83 related articles
·2 min
Is Being a Computer Vision Engineer Worth It? A Deep Dive into Salary and Career Paths
In-depth analysis comparing CV engineer vs. standard SDE salaries, career growth, and satisfaction. Explore the advantages and market limitations of specializing in computer vision.
Read more →
·6 min
AI Coding Boosts Productivity 10x: Are Programmers Writing Their Own Pink Slips?
A senior developer admits 95% of work is done by Claude Code, with 10x productivity gains. From coding to architecture, AI is eroding programmers' core skill moats. Deep analysis of AI coding's impact on tech employment.
Read more →
·3 min
CraftStory Review: Train a Digital Avatar in 15 Seconds, AI Human Videos at 4.5 Cents Per Second
CraftStory is a lightweight AI human video tool supporting single-image video generation and 15-second custom digital avatars at just 4.5 cents per second, built on licensed actor data.
Read more →
·2 min
book-to-skill: An Open-Source Tool That Converts Technical Book PDFs into Claude Code Skills
book-to-skill is an open-source GitHub project with over 10K stars that converts technical book PDFs into Claude Code Skills, enabling AI coding assistants to directly leverage book knowledge.
Read more →
·4 min
Opus 5 Real-World Testing: Cheaper Yet Stronger — Why It's Now My Default Coding Model
In-depth testing of Claude Opus 5's coding abilities vs Fable 5 and 5.6 Sol. Why Opus 5 outperforms pricier models at half the token cost, plus selection guide and distillation explained.
Read more →
·3 min
Kimi K3 Launch: Performance Rivaling Claude at One-Third the Price, US-China AI Gap Narrows to 3 Months
Moonshot AI launches Kimi K3 reasoning model with performance rivaling Claude and OpenAI's top models at one-third the price. The US-China AI gap narrows from 6-12 months to just 3 months.
Read more →
·4 min
AI-Powered Automated Testing: Using Pytest + MCP to Tackle Non-Determinism
Deep dive into AI-era automated testing: using Pytest + Playwright + MCP for stable automation, constraining code conventions with Skills, avoiding non-determinism and high token costs. Includes real debugging war stories.
Read more →
·4 min
GPT-5.6 & OpenAI Super App Deep Dive: Loop Engineering as the New Paradigm Replacing Prompt Engineering
Deep dive into GPT-5.6 (Sol/Terra/Luna) and OpenAI's Super App: Loop Engineering, Parallel Agents, and Computer Use — unpacking the shift from prompt to loop engineering with real test cases and a startup framework.
Read more →
·7 min
OpenAI Loses Over $100 Billion a Year: How the AI Cost Paradox Is Devouring Tech Giants
Leaked financials show OpenAI's -122% operating margin — losing money on every sale. MIT research reveals 95% of enterprise AI investments yield zero returns. A deep dive into the AI cost paradox.
Read more →
·3 min
GPT-5.6 Launches, Siri Gets a Major Overhaul: Your Complete AI Industry Roundup
OpenAI launches GPT-5.6, Apple rebuilds Siri, China's AI companionship regulations take effect, Google labels AI images — your one-stop global AI industry roundup.
Read more →
·2 min
Training a CPU-Native LLM on Zero Budget: The Architectural Gamble of Ternary Quantization × Sparse MoE
An indie dev attempts to train a CPU-native LLM on $0 budget using ternary quantization, sparsity, and fine-grained MoE — with pre-registered success criteria and full public reporting.
Read more →
·2 min
Getting Started with Claude Code: AI Programming Has Entered Its Fifth Stage
Explore the five stages of AI programming evolution — from handwritten code to Claude Code and Codex enabling autonomous debugging and commits. Understand AI's limits from 0-to-1 vs 1-to-100, and what skills developers need next.
Read more →
Computer Vision Career Paths: A Guide …
·3 min
Computer Vision Career Paths: A Guide for Undergraduates
Is Computer Vision worth pursuing as a career? This guide covers CV job market realities, master's vs. industry tradeoffs, edge deployment skills, and how to transition toward multimodal AI engineering.
Read more →
Continual Learning: The Overlooked Cor…
·3 min
Continual Learning: The Overlooked Core Bottleneck on the Road to AGI
Why is Continual Learning the biggest barrier to AGI? This deep dive covers catastrophic forgetting, real-world deployment challenges, and the Amodei vs. Dwarkesh debate on AGI pathways.
Read more →
·2 min
Distributed AI Systems: A Practical Engineering Guide to Training, Inference, and Production Deployment
A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.
Read more →
·2 min
Mercor Races Toward a $20B Valuation: The Capital Logic Behind the AI Data Labeling Race
AI talent and data labeling platform Mercor is in talks for a new funding round targeting a $20B valuation, nearly doubling from $10B months earlier. A deep dive into Mercor's business model and the AI data supply chain logic.
Read more →
·4 min
The Claude Code Covert Tagging Scandal: The AI Trust Crisis Behind Alibaba's Ban
Anthropic's Claude Code is accused of covert tagging via Unicode punctuation encoding, prompting Alibaba to ban its use. A deep dive into the reverse-engineering findings, distillation allegations, and the AI-era battle over compute monopoly and developers' right to know.
Read more →
·3 min
Can MiniMax Serve as a Hermes Agent's Brain? A Complete V0.18 Evaluation
A hands-on test of MiniMax as an AI Agent brain using the Hermes V0.18 framework: fast inference, low cost, stable long tasks—but clear flaws in complex reasoning and tool calling. Learn its three strengths, three weaknesses, and best-fit workflows.
Read more →
·7 min
Breaking Down the Core Skills of an AI Application Engineer: From Beginner to Industrial-Grade Deployment
Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.
Read more →
·6 min
Spec-Driven Development in Practice: The New AI Coding Paradigm from Andrew Ng × JetBrains
Andrew Ng partners with JetBrains to launch a Spec-Driven Development course, teaching how to direct AI coding agents via spec files to boost intent fidelity and build maintainable production apps.
Read more →