#tokenization
183 related articles
·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
Read more →
·3 min
Claude Opus 5 Officially Released: Performance Approaching the Top Tier as the Open-Weight Debate Heats Up Again
Anthropic releases Claude Opus 5 with near-frontier performance at lower prices. Same day, Jensen Huang co-signs open-weight letter with 20+ companies while DeepSeek fundraising rumors surface.
Read more →
·3 min
Why Can't AI Draw Charts Properly? The Cognitive Blind Spots in LLM Visualization Capabilities
Top AI LLMs can write code and pass professional exams, yet can't produce an accurate chart. This article analyzes why AI fails at chart generation and reveals the uneven nature of AI intelligence.
Read more →
·3 min
AI Companies Destroying Rare Books for Training Data: The Cultural Cost Behind Efficiency
Some AI companies are buying rare antique books, using destructive scanning for training data, then destroying the originals. This raises urgent questions about AI data ethics and cultural heritage.
Read more →
·4 min
GenAI Job Interview Gone Wrong: Interviewer Googles Gemini for Questions on the Spot — What's Broken in AI Hiring?
A fresh grad interviewing for a GenAI Trainer role faced prime number coding and activation function questions while the interviewer used Gemini to generate questions live — exposing AI hiring chaos.
Read more →
·3 min
Wattage: An AI Agent Token Cost Profiling and Regression Protection Tool
Deep dive into Wattage, an AI Agent token consumption profiling and cost regression protection tool, exploring its core features, industry context, and value for developers.
Read more →
·3 min
Sub-Second Code Search: Building an Indexing Plugin with Cursor + Codex
How to achieve millisecond-level code search in massive repositories with hundreds of thousands of files? A hands-on look at building a code search plugin with Cursor + Codex, powered by Lucene inverted indexing and BM25 ranking.
Read more →
·3 min
Sub-Second Code Search: Building an Indexing Plugin with Cursor + Codex
How to achieve millisecond-level code search in a repo with hundreds of thousands of files? Building a search plugin with Cursor + Codex, powered by Lucene inverted indexing and BM25 ranking.
Read more →
Dive into LLMs: A Complete Guide to th…
·1 min
Dive into LLMs: A Complete Guide to the 44.8K-Star Hands-On LLM Tutorial
"Dive into LLMs" is a 44,830-star Chinese LLM tutorial on GitHub. Using Jupyter Notebooks, it covers Transformers, LoRA fine-tuning, RAG, and Prompt Engineering.
Read more →
·6 min
The AI Industrial Age Arrives: Compute Wars, Chip Reconstruction, and the GPT-5.6 Cheating Scandal Explained
Five key AI industry trends: Doubao surpasses 180 trillion daily calls, OpenAI's in-house AI chip, NVIDIA's $3-4 trillion compute forecast, China catching up, and the GPT-5.6 cheating scandal.
Read more →
Kronos Financial Foundation Model: Usi…
·7 min
Kronos Financial Foundation Model: Using AI to Read the Market Language of Candlesticks
Kronos is the first open-source foundation model treating candlestick data as the "language of financial markets," using an autoregressive Transformer and earning 32K GitHub Stars. A deep dive into its principles, applications, and limits.
Read more →
·5 min
Inside Cursor: How Recursive Model Improvement Enables AI to Self-Evolve
A Cursor ML engineer breaks down AI training methodology: outer/inner loop acceleration, preventing reward hacking, textual feedback, and recursive self-improvement (RSI) where models train the next generation.
Read more →
·6 min
Claude Sonnet 5 In-Depth Testing: 8 Real-World Tasks Reveal Its True Capability Boundaries
Bilibili creator KaterSony tests Claude Sonnet 5 across 8 real-world tasks—image recognition, 3D modeling, web generation—comparing it against GPT-5.5, Gemini 3.1 Pro, and revealing its true capability limits and cost traps.
Read more →
·4 min
Claude Usage Anxiety: The Hidden Cost Trap of AI Coding Tool Subscriptions
Real Reddit user rants reveal AI subscription pain points: Claude, Sol, and other tools consume usage at wildly different rates—does faster mean pricier? A deep dive into AI billing logic, usage transparency, and platform trust.
Read more →
·3 min
Qwen Next-Gen, DeepSeek V4, New GLM Spotted Simultaneously: China's LLM Race Accelerates
Qwen next-gen (KLab), DeepSeek V4 GA, and Zhipu GLM's new version are all in testing simultaneously. A deep dive into the latest developments and tech trends.
Read more →
·3 min
Claude Sonnet 5 Deep Dive: Impressive Benchmarks, Disappointing Reality — Stick with OPUS 4.8
Anthropic's Claude Sonnet 5 claims near-OPUS 4.8 performance at lower cost. Real-world tests reveal hidden tokenizer costs, weak creative output, and only 13th place on Cursor rankings.
Read more →
·2 min
Wildcards in Action: A Guide to Batch Exploration and Diversity in AI Image Generation
Wildcards are one of AI image generation's most underrated features. Learn how the randomization mechanism works, how to use ChatGPT to bulk-generate vocabulary lists, and how to build reproducible, systematic creative workflows.
Read more →
·4 min
Understanding Transformer From the Ground Up: How Language Models Predict the Next Word
From Tokenization and Embedding to the Attention mechanism, this article systematically breaks down how Transformer works — and how ChatGPT turns input text into next-token probabilities.
Read more →
Claude Usage Draining Too Fast? A Deep…
·2 min
Claude Usage Draining Too Fast? A Deep Dive into Token Billing and Usage Transparency
Users report Claude usage quotas draining faster than expected. This article explains token billing, context window accumulation, rate limits, and how to optimize your AI usage.
Read more →
·4 min
Getting Started with AI Test Development: Core Principles and Underlying Logic of Large Language Models
New to AI test development? This article breaks down the differences between machine learning and traditional programming, the origins of AI hallucinations, and the core principles of NLP/NLU/NLG to help test engineers build a solid AI knowledge framework.
Read more →