Posts
Automated Prompt Optimization: From AutoPrompt (2020) to TextGrad (2024)
A chronological survey of automated prompt optimization 2020–2025: AutoPrompt, APE, OPRO, EvoPrompt, DSPy, TextGrad, PromptAgent, and how to choose between them.
LLM Prompt Compression: LLMLingua, GIST Tokens, and the Path to 480x Compression
A practitioner's guide to LLM prompt compression: LLMLingua, GIST Tokens, 500xCompressor, KV-cache methods, and the rate-distortion limits of compressing context.
Prompt Structuring Techniques: From Chain-of-Thought to the Instruction Hierarchy
A chronological survey of LLM prompt structuring: chain-of-thought, the instruction hierarchy, system prompt design, evaluation frameworks, and the theoretical foundations behind why prompts work.
LLM Safety Techniques: Constitutional AI, Harmony, SAIF, and Llama Guard Compared
A practitioner's survey of LLM safety techniques across OpenAI Harmony, Anthropic Constitutional AI, Google SAIF, Meta Llama Guard, and open-source RLHF frameworks.
Tackling Data Imbalance in Federated Learning
How Fed-Focal Loss addresses one of the most challenging problems in distributed machine learning: handling imbalanced data across federated clients.
The AI Copyright Challenge: Building Legal Frameworks for Generative AI
As generative AI transforms content creation, we need new frameworks that respect copyright while enabling innovation. Here's how we can build them.
The MEV Problem: Why Ethereum Needs Fairer Value Distribution
Exploring Maximal Extractable Value (MEV) in Ethereum and why we need better mechanisms for fair value distribution across the ecosystem.
DePIN: The Future of Physical Infrastructure
Why Decentralized Physical Infrastructure Networks (DePIN) represent a fundamental shift in how we build and own critical infrastructure.
Why Deepfake Detection Needs Decentralization
As deepfake technology becomes more sophisticated, centralized detection approaches are failing. Here's why we need decentralized solutions.