When Your AI Transcription Turns "Tasty Burger" Into "Nasty Murder"
WER vs SNR for Transcription Models
Sameer Gupta
Tracing the Thoughts of Claude: Peering into an AI’s Mind
Introduction
Large language models like Anthropic’s Claude have achieved feats once reserved for science fiction, such as multilingual translation, creative writing, and complex reasoning. Yet their inner workings remain largely mysterious, resembling “black boxes” that produce results we cannot fully explain. What if we could see how Claude processes
Can Your AI Explain Why It’s Moral?
Large‑language models (LLMs) already draft contracts, triage medical claims, and screen résumés. Every one of those tasks is laced with ethical choices, yet most benchmarks still judge models on math puzzles or multiple‑choice trivia. The authors of the paper “Auditing the Ethical Logic of Generative AI Models” step
Skipping the "Thinking": How Simple Prompts Can Outperform Complex Reasoning in AI
Introduction
In the realm of AI, especially with large language models, the prevailing belief is that complex reasoning tasks require detailed, step-by-step "thinking" processes. These processes often involve generating extensive intermediate steps before arriving at a solution, consuming significant computational resources.
However, the paper titled "Reasoning Models
Mastering the Art of Prompt Engineering: A Practical Guide for Better AI Outcomes
Prompt engineering might just be one of the most accessible yet impactful skills in artificial intelligence today. At its core, prompt engineering involves crafting specific inputs that guide Large Language Models (LLMs) to produce precise and accurate outputs, essential for ensuring AI quality. You don't have to be
APIGen-MT: Structured Multi-Turn Data via Simulation
Intro: Why this matters
Picture this: You’re building an AI agent to help users book travel, troubleshoot software, or manage finances. One task leads to another. The user changes their mind halfway. New context unfolds mid-conversation. How do you train your AI to navigate all of that without losing
CoTools and the Future of LLM Tool Use for Complex Reasoning
Imagine asking an AI, “What’s the best route to work tomorrow morning?” and receiving a response that not only understands your intent but actually checks live traffic data via an external API and gives you the optimal route.
This isn’t a future concept. It’s happening right now—