Category: Science & Research

Tamara Weed, Jun, 17 2026

Explore how Query, Key, and Value projections work in LLM attention mechanisms. Understand what these matrices learn during training and how they enable context-aware processing in transformer models.

Tamara Weed, May, 27 2026

Explore how to fix overconfident AI. Learn about token probability calibration, Full-ECE metrics, and practical techniques like temperature scaling to ensure your LLM's confidence matches its accuracy.

Tamara Weed, May, 25 2026

A technical walkthrough of Transformer architecture, explaining self-attention, multi-head mechanisms, and how LLMs process and generate text efficiently.

Tamara Weed, May, 21 2026

Explore the differences between sinusoidal and learned positional encoding in Transformers. Learn why modern LLMs favor RoPE and ALiBi for better long-context performance.

Tamara Weed, May, 20 2026

Explore the technical evolution of Generative AI, from early Markov chains and LSTMs to the transformer revolution. Understand the architectural shifts, key milestones, and future challenges shaping modern AI systems.

Tamara Weed, May, 14 2026

Explore the critical copyright risks of multimodal generative AI in 2026. Learn why AI images, music, and videos lack protection in the US, how training data lawsuits threaten creators, and strategies to mitigate legal exposure.

Tamara Weed, May, 12 2026

Explore how Generative AI transforms life sciences research through de novo protein design and automated literature reviews. Learn about tools like BoltzGen and RFdiffusion3.

Tamara Weed, Apr, 20 2026

Explore how Multimodal Large Language Models (LAMs) are revolutionizing audio understanding, from spectrogram processing to real-time voice reasoning.

Tamara Weed, Apr, 15 2026

Explore the core pretraining objectives of Generative AI: Masked Modeling, Next-Token Prediction, and Denoising. Learn how they power BERT, GPT, and Stable Diffusion.

Tamara Weed, Apr, 10 2026

Explore the hidden environmental costs of Generative AI, from massive energy demands and water cooling to carbon emissions and electronic waste.

Tamara Weed, Apr, 1 2026

Exploring emergent capabilities in Generative AI: definition, examples like chain-of-thought, the 'mirage' debate, and safety implications for 2026.

Tamara Weed, Mar, 31 2026

Explore how layer dropping and early exit techniques accelerate Large Language Model inference, reducing latency and costs without sacrificing accuracy.