Effective defense begins with understanding how attacks unfold. Here's a breakdown of common attack patterns, backed by ...

Key considerations for discovery in AI-focused intellectual property (IP) litigation, including an examination of a hypothetical patent infringement and trade secret misappropriation case on highly ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Context engineering—the art of shaping the data, metadata, and relationships that feed AI—may become the most critical ...

neural network: A computational model that resembles the human brain's structure and is meant to recognize patterns in data. Consists of interconnected nodes, or neurons, that can recognize ...

Explore the fascinating world of convolutional neural networks (CNNs) and uncover how they’ve revolutionized the field of computer vision and deep learning. Understand the building blocks of CNNs and ...

Start with the basics: get a handle on what AI is, why it matters, and how it’s used in the real world. Make a plan: figure ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Generative AI is different from older AI because it creates new things, while older AI usually just sorts or analyzes stuff.

Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow. Inspired from Andrej Karpathy's char-rnn.