Wildlife imaging shows that AI models aren't as smart as we think

Using AI to identify wildlife reveals a potential "transferability crisis," researchers say. Marketing for AI imaging systems often suggests that models can easily tackle novel scenarios across ...
cryptopolitan

Tesla’s AI team creates a patent that addresses AI “drift” in positional encoding

Tesla’s AI team has created a patent for a power-sipping 8-bit hardware that normally handles only simple, rounded numbers to perform elite 32-bit rotations. Tesla slashes the compute power budget to ...
Hosted on MSN

Positional encoding in transformers explained clearly

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
GitHub

Vision Transformer (ViT) for Image Classification

This project implements Vision Transformer (ViT) for image classification. Unlike CNNs, ViT splits images into patches and processes them as sequences using transformer architecture. It includes patch ...
GitHub

FEG: A New Geometric Positional Encoding for Long-Context Models

Instead of using RoPE’s low-dimensional limited rotations or ALiBi’s 1D linear bias, FEG builds position encoding on a higher-dimensional geometric structure. The idea is simple at a high level: Treat ...
IEEE

SPGFormer: Structure Perception Graph Transformer with Laplacian Position Encoding for Hyperspectral Image Classification

Abstract: With the integration of graph structure representation and self-attention mechanism, graph Transformer demonstrates remarkable effectiveness in hyperspectral image (HSI) classification by ...