Artificial Intelligence (AI) has made significant strides over the past few decades, tackling problems once thought to be solvable only by human intelligence. One of the areas of focus in AI research today is enabling systems to emulate human long-term memory, a critical capability that could transform industries and daily life. Unlike short-term memory, which is transient and task-specific, long-term memory allows systems to retain, recall, and build upon experiences over t

In the advancing field of artificial intelligence (AI), we're constantly discovering innovative ways to make machines learn more efficiently and effectively. One such breakthrough is the concept of self-modeling in neural networks—a technique that not only enhances the network's performance but also simplifies its internal structure. In this exploration, we'll look into the research presented in the paper " Unexpected Benefits of Self-Modeling in Neural Systems " by Vickram

The Rise and Reign of Transformers Since their introduction in 2017 by Vaswani et al. , transformers have been the cornerstone of some of the groundbreaking developments in artificial intelligence (AI). From language models like GPT-4 to vision applications like ViT (Vision Transformers), this architecture’s versatility and scalability have powered results across various domains. But as we push the boundaries of what’s possible in AI, we’re confronted with questions about its