Large Language Models (LLMs) have revolutionized the world of Natural Language Processing (NLP) with their remarkable abilities to handle intricate and complex tasks. These models have been trained on massive datasets using immense computational power, showcasing impressive long-context capabilities. However, the key to accessing these long-context capabilities lies within proprietary…

When a human acquires the knowledge that “Olaf Scholz was the ninth Chancellor of Germany,” they can effortlessly respond to the question, “Who was the ninth Chancellor of Germany?” This seemingly simple act of generalization is a fundamental aspect of human cognition, often taken for granted. However, in a new…

The most prominent distinction between LLaMA-1 and LLaMA-2 lies in the incorporation of higher-quality corpora, a pivotal factor contributing to significant performance enhancements in LLaMA-2. This, coupled with its commercial availability, extends the potential for creative applications of large models within the open-source community. Nevertheless, it’s widely recognized that the…

Predictive models and lossless compressors have long been known to share a transformative relationship. Recently, the remarkable success of large pre-trained Transformers, often referred to as foundation models, in a diverse range of predictive tasks has positioned them as potent candidates for the role of robust compressors. In a groundbreaking…

Motion is one of the most conspicuous visual cues in the natural world, and humans possess a remarkable sensitivity to it. …

Recent developments in large-scale language models have showcased their remarkable ability to tackle a wide array of tasks using a single model. However, a significant challenge lies in comprehending their internal workings, particularly as scaling these models up also raises the bar for interpretability. In a new paper titled “Neurons…

In recent years, the rapid progress of Large Language Models (LLMs) has showcased their potential in creating autonomous agents capable of tackling complex tasks and engaging with the world, humans, and fellow agents through a profound understanding of their surroundings. However, despite this promising trajectory, the creation of such agents…

One of the intriguing puzzles within the realm of neural network generalization is a phenomenon known as “grokking.” It involves a neural network achieving perfect training accuracy but displaying poor generalization capabilities. Interestingly, it has been observed that further training can transform a network experiencing this phenomenon into one that…

Large Language Models (LLMs) have undoubtedly showcased remarkable performance in the field of natural language processing. However, beneath their accomplishments lies a profound and far-reaching impact on the economic landscape, and they have yet to fully redefine the artificial intelligence framework and even cognition itself. On the flip side, the…