I cried the next day as the hot shower caressed my back. I did not know how not to cry. Don has resonated with me so deep, that it was cathartic. I was not sure what I was getting into when I got an invite to watch the biographical, comical…

The quest to enhance the safety of Large Language Models (LLMs) is a sophisticated interplay of technical innovation, ethical considerations, and practical applications. …

Adversarial attacks on Large Language Models (LLMs) represent a sophisticated area of concern in AI safety, requiring an intricate blend of mathematical rigor and strategic foresight. These attacks, aimed at manipulating LLMs to produce unintended outputs, range from subtle input alterations to exploiting systemic vulnerabilities. In this blog I provide…

The study of allelic expression in heterozygous loci of the human genome is a central theme in understanding the intricacies of human genetics and genomics. It unveils the complexities underlying genetic diversity, disease predisposition, and phenotypic variation. …

In the journey of parenting, one of the most profound questions we often face is: “How do we build better children?” While I don’t claim to be an expert, my experience raising two successful boys has given me some valuable insights. Particularly, I believe that from the tender age of…

Transformers, central to advancements in machine learning, leverage the self-attention mechanism for tasks across various domains, including natural language processing and computer vision. However, the underlying dynamics of these models, particularly concerning self-attention networks (SANs), present challenges like rank collapse. A recent study provides a mathematical analysis of this phenomenon…

Let me start with saying that this is one of the best evolutions I have come across ever since the inception of Transformers! Large language models (LLMs) can expand their capabilities through various scaling strategies. The more straightforward approach involves amplifying the computational resources — this is a matter of…

The field of Large Language Models (LLMs) is rapidly advancing, necessitating robust red teaming strategies to ensure their safety and reliability. In part 4, I covered “Enhancing Safety in LLMs: A Rigorous Examination of Jailbreaking” Red teaming, a method of simulating adversarial attacks to identify vulnerabilities, requires a deep understanding…

The concept of jailbreaking Large Language Models (LLMs) such as GPT-4 represents a formidable challenge within the domain of artificial intelligence. This process entails the strategic manipulation of these advanced models to operate beyond their predefined ethical guidelines or operational boundaries. In the previous blog, I covered “Mathematically Assessing Closed-LLMs…