Thoughts on AI, security, LLMs, and more.
AI has compressed the cost of building software and the cost of copying it. The durable edge is no longer just code quality, but how fast an organization can ship, learn, and adapt on top of the right architecture.
Read post →As anyone in tech, I constantly get bombarded with countless papers, links, and resources to read. I dedicate Fridays to tackling this "technical debt" by reading through as much as possible.
Read post →This paper is one of the important foundational papers from OpenAI, published in 2020. GPT-3 demonstrates that LLMs pretrained with large volume of data can learn very quickly with few examples, possibly cutting the need for fine-tuning.
Read post →This is a recent paper from Google Research and DeepMind that introduces Med-PaLM, a Large Language Model tailored to answer questions about the clinical (medical) domain, achieving SOTA results on various domain specific datasets.
Read post →You probably heard the buzz around "metaverse". Regardless of which side of the argument you are in, in this article, I discuss metaverse security — from infrastructure to identity to data privacy.
Read post →This paper proposes a methodology to use side channel information (electromagnetic signals) to identify malware activity, type, and identity, even in the presence of obfuscation. A paper from ACSAC 2021.
Read post →Risk management is a fundamental part of Cloud Service Management. This post explains how an AI-based approach can standardize different domains to quantify risk using NLP, applied in IBM Cloud Pak for Multicloud Management.
Read post →A disclosure: I am not an avid blogger, however, I do read and write quite a lot and always willing to become an avid blogger.
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