As general manager of the Oakland Athletics, Billy Beane applied statistical analysis (also known as sabermetrics) to the evaluation of baseball players, which enabled the team to excel in the 2020 season. Beane was the subject of Michael Lewis’s book “Moneyball,” which was made into a movie starring Brad Pitt as Beane.

It’s no surprise that AI is rapidly becoming the most powerful tool for developers. The ease of use and accuracy of such tools can even generate code snippets for a website written entirely on a napkin! While the potential of AI is exciting, it is crucial to address the potential vulnerabilities that bad actors can exploit within AI systems.

Bitcoin and Coinbase have been in some hot water lately. How they handle cryptocurrency might not be legal or safe. The lack of regulations is causing concern from the government about potential criminal activity, fraud, and money laundering. The good news? Rules are being implemented for crypto exchanges to stop corrupt events from happening. Regulations like Know Your Customer (KYC) are an absolute must for exchanges to keep operating legally.

Amid an AI boom and developing research, machine learning (ML) models such as OpenAI’s ChatGPT and Midjourney’s generative text-to-image model have radically shifted the natural language processing (NLP) and image processing landscape. Due to this new and powerful technology, developing and deploying ML models has quickly become the new frontier for software development.

In this post I will introduce sysgrok, a research prototype in which we are investigating how large language models (LLMs), like OpenAI's GPT models, can be applied to problems in the domains of performance optimization, root cause analysis, and systems engineering. You can find it on GitHub.