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.

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.

Elasticsearch® has been used by developers to build search experiences for over a decade. At Microsoft Build this year, we announced the launch of Elasticsearch Relevance Engine™ — a set of tools to enable developers to build AI-powered search applications. With generative AI, large language models (LLMs), and vector search capabilities gaining mindshare, we are delighted to expand our range of tools and enable our customers in building the next generation of search apps.

In the blog “How Generative AI Can Benefit Knowledge Management”, we looked at the benefits of AI to knowledge management to enhance the quality, automating the creation of content and enabling more engaging content. In enabling generative AI to become part of the knowledge management framework introduces concerns about accuracy, data bias, privacy and security. Now, it’s time to look at how we can make it work well together...