We are pleased to share a sneak peek of Query Assistant, our latest innovation that bridges the world of declarative querying with Generative AI. Leveraging our large language models (LLMs), Coralogix’s Query Assistant translates your natural language request for insights into data queries. This delivers deep visibility into all your data for everyone in your organization.
We had the opening keynote by Adam Selipsky. If you missed the live stream, you can watch it on YouTube here. Unsurprisingly, so much of the keynote was about AI.
For modern enterprises aiming to innovate faster, gain efficiency, and mitigate the risk of failure, operational resilience has become a key competitive differentiator. But growing complexity, noisy systems, and siloed infrastructure have created fragility in today’s IT operations, making the task of building resilient operations increasingly challenging.
Does this sound familiar? The incident has just been resolved and management is putting on a lot of pressure. They want to understand what happened and why. Now. They want to make sure customers and internal stakeholders get updated about what happened and how it was resolved. ASAP. But putting together all the needed information about the why, how, when, and who, can take weeks. Still, people are calling and writing. Nonstop.
Ever since we launched Query Assistant last June, we’ve learned a lot about working with—and improving—Large Language Models (LLMs) in production with Honeycomb. Today, we’re sharing those techniques so that you can use them to achieve better outputs from your own LLM applications. The techniques in this blog are a new Honeycomb use case. You can use them today. For free. With Honeycomb.
In today's dynamic world of technology and innovation, building products that resonate with customers and stand the test of time is no easy feat. At Almaden, we've cultivated a unique, Customer-Centric Product Design, approach to product development that prioritizes the customer's perspective over mere technological prowess. In this blog post, we'll delve into the core principles that drive our product development process, emphasizing the importance of understanding objectives, agile methodologies, and the modern tools we use to bring our ideas to life.
This tutorial guides you on how to use the Amazon SageMaker Orb to orchestrate model deployment to endpoints across different environments. It also shows how to use the CircleCI platform to monitor and manage promotions and rollbacks. It will use an example project repository to walk you through every step, from training a new model package version to deploying your model across multiple environments.
Top tips is a weekly column where we highlight what’s trending in the tech world today and list out ways to explore these trends. This week, we’re examining four use cases for AI in the ever-growing FinTech sector. The FinTech sector has transformed the discussion around the financial services industry from top to bottom.
