Operations | Monitoring | ITSM | DevOps | Cloud

AI

Herding Llama 3.1 with Elastic and LM Studio

The latest LM Studio 0.3 update has made Elastic’s AI Assistant for Security run with an LM Studio-hosted model easier and faster. In this blog, Elastic and LM Studio teams will show you how to get started in minutes. You no longer need to set up a proxy if you work on the same network or locally on your machine.

Anthropic Partners with Datadog to Bring Trusted AI to All

At Datadog’s 2024 DASH conference, Anthropic President and Co-Founder, Daniela Amodei, announced the new Anthropic integration with Datadog’s LLM Observability. This new native integration offers joint customers robust monitoring capabilities and suite of evaluations that assess the quality and safety of LLM applications. Get real time insights into performance and usage, with full visibility into the end to end LLM trace. Enabling you to troubleshoot any issues, reduce downtime and get your Claude powered applications to market faster.

Digitate Webinar Series | Embrace the Autonomous Future: AIOps, Unified Observability & AI Insights

Welcome to Digitate’s Webinar Series, where we explore the next frontier of enterprise technology: the autonomous future. In this exclusive series, you’ll gain insights from industry experts and customers who have successfully transformed their operations with AIOps, Unified Observability, AI-powered insights, and closed-loop automation. These groundbreaking technologies are reshaping the way businesses function, enabling them to stay ahead in a fast-evolving digital landscape.

The Intersection of IT and Construction: How Technology is Revolutionizing General Contractor Workflows

The construction industry, one of the oldest in human history, is undergoing a profound transformation thanks to the integration of cutting-edge technologies. With new tools, digital platforms, and advanced software becoming indispensable in construction, general contractors are experiencing a shift in how they manage projects, collaborate with teams, and meet deadlines.

Skeptical that Voice Automation Technology Can Do Something AI and Other Technology Can't? See If You Believe After Hearing This.

Many people I’ve worked with have found on-device voice technology far faster and easier to deploy and scale as well since it typically doesn’t require the same outdated code or infrastructure as older voice technology platforms. (I’m talking specifically about the voice technology used to automate mobile workflows, not just direct picking.)

Retail Detail: How AI Leverages Real-Time Data to Unlock Revenue Potential

Real-time intelligence is no longer a nice-to-have, but necessary to attract customers and build future-proofed retail operations In the last 15 years, we’ve seen slow but significant advances in AI when it comes to retail. We can all remember when AI-powered “bots” or virtual assistants began showing up on most major retail websites to assist with consumer questions and complaints.

How to Measure Success When AI Breaks Your Metrics

We celebrate “disruptiveness” in the tech space for its potential to revolutionize industries and drive innovation, often focusing on the excitement of what's new. But true disruption doesn't just add to our toolkit; it challenges us to rethink the very foundations we've relied on, including how to measure success. Organizations use metrics like productivity, efficiency, and user satisfaction to gauge how new technologies are performing and to steer their decisions.

Boosting Telecom Efficiency and Cutting Costs with Network Automation

In today’s fast-evolving technological landscape, the telecommunications sector faces both exciting opportunities and significant challenges. With the ongoing need to build, maintain, and upgrade digital communication infrastructures, Communication Service Providers (CSPs) are under pressure to make strategic decisions that will shape the future of connectivity.

High-Performance AI Unleashed

The AI revolution is transforming enterprises faster than you can say, “sudo apt-get install skynet.” According to McKinsey, 65% of organizations now regularly use generative AI, nearly doubling from last year. However, as developers rush to integrate AI into their products, the shift from AI proof-of-concept to production can feel like trying to assemble flat-box furniture in a hurricane.

6 top incident management use cases for AI copilots

The news is filled with buzz about how companies approach AI. As a result, many organizations are trying to identify how AI can effectively support their business goals. There seem to be infinite use cases, but finding those that add the most value is often the first challenge. In the ITOps environment, generative AI copilots can effectively improve team efficiency, share knowledge, and support day-to-day tasks to deliver immediate value.