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PostgreSQL for AI applications

If you’re working with AI, you’re working with data. From numerical data to videos or images, regardless of your industry or use case, every AI project depends on data in some form. The question is: how can you efficiently store that data and use it when building your models? One answer is PostgreSQL, a proven and well-loved database that, thanks to recent developments, has become a strong choice to support AI.

Accelerate AIOps with Hollywood's Human-Friendly AI Insights

AI has emerged as a major inflection point in the technology industry, driving providers to rush to introduce AI-enhanced products and services. The remarkable momentum surrounding AI, fueled by its perceived value and excitement, is evident, with businesses reporting an average return on investment of 3.5 times or 250%, according to IDC. Consequently, it comes as no surprise that IDC anticipates a shift in IT spending toward AI.

Ubuntu AI | S2E2 | Edge AI at NVIDIA GTC 2024

A special episode is out to talk about NVIDIA GTC 2024. Gustavo Sanchez will give a talk about edge AI deployments to accelerate smart city development. It will focus on how cloud native infrastructure and open source tooling enable such a project. Listed to the podcast to learn more about the use cases, challenges and key considerations for such a use case. From architectural details to possible improvements, Gustavo delights us with tons of useful information.

How to Collect IoT Data Through Cribl Stream and Cribl Search

Cribl’s suite of products excel at collecting and organizing your IT and security event data. Did you know it can also help with IoT data collection and analysis? If you can get the text of the data into Cribl, in most cases, we can process it, transform it, and send it to where you want it to go. A few years ago, I bought a weather station. I immediately hooked up some home automation gear to show me the temperature, humidity, and air quality. But the geek in me wants more.

Beyond APM: What Datadog Won't Tell You with Leon Adato of Kentik

APM tools promise a unified observability platform, yet they inherently focus on internal metrics, traces, and logs. This internal focus, while valuable, misses critical dimensions of the user experience and network performance that are essential for a complete understanding of application behavior in real-world scenarios. With Kentik you can dive deep into your network performance and find problems before they affect your users.
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How to improve INP (the newest Core Web Vital)

From the first introduction of Core Web Vitals, Google has maintained that these user experience metrics will keep evolving. Since 2022, the Google team has been testing Interaction to Next Paint (INP), a new interactivity metric, and asking for feedback from the development community. Late in 2023, they announced that INP would replace FID as a Core Web Vital. The transition to INP is effective from March 2024.

AI-Assisted Network Monitoring: Real or Hype?

Networking experts Chris O'Brien and Nina Bargisen join Capacity Media's Jack Allen to explore the evolving role of AI in network monitoring. They delve into historical applications of AI and machine learning in network observability, the integration of large language models for enhanced troubleshooting, and the significance of diverse data sources. The session includes a live demonstration of the AI-assisted query features of Kentik NMS (Network Monitoring System) and highlightings the advantages of streaming telemetry over SNMP. There's also an insightful Q&A session at the end.