Enterprises across industries are experiencing a seismic shift as they gear up to embrace Large Language Models (LLMs). Their extensive adoption has opened a new set of opportunities for professionals and enterprises enabling them to enhance decision-making, undertake a digital transformation, and drive innovation like never before.
In a keynote at AI.Dev, Robert Nishihara (CEO, Anyscale) described the shift: A year ago, the people working with ML models were ML experts. Now, they’re developers. A year ago, the process was to experiment with building a model, then put a product on top of it. Now, it’s ship a product, find the market fit, then create customized models. The general-purpose generative AI models available to all of us today (such as ChatGPT) change the way work is done.
Recently, InfluxData CEO Evan Kaplan sat down with Developer Advocate Jay Clifford to discuss the role of time series data and AI in industry, how it’s evolving, and specifically, the role of time series data in AI. They also discussed the future of InfluxDB in terms of real-time analytics and its role in the AI landscape.
Audit finds that there are 1,200+ government AI use cases in development and in use today.
The European Union’s new legislation is the first of its kind — and has global reach On December 8, 2023, the European Union made a significant step in digital governance by introducing the first set of comprehensive artificial intelligence (AI) regulations. This legislation, poised for a European Parliament vote by early 2024, is first out of the gate in regulating AI.
Gartner’s IT Infrastructure, Operations & Cloud Strategies Conference (IOCS) is an annual event that attracts ITOps, SRE, and DevOps leaders from around the world. As Gartner explains, IOCS “brings the world’s technology leaders together to hear top trends, find objective answers, and explore topic coverage in addition to best practices. Gain the insights and guidance to create an effective pathway to the future and network with your peers.”
In this webinar hosted by InfluxDB and HiveMQ, we focus on how you can create value for your business using new tools in the AI and database ecosystem to quickly deploy AI models to perform tasks like anomaly detection. The webinar starts with a high-level overview of how MQTT and time series data can be valuable in an industrial IoT environment.
Did you miss our latest roundtable on AI-driven FinOps? Don’t worry, we got you! In this recap, we’ll review what our FinOps experts discussed and the key takeaways from the roundtable discussion. Not much of a reader? Watch it on demand!
Despite the siren song of AI in the keynotes, visitors were far more focused on solving real-world problems. These are the issues that have plagued IT practitioners for years, if not decades: troubleshooting and validating performance and availability of their applications, services, and infrastructure.
Large Language Models (LLMs) are advanced artificial intelligence models designed to comprehend and generate human-like language. With millions or even billions of [parameters, these models, like GPT-3, excel in natural language processing, understanding context, and generating coherent and contextually relevant text across various applications.
Who could have predicted that 2023 would see such a huge leap forward in Artificial Intelligence (AI)? That this was going to be the year industries decided that, this is the decade, we would solve AI. From the earliest research as far back as the 1940s, we’ve all been holding our breath, wondering when AI will live up to the expectations painted by science fiction writers and futurists. With the arrival of ChatGPT from OpenAI, we’ve been catapulted into the next generation.
IT automation delivers plenty of excitement for the financial services industry, with its power to make AI even more intelligent, as AI plays a part in today’s automation journeys.
Last week, I attended the Amazon Web Services (AWS) re:Invent conference in Las Vegas, NV, with 50,000+ others. It was quite a busy week with several keynotes, announcements, and many sessions. While the hot topic at re:Invent was generative AI, I’ll focus my blog post on a few customer sessions I attended around observability: Stripe, Capital One, and McDonald’s.
Cloud-native developers and practitioners gathered from around the world to learn, collaborate, and network at KubeCon/CloudNativeCon North America 2023 between November 6th and 9th at McCormick Place in Chicago, IL—myself included. This wasn’t my first time attending—I’ve been coming to KubeCon since 2016—but it was easily one of the most exciting experiences I’ve had as part of the Cloud Native community.
Gartner recently held their annual IT Symposium/Xpo in Orlando and Barcelona, respectively. We attended both events, a jam-packed four days of learning, dynamic conversations, and innovative sessions. It was great showcasing our latest capabilities, reconnecting with our clients, and witnessing first-hand the demand for Internet resilience within the broader community.
Your device pings, signaling another tech alert. Before you can address it, two more chime in. We all know the feeling. In today’s digital world, it’s easy to feel overwhelmed by the sheer number of notifications we receive. But what if there was a smarter way to handle them?
Recently, I sat down with Adelaide O’Brien, research vice president at IDC Government Insights, to discuss the current and future state of generative AI in the public sector worldwide. The full conversation is available to view on demand, but I also wanted to highlight some of the takeaways from the discussion.
