Generative AI is a powerful tool for rapidly creating and iterating on content of all kinds.
The sheer breadth of data that telecommunications providers collect day-to-day is a huge advantage for the industry. Yet, many providers have been slower to adapt to a data-driven, hyperconnected world even as their services — including streaming, mobile payments and applications such as video conferencing — have driven innovation in nearly every other industry. The speed with which generative AI will change how we work, live, communicate and entertain ourselves is nearly unfathomable.
A catastrophe hazard is a severe and widespread event that causes significant damage and financial loss. These events are frequently natural disasters or large-scale human-made incidents that affect expansive and contemporary claims. Catastrophe hazards pose substantial trouble to insurers, as they can lead to a high volume of claims within a short period, potentially impacting insurance companies’ financial stability.
If 2023 was the year we woke up to how generative AI would change our world, 2024 is the year we realize the change. The real-time AI-driven enterprise may not be pixel-perfect yet, but we’re well on the way. Gen AI has a knock-on effect on all the trends and challenges we will see in 2024. Here’s our take.
For the next interview in our series speaking to tech founders from around the world, we’ve welcomed Seung Oh, Co-Founder and CEO of Data B, the company behind Engram, the first AI-powered writing platform designed for non-native English speakers.
Artificial intelligence is changing the world. With use cases ranging from content generation to deep data analysis to detecting health issues, AI can greatly improve lives and enhance business outcomes. And with the explosion of generative AI services and large language models, we can expect AI to become even more ubiquitous than it already is. But AI isn’t perfect. In particular, AI privacy issues put organizations at risk or prevent adoption in the first place.
Snowflake account managers need their fingers on the pulse of which workload shifts or performance optimizations could improve customer experience. Yet without an all-encompassing view of their customers, sales teams have to piece together customers’ wants and needs through duplicate CRM accounts and various BI tools and dashboards.
AI automation is changing the game in business operations. For many companies, global competition is heating up fast on an increasingly crowded playing field. In the past, business leaders knew their competitors and how they operated. But now, executives across industries have to look over their shoulders for new challengers that arrive with surprising speed from virtually any corner of the globe.
As an industry built on data, financial services has always been an early adopter of AI technologies. In a recent industry survey, 46% of respondents said AI has improved customer experience, 35% said it has created operational efficiencies, and 20% said it has reduced total cost of ownership. Now, generative AI (gen AI) has supercharged its importance and organizations have begun heavily investing in this technology.
With the integration of BigQuery and Document AI, you can extract insights from document data and build new large language model (LLM) applications.
Vertex AI transcription models in BigQuery let you transcribe speech files and combine them with structured data to build analytics and AI use cases.
Businesses are in a persistent productivity slump that could last through 2030, according to a 2023 World Bank study. The tech boom that powered innovation and growth over the last three decades is fading. Many companies are counting on artificial intelligence (AI) to boost operational efficiency and counteract these alarming trends.
Artificial intelligence based APIs are reshaping traditional subscription models thanks to their unique monetization frameworks. These API products enable companies seeking tailored solutions in automation and AI workflows, departing from one-size-fits-all UI approaches and embracing a highly customizable experience. Originally designed for internal platforms, APIs built with AI are now evolving into revenue gateways, transforming them into strategic assets contributing directly to company revenue.
2023 was a breakout year for artificial intelligence. It dominated news headlines as well as LinkedIn feeds. But its impact goes beyond the professional—I often overhear conversations at coffee shops about AI from people who aren’t knee-deep in the field. Whoever you are, AI is likely having a transformative impact on your life.
Traditional AI models typically specialize in processing a specific type of user prompt, whether image- or text-based. However, a paradigm shift is underway with the emergence of a new generation of AI models known as "multimodal" systems. Unlike their predecessors, these advanced models can process a diverse range of inputs seamlessly. They can adeptly handle various media types, such as text, images, audio, video, and even code.
How generative AI brings radical new capabilities to the world of AI and machine learning.
The foundation of any successful AI initiative is a well-integrated and meticulously managed data platform.
The business landscape is undergoing radical change across industries, driven by artificial intelligence (AI) and automation. This article will differentiate AI and automation, debunk misconceptions, and highlight what business leaders need to know to navigate the challenges of integrating AI and automation across the value chain. So what’s the difference between AI and automation? AI and automation have distinct purposes.
