Generative AI is a branch of artificial intelligence that can create new content, such as images, text, music, and code, based on existing data and models. It has been hailed as a game-changer for various industries and applications, from entertainment and education to healthcare and cybersecurity. But how will generative AI affect the cloud computing market, where the three dominant players, Amazon Web Services, Microsoft Azure, and Google Cloud, are competing for supremacy?
Supercloud 5: The Battle for AI Supremacy
To explore this question and more, SiliconANGLE and theCUBE, the live streaming studio of SiliconANGLE Media, are hosting a free editorial event called Supercloud 5: The Battle for AI Supremacy, from Nov. 27 to Dec. 1. The event will feature recorded and live interviews and analysis with top leaders from major industry players, as well as on-the-ground coverage from AWS’ annual user conference. This will be the fifth in SiliconANGLE’s Supercloud event series, which has featured tech leaders from Walmart, Saks, Western Union, Google, Cisco, Snowflake, Databricks, Cloudflare, CrowdStrike, VMware, Greylock Partners and many others on cloud data and cybersecurity.
The event will take a closer look at the explosive new world of generative AI and its impact on the major cloud titans. Find out all you need to know about SiliconANGLE and theCUBE’s Supercloud event series at supercloud.world.
Generative AI: A new driver for cloud growth
According to a recent report by Evercore ISI analyst Mark Mahaney, generative AI workloads could drive more cloud computing usage in the next 12 to 18 months. He said that AI could unlock new potential cloud workflows and help re-accelerate cloud demand. He also noted that AI will start to drive greater revenue to cloud as IT spending on innovation projects resumes and ramps.
However, there is also uncertainty around how generative AI will impact the major cloud providers. Among the top three, only Microsoft has commented publicly on the financial impact, indicating in its most recent earnings report that much of the growth for its Azure’s cloud platform in the past quarter could be attributed to the firm’s investments in AI. AWS parent company Amazon Inc. and Google Cloud’s Alphabet Inc. did not offer income specifics about the impact of AI on its cloud businesses in its most recent reports.
A central question surrounds where in the enterprise AI work will be performed. Will it be on public or private infrastructure? Survey data provided to SiliconANGLE by its research partner Enterprise Technology Research offers a few insights.
Generative AI: A challenge for cloud security and governance
One of the challenges in the gen AI space is transitioning from flashy demos to production-ready, scalable applications. This involves several aspects, such as security and data governance, cost and reliability, according to Ori Goshen, co-founder and co-chief executive officer at AI21 Labs Ltd., a company that develops generative AI models and products.
Goshen said that the issue of security and data governance is especially important, as generative AI models can potentially expose sensitive data that is used to train or customize them. He also said that the cost of running generative AI models on the cloud can be prohibitive for some use cases, and that the reliability and robustness of the models can vary depending on the quality and quantity of the data.
Therefore, he suggested that enterprises should carefully evaluate the trade-offs between using public cloud services or building their own private infrastructure for generative AI workloads. He also said that enterprises should look for generative AI solutions that are tailored to their specific needs and domains, rather than relying on generic models that may not deliver the desired results.
Generative AI: A catalyst for cloud innovation and transformation
Despite the challenges, generative AI also offers tremendous opportunities for cloud innovation and transformation. Generative AI can enable new forms of creativity and productivity, as well as new ways of solving problems and generating value. For example, generative AI can help create realistic and engaging content for entertainment and education, such as images, videos, music, and stories. It can also help generate code, design, and data for software development and engineering. It can also help synthesize and analyze information for healthcare and cybersecurity, such as medical reports, diagnoses, and threat detection.
Generative AI can also transform traditional industries and scale for nontech sectors, such as retail, manufacturing, and finance. For instance, generative AI can help create personalized and customized products and services, such as fashion, jewelry, and insurance. It can also help optimize and automate processes and operations, such as supply chain, inventory, and pricing. It can also help enhance and augment human capabilities and experiences, such as communication, collaboration, and learning.
Generative AI is not only a powerful tool, but also a paradigm shift, that can reshape the cloud computing landscape and beyond. As the cloud titans battle for AI supremacy, they will also have to contend with the opportunities and challenges that generative AI brings. The outcome of this battle will have profound implications for the future of technology and society.
