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GenerativeAI took the consumer landscape by storm in 2023, reaching over a billion dollars of consumer spend 1 in record time. Over the past couple months, we’ve spoken with dozens of Fortune 500 and top enterprise leaders , 2 and surveyed 70 more, to understand how they’re using, buying, and budgeting for generativeAI.
They addressed the top concern for CISOs: the impact of generativeAI on enterprise security. Here’s what they had to say about the key considerations for technology adoption and strategies CISOs can employ to navigate the rise of AI-driven security solutions: 1. What is the biggest security threat that enterprises face today?
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The rise of foundation models and generativeAI only furthers this trend. Typical data lake storage solutions include AWS S3, Azure Data Lake Storage (ADLS), Google Cloud Storage (GCS) or Hadoop Distributed File System (HDFS). Data Lakes have been a staple for a long time, storing both structured and unstructured data.
Then we’re going to do some work together to figure out how to take those models, those platform building blocks, and get them deployed into products that Microsoft offers, like GitHub Copilot, as well as deploy these things into environments like Azure and Azure OpenAI API, where people can just build their own software on top of it.”
AI Commentary Some interesting AI commentary / stats I wanted to highlight from a couple earnings calls this week Microsoft on AI “We're excited that only 2.5 years in, our AI business is on track to surpass $10 billion of annual revenue run rate in Q2. I suspect we'll spend more on that in 2025.
In just the past few years, weve watched Software-as-a-Service evolve at breakneck speed, transforming from a neat cloud-based delivery model into an essential driver of business innovation. AI is turning SaaS from a reactive tool into a proactive business partner. (B) GenerativeAI is now embedded into SaaS tools everywhere.
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