CxOs are racing to invest in generative AI but skimping on the data foundation needed to execute, according to an Ernst & Young (EY) survey.
Enterprise software could be disrupted as category windows become collateral damage to generative AI. The scenario: Today's go-to systems are relegated to plumbing as generative AI becomes the de facto user interface that democratizes data, insights, analytics and automation.
Amazon Web Services is focused on enabling generative AI throughout its platform in a bid to move projects from pilots to production. The strategy is to meet enterprises where they are with practical features including fine-tuning of large language models (LLMs), guardrails and additons to Amazon Bedrock.
Enterprises have thousands of use cases for generative AI and are now working through prioritizing them and ultimately moving to production. At AWS Summit 2024 in New York, a panel of partners and integrators talked about Amazon Q early adoption and genAI use cases with a focus on pilots to production.
Generative AI models are going to have a big training data issue as public web access becomes more restricted and it's unclear whether large language models (LLMs) will be able to avoid the garbage in, garbage out issue.
Tableau President and CEO Ryan Aytay said the company's future as part of the Salesforce product portfolio is to leverage generative AI in the future to offer "precision decisions" and a semantic layer that can democratize analytics and enable data sharing.
Google Cloud updated Vertex AI with new models, context caching, provision throughput and a bevy of grounding updates with Google Search, third party data and an experimental "grounding with high-fidelity mode."
Progress Software CEO Yogesh Gupta realizes that generative AI is going to change the way software is priced and his company is experimenting accordingly. One thing is clear: GenAI is going to upend current software pricing models especially those based on seats.
Anthropic's move to couple its Claude LLM with collaboration features is a smart one that can win out with businesses over time.
Generative AI projects in the enterprise have moved beyond the pilot stage with many use cases going into production. Scaling has been a bit of a challenge, but the maturation of how CxOs are approaching genAI is underway.
Generative AI projects are gaining steam in the enterprise, but there's a big hurry up and wait vibe to them. Why? Enterprises operate on a continuum and don't have their ERP, cloud and data transformations complete.
Anthropic launched Claude 3.5 Sonnet, its latest large language model (LLM), with availability on Anthropic API, Amazon Bedrock and Google Cloud Vertex AI.
