Red Hat AI to fuel innovation
Generative AI (GenAI) has changed the game in terms of new products and service offerings, improved customer experiences, and accelerating efficiency and productivity, but the technology is changing rapidly. Enterprise organizations of every size are under pressure to identify, choose, build, and deliver these AI solutions. They need ready-to-use solutions that provide a quick ramp up and allow scaling at their own pace without making large investments or having a strong AI knowledge base. The key challenges that they face include: - Option fatigue. They are met with too many options and approaches for getting started with their AI projects. - Budget, hardware, and data requirements. There is no one-answer-fits-all solution. Both predictive and generative AI models require large data sets, skilled personnel, and specialty hardware and deciding where to train or deploy models can affect budget, hardware accessibility, and data concerns. - Scale across the model and application lifecycle.. Once models are ready to be incorporated into existing and new applications, then a new set of challenges arises such as: scalability, resource management (storage and hardware), lifecycle management, and monitoring. As more and more applications are modernized with AI, enterprise organizations will need to consider the impact on IT operations and the effort it takes to manage and automate the lifecycle of both models and applications.
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Jennifer Vargas | Senior Principal Product Marketing Manager, AI Business Unit, Red Hat
Jennifer is a product marketer helping organizations navigate their transition to the cloud and adoption of AI initiatives. During the last 5 years, she has been working on a variety of emerging technologies by developing product strategies, launching new products, andtesting new initiatives in nascent market segments. She enjoys solving business and technicalchallenges that appear disconnected. Her passion towards software led her to change industries from oil and gas to information technology. Prior to joining Red Hat, Jennifer worked as a strategist consultant and technical sales lead providing customers with proven solutions for complex scenarios in the utility, telco and insurance industries.