As enterprise AI adoption accelerates, it is essential to understand how the latest advancements in software and computing impact performance and scalability. In this episode of AMD Meet The Experts, Seekr President and CTO Rob Clark shared valuable and practical insights on building and running trusted generative AI applications. Discover how Seekr and AMD are transforming industries and shaping the future of AI by watching the webinar or reviewing the key takeaways below.
Key takeaways
1. High memory and bandwidth are key for generative AI success
Efficient generative AI systems rely on high memory and bandwidth to deliver accurate, fast, and scalable solutions. Training large AI models requires vast amounts of memory and bandwidth to manage the complex data involved. This means moving large datasets like model weights, gradients, and optimizer states quickly and accurately to improve the model’s learning process. Inference benefits from high memory, enabling faster responses and better throughput. For users, this translates into faster responses and more seamless experiences.
2. Building trust and accuracy in AI models requires more than just retrieval
Traditional AI approaches often focus on retrieval-augmented generation (RAG) approaches, which rely heavily on pulling and summarizing data from databases. Seekr takes this further by building solutions that emphasize reasoning and understanding. This shift is powered by advanced computing capabilities that enable deeper analysis, context comprehension, and richer explainability. As we shift the focus on reasoning-driven AI, enterprises can better trust and understand their AI outputs, ensuring accuracy and credibility in every application. This approach enables users to move beyond surface-level insights to achieve meaningful, actionable outcomes.
3. AI solutions need to be tailored to specific industries
Industry-specific models deliver solutions that address the unique challenges of different verticals. Unlike generic AI solutions, these specialized models provide deeper insights and higher accuracy by focusing on the nuances of each industry. SeekrFlow™ uses an agentic data generation workflow to ingest, structure, and process relevant documents, ensuring that critical facts, rules, and styles are captured. Through recursive prompting, the AI platform distills this information into a fine-tuning dataset that helps the model understand and apply an organization’s specific tone, language, and requirements. Whether for healthcare, finance, or legal industries, this process allows SeekrFlow to deliver tailored AI models that go beyond surface-level knowledge.
Start building trusted AI applications with SeekrFlow
The SeekrFlow AI platform was recently recognized alongside AI industry leaders in GAI Insights’ Q4 2024 Corporate Buyers’ Guide to Enterprise Intelligence Applications.
If you’re interested in learning more about how SeekrFlow can transform your AI development, book a consultation with a product expert to get started today.
