#enterprise-ai

#enterprise-ai

Organizations are focusing on efficiently and securely integrating advanced AI models at scale.

Practical strategies and real-world insights are essential for navigating AI and data engineering challenges.

The future of generative AI lies in compound AI systems that integrate multiple models and real-time data for better performance.

Mastering Large Language Models is critical for engineers in today's rapidly evolving AI landscape.

ODSC East provides expert-led sessions for both beginners and advanced users in LLM application.

Real-world development workflows and governance are key to successful LLM integration across teams.

IBM is leading in open-source AI with the release of Granite AI 3.0 models, emphasizing business applications despite common industry hesitation.

25% of AI developers have at least one enterprise AI application in production, signaling a surge in enterprise AI adoption.

SoftBank is finalizing a $40 billion investment in OpenAI, significantly increasing its valuation to $300 billion.

The next generation of generative AI will be dynamic compound AI systems that integrate various models and external knowledge for effective business solutions.

Cohere raises $500 million in funding, positioning for accelerated growth in the enterprise AI market.

AI application development is hindered by a significant skills gap and lack of effective tools, making it challenging for developers to innovate effectively.

CMOs can enhance their leadership role through strategic adoption of generative AI, connecting it directly to business outcomes.