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How To Plan For The Unpredictability Of AI Data In 2024

Feb 22, 2024 - forbes.com
The article discusses the future of AI in 2024, emphasizing the need for companies to invest thoughtfully and aggressively in AI. It highlights the importance of considering the practicality of compute power, the cost of large language models, and security and privacy concerns. The article suggests that smaller, tightly focused AI models might be more cost-effective and secure than larger general-purpose models.

The author also provides four suggestions for companies to be ready for AI: getting their data together, vetting service providers carefully, addressing security concerns, and building incrementally with AI. The article concludes by stating that 2024 will be the year executives get serious about AI, moving beyond the hype and focusing on its practical applications.

Key takeaways:

  • Companies should consider the practicality of compute power and the expense of large language models (LLMs) in their AI strategies, with a focus on security and privacy concerns.
  • Investment in AI should be strategic and thoughtful, with a roadmap for deeper integration into the organization, while considering the impact on data volumes.
  • Enterprises need to organize and digitize their data to be consumable by AI applications, and vet AI service providers carefully.
  • Companies should start with AI incrementally, carefully monitoring for potential problems and expanding as programs prove their worth.
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