Forbes November 15, 2024
By Gary Drenik, Forbes Contributor covering AI, analytics, and innovation
Artificial Intelligence (AI) stands at a pivotal juncture, facing a critical decision: continue down the path of large-scale data accumulation with its inherent challenges, or embrace more focused, high-quality data sources to achieve meaningful outcomes. This decision is underscored by the high failure rates of AI projects, with some estimates indicating that over 80% of AI initiatives do not succeed.
Challenges in AI Data Quality and Large Language Models (LLMs)
AI systems, particularly those utilizing Large Language Models (LLMs), encounter significant obstacles related to data quality and reasoning capabilities:
- Data Quality Issues: High-quality data is crucial for AI models to deliver accurate and reliable outcomes. Poor data quality can...
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