According to DeepLearning.AI on Twitter, the new 'Pretraining LLMs' course developed with UpstageAI highlights that while prompting or fine-tuning large language models (LLMs) is generally effective for broad language tasks, pretraining is crucial when targeting specialized domains or underrepresented languages. For AI-driven trading, this approach can enhance model accuracy in financial text analysis or crypto market sentiment when mainstream models fall short, offering a competitive edge for traders operating in niche or emerging markets (source: DeepLearning.AI, May 2, 2025).

According to DeepLearning.AI, the new 'Pretraining LLMs' course developed with Upstage highlights that while prompting or fine-tuning large language models (LLMs) is effective for general NLP tasks, pretraining is critical for building models tailored to specialized domains or underrepresented languages. This has direct trading implications for crypto projects seeking to develop proprietary AI models for blockchain analytics or DeFi platforms, where domain-specific data and terminology are not covered by mainstream LLMs. Traders and developers should note that investing in pretraining can deliver a competitive edge in crypto-focused AI applications, as verified by DeepLearning.AI's official Twitter announcement (source: @DeepLearningAI, May 2, 2025).