TechCrunch has developed a methodology to review AI models, focusing on their general capabilities rather than elusive specifics. This includes asking about evolving news stories, seeking sources on older stories, asking trivia questions, seeking medical and mental health advice, asking controversial questions, asking for jokes, product descriptions, summarizing recent articles, and analyzing structured documents. The article emphasizes that this approach is not comprehensive but provides a more realistic evaluation than abstract benchmarks.
Key takeaways:
- AI models are too numerous, broad, and opaque, making it impossible for comprehensive evaluation. They are constantly updated and can perform a wide range of tasks, many of which their creators didn't anticipate.
- Despite the challenges, it's crucial to attempt to review AI models to provide a real-world counterweight to industry hype and to challenge the claims made by companies like Google and OpenAI.
- TechCrunch has developed a methodology for reviewing AI models, which includes asking about evolving news stories, asking for sources on older stories, asking trivia-type questions, asking for medical and mental health advice, and asking about controversial topics, among others.
- While this approach doesn't provide a comprehensive review, it offers a general sense of an AI's capabilities and can reveal important qualitative differences between models. However, the review process is constantly evolving to keep up with the fast-paced AI industry.