A blog post comparing when to use regular Google search versus LLMs for research, outlining the strengths and weaknesses of each. It details scenarios where search engines excel (facts, current events, specific sources) and where LLMs shine (analysis, synthesis, creative thinking). It also lists tasks LLMs struggle with, such as complex reasoning, real-time information, and fact verification.
This blog post details an experiment testing the ability of LLMs (Gemini, ChatGPT, Perplexity) to accurately retrieve and summarize recent blog posts from a specific URL (searchresearch1.blogspot.com). The author found significant issues with hallucinations and inaccuracies, even in models claiming live web access, highlighting the unreliability of LLMs for even simple research tasks.
The article discusses the ability of AI systems to interpret images, particularly focusing on the limits and reliability of these systems in answering questions about visual content. The author, Dan Russell, challenges readers to evaluate how well AI can identify objects in provided images and what kinds of questions can be reliably answered by AI.
This blog post discusses strategies for staying up-to-date on the rapidly evolving field of AI, covering resources, tools, and techniques for tracking news, research, and developments.
Key concept: Setting mental models can help users understand how to interact with products that adapt over time. This chapter covers:
Identifying existing mental models
Onboarding in stages
Planning for co-learning
Accounting for user expectations of human-like interaction
Key concept: To build effective mental models of AI-powered products, consider what you want people to know about your product before their first use, how to explain its features, and when it will need feedback from them to improve.
Identifying existing mental models
Onboarding in stages
Planning for co-learning
Accounting for user expectations of human-like interaction
Key concept: To build effective mental models of AI-powered products, consider what you want people to know about your product before their first use, how to explain its features, and when it will need feedback from them to improve.
