How to Use Generative AI, Part 7: Iterate
Iterate by critiquing, interacting, and iterating to improve outpus. Part 7 in our How to Use Generative AI series.
The Future of (Generative AI) Search
Explore the future of search with generative AI. Discover how Apple Intelligence, context-based understanding, intent-driven interactions, and integrated workflows are transforming search. Learn about the trust challenges and the critical balance needed for reliable, AI-powered search experiences.
The Synergy of Human Creativity and AI
Discover how human creativity and AI collaborate in the face of advancements. Explore the unique qualities of human flexibility, diverse responses, and AI's ability to overcome creative blocks. Learn how architecture, analogical reasoning, and rap benefit from AI's divergent thinking capabilities.
The ARC Prize and What it Means for AGI
Explore the debate on achieving AGI: scaling laws vs new approaches. Learn about the ARC prize, a $1M competition challenging the current consensus and proposing a benchmark focused on skill acquisition. Discover why benchmarks matter in shaping AI's future and driving industry perceptions.
Is AI Really as Creative as Humans?
Recent studies claim AI outperforms humans in creativity tests, but these only measure "creative potential." Examples show AI ideas often lack practicality and appeal. The future of AI-enhanced creativity lies in designing tools that allow for exploration, playfulness, and guidance.
Decoding the Complexity of Innovation with AI
AI and network analysis reveal innovation's complex structure, manage creative tensions, and amplify human potential by uncovering patterns in invention data. AI guides the process, but human intuition remains crucial in navigating the unequal market of ideas.
Jonathan Feinstein: The Context of Creativity
An interview with Jonathan Feinstein, professor at the Yale School of Management and author of Creativity in Large-Scale Contexts: Guiding Creative Engagement and Exploration.
AGI Needs a New Name
The current obsession with AGI, fueled by the hype from companies like OpenAI, is a dangerous distraction we must firmly reject. Don't fall for the red herring argument that we need superintelligent AI to save us from ourselves. It's an insult to human intelligence and agency.
The Brittleness of Agentic Reasoning and Planning Using LLMs
Research suggests that LLMs are not demonstrating genuine reasoning abilities but are instead relying on pattern matching and retrieval based on the provided examples. We're still a ways off reliable performance of LLMs in reasoning and decision-making tasks.
Can LLMs reason and plan?
LLMs are great at coming up with approximate knowledge and ideas for potential plans. But to actually use those ideas, you need to pair the LLM with external programs that can rigorously check the plans for errors. The key is to use them as part of a bigger system.
How to Use Generative AI, Part 6: Create
Create by mixing modes, varying both inputs and outputs, and perspectives. Part 6 in our How to Use Generative AI series.
Graph RAG: Querying Enterprise Data with LLMs
Graph RAG doesn't necessarily replace knowledge graphs but can serve as a complementary tool, especially in scenarios where rapid, scalable, and dynamic summarization of large unstructured datasets is required.