@Phoenixyin13: This kind of assessment method where students create questions that stump AI is indeed very innovative and highly forward-looking. Students need to explore the strengths and weaknesses of the three models: Claude, DeepSeek, and MiniMax. In this process, students no longer blindly trust AI outputs but learn to review AI responses with a critical and discerning eye, which...
Summary
This educational assessment method encourages students to explore the strengths and weaknesses of Claude, DeepSeek, and MiniMax, creating questions that defeat AI, thereby cultivating critical thinking and competitiveness needed in the AI era.
View Cached Full Text
Cached at: 07/01/26, 01:57 AM
This kind of student-generated challenge that stumps AI is indeed a novel and highly forward-looking assessment approach.
Students need to explore the strengths and weaknesses of three models: Claude, DeepSeek, and MiniMax. In this process, students no longer blindly trust AI outputs—they learn to review and verify AI responses with a critical eye. This is precisely the kind of competitive edge that is rare in the AI era.
In the future of education, the focus will no longer be on who possesses more known knowledge. https://t.co/vibnigJMVs
Similar Articles
@akokoi1: The first skill of this AI teaching tool, "3D Geometry Problem Solving," has been released, supporting text-based problem solving, image-based problem solving, and random question generation. After testing mainstream models, deepseek-v4-pro offers the best cost-performance ratio at 0.2-0.3 yuan per question, with accuracy on some questions even surpassing GPT5.5.
The first skill of the AI teaching tool, "3D Geometry Problem Solving," has been released, supporting text-based problem solving, image-based problem solving, and random question generation. Tests show that deepseek-v4-pro offers high cost-performance, with accuracy on some questions even surpassing GPT5.5.
@FudanUniversity: Final exam at Fudan: students don't answer questions. They write them — to stump AI. 51 students, 10 questions each, 3 …
Fudan University held a novel final exam where 51 students each wrote 10 questions designed to stump three AI models (Claude, DeepSeek, MiniMax), with grades based on how difficult the questions were for the AI.
@Aoyi21: https://x.com/Aoyi21/status/2064975015200829457
This article proposes that the most cost-effective way to learn AI is to deconstruct others' Skills. By analyzing their task definitions, trigger conditions, operation steps, prohibitions, and acceptance criteria, you can learn how experts think and train AI, rather than just using tools.
@ba_niu80557: https://x.com/ba_niu80557/status/2068751230667755859
The article explores how increasingly powerful AI models eliminate those whose skills can be encoded into prompts, emphasizing that the truly irreplaceable value lies in tacit knowledge, physical-world operations, and interpersonal trust. Through the example of a friend transitioning from a consultant to a hardware integrator, the author illustrates how proactively yielding to AI-replaceable tasks while deepening expertise in areas beyond AI's reach is key to surviving and thriving in the technological wave.
@Phoenixyin13: Incredible! This Red Queen Gödel Machine from NVIDIA, Cambridge University, and other teams is absolutely one of the most important AI papers I've seen recently. This time, the paper directly targets the core bottleneck of self-improving AI: previously, once the evaluator was fixed, it led to agents gaming the system or quickly stagnating...
The Red Queen Gödel Machine paper from NVIDIA, Cambridge University, and other teams solves the bottleneck of recursive self-improvement by co-evolving agents and evaluators. It surpasses existing SOTA on tasks like code and paper writing, providing an important methodology for controlled open-ended AI evolution.