गाइड से जुड़ी प्रश्नोत्तरी · कठिन स्तर
एआई मिथक प्रश्नोत्तरी
धाराप्रवाह उत्तरों, डेटा और मॉडल-आकार की धारणाओं, डेमो, बेंचमार्क, स्वचालन जिम्मेदारी और दायरे के पीछे साक्ष्य का परीक्षण करता है।
प्रश्न 1 का 8
A model answers fluently and names a source. What should a reader still check?
प्रत्येक प्रश्न का पूर्वावलोकन करें8 प्रश्न
जैसे ही आप प्रश्नोत्तरी लेते हैं उत्तर और स्पष्टीकरण दिखाई देते हैं।
- A model answers fluently and names a source. What should a reader still check?
- Only whether the answer is polite
- Whether the response is long enough
- Whether the model used a large context window
- Whether the source exists and supports the claim
- Does more training data guarantee a better system?
- No; data can be irrelevant or systematically flawed
- Yes, if it comes from the internet
- Yes, regardless of the task
- No model can learn from more data
- Why compare a larger model with smaller or simpler alternatives?
- Larger models always have worse accuracy
- It may cost more without meeting the task’s needs
- A benchmark score cannot be measured
- Model size determines deployment law
- A demo solves one impressive case. What conclusion is justified?
- That the system can handle every difficult case
- That it will be reliable in production
- Only that the demonstrated setup handled that case; more tests are needed
- That no tool or context contributed
- Does automation remove human responsibility for the system?
- Yes, when outputs are generated automatically
- Yes, if a vendor hosts the model
- Only if a model has a high score
- No; people choose goals, data, interfaces, permissions, and deployment conditions
- What does one failure tell you about a system?
- It reveals a failure worth testing, but not that every use is ineffective
- That the system is useless for all tasks
- That the model is conscious
- That all future versions will fail identically
- What is a benchmark result distinct from?
- A measured score
- A future prediction or a statement about consciousness
- An evaluation setup
- A task-specific test
- How should a broad capability claim be phrased?
- As strongly as possible to attract attention
- As a guarantee based on a single score
- At the scope the supporting evidence actually covers
- Without naming the test conditions