कोरवेव प्रश्नोत्तरी

जैसे ही आप प्रश्नोत्तरी लेते हैं उत्तर और स्पष्टीकरण दिखाई देते हैं।

1. CoreWeave मुख्य रूप से क्या प्रदान करता है?
   • एआई के लिए एनवीडिया जीपीयू के बड़े बेड़े तक क्लाउड पहुंच
   • उपभोक्ता स्मार्टफोन
   • फिल्में स्ट्रीमिंग
   • इलेक्ट्रिक स्कूटर
2. What business did CoreWeave operate before focusing on GPU cloud infrastructure?
   • Food retail demand forecasting
   • क्रिप्टोकरेंसी खनन
   • Speech transcription services
   • A consumer social network
3. Which services does CoreWeave list as part of its AI cloud platform?
   • Only a hosted language model with no infrastructure
   • Food inspection cameras and recipe tools
   • GPU compute together with networking, storage, and supporting software
   • A smartphone app for mining cryptocurrency
4. Why should a customer benchmark its own workload on a specialized GPU cloud?
   • A specialized cloud guarantees a speedup for every model
   • The GPU name alone determines total cost
   • Cloud providers use identical networking and storage
   • Performance and cost depend on the workload, system configuration, and service requirements
5. Which business risks do CoreWeave filings identify for customers and suppliers?
   • Concentration risks that can make the business sensitive to a small number of counterparties
   • Guaranteed demand from every customer
   • No dependency on hardware supply
   • A risk that only affects food safety inspections
6. 2025 में CoreWeave किस महत्वपूर्ण कॉर्पोरेट मील के पत्थर तक पहुंचा?
   • इसने GPU का उपयोग बंद कर दिया
   • यह शेयर बाज़ार में सार्वजनिक हो गया
   • यह एक गैर-लाभकारी संस्था बन गई
   • इसका कॉफ़ी श्रृंखला में विलय हो गया
7. What is one infrastructure dependency a GPU cloud provider must manage for large AI clusters?
   • Only the model’s tokenizer vocabulary
   • The hotel’s room occupancy
   • Power, networking, cooling, and accelerator availability at data-center scale
   • The number of emotion labels in a dataset
8. Why should an enterprise compare end-to-end workload cost across GPU cloud providers?
   • The same nominal GPU always produces identical service cost
   • Model parameter count alone determines the bill
   • A public-company listing guarantees low prices
   • Hardware, interconnect, storage, utilization, and software affect total performance and cost