In what form does LLM classify the query — what exactly does it return for scenario selection?
Machine Learning / AI
What is Kafka?
What is the order of execution of operators in an SQL query?
```python import asyncio import time async def work(): await asyncio.sleep(1) async def main(): start = time.perf_counter() await asyncio.gather(*(work() for _ in range(5))) print("Total time:", time.perf_counter() - start) asyncio.run(main()) ``` ```python import time def work(): time.sleep(1) start = time.perf_counter() for _ in range(5): work() print("Total time:", time.perf_counter() - start) ```
Is a space considered a character in a task?
On what indicators can you understand that the model has degraded?
What is the difference between multithreading and multiprocessing in Python, and when to use each?
How to sort 20 chunks and select the top 5 most relevant for passing to LLM?
Why is it necessary to separate data types into mutable and immutable?
Can a hash match for different keys?
Why did you choose exactly two agents? Why not one or more?
How does feature scaling affect model training?
How does the zip function in Python work and what are its key arguments?
Why is regularization needed in models?
What is structured output and how is it used in LLM?
What is range in Python and how is it used as an argument?
How does GPT architecture differ from BERT architecture?
Why is context important in text classification tasks?
How do you evaluate the quality of clustering?
What can be seen in Grafana when monitoring a multi-agent system?