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Chatbots can struggle with
, which requires advanced processing capabilities.
Latency in chatbots can affect the overall
experience and satisfaction.
One of the major ethical challenges of chatbots is ensuring the
of users' data.
Bias
In machine learning, the term
refers to a model that is too complex for the amount of training data available.
A key challenge in developing chatbots is understanding
in user queries.
Chatbots must be programmed to handle sensitive
responsibly to avoid ethical pitfalls.
Data Privacy
Collecting and curating a
that reflects real-world conversations can enhance the chatbot's performance.
The
of a chatbot's architecture can impact its scalability and ethical implications.
Ethics
Conversational AI
Latency
When training a chatbot, it is important to consider the
between model complexity and processing power.
Chatbots require significant
resources to provide real-time responses to user queries.
Effective chatbots use natural language processing to comprehend the
of a conversation.
Reducing latency can be crucial in providing real-time
to users in chatbot interactions.
The architecture of a chatbot needs to be designed to handle large
of data efficiently.
Processing power greatly influences how quickly a chatbot can
user input.
The integration of
learning allows chatbots to improve their understanding over time.
