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Define General Artificial Intelligence (AGI) in brief.
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AGI refers to AI systems with human-like cognitive capabilities, currently not achieved by existing technologies.
In which period did artificial intelligence (AI) begin as a discipline?
Post-WWII with the advent of digital computers.
What are some challenges associated with AI compliance with GDPR?
Due to the data and methods used in training neural networks, ensuring compliance with GDPR is complex.
How do neural networks in AI mimic biological neural networks?
They perform pattern recognition and adjust the network to produce desired outputs, similar to how neurons in the brain process signals.
What are the potential future directions for AI according to recent advancements?
Addressing ethical issues, improving limitations, and striving towards more advanced AI, possibly achieving AGI.
What was the significance of the 'Attention Mechanism' discovered post-2012 in AI?
It led to the development of Transformer architectures, significantly improving capabilities in tasks like language processing.
How can biases and toxicity in AI training data impact AI outputs?
They can lead to inherited biases and offensive content in AI outputs, despite efforts to implement guardrails.
What is supervised learning in the context of AI?
It uses training data consisting of input-output pairs to learn a mapping from inputs to outputs.
What distinguished GPT-3 from earlier AI models?
Its large number of parameters (175 billion) and extensive training on 500 billion words from the web.
Why is training data crucial for supervised learning?
It provides the necessary input-output pairs that the model uses to learn and make predictions.
What fuels the debate about machine consciousness in AI systems?
Claims of AI sentience, such as those by Blake Le Moine about Google's Lambda, although lacking substantial evidence.
What are some concerns associated with AI accuracy and truthfulness?
AI systems often produce plausible but incorrect information which users must fact-check.
What major development since 2005 has significantly improved AI?
The rise of machine learning, especially since 2012.
What does poor performance on tasks outside its training data illustrate about current AI capabilities?
It shows that AI is fundamentally different from human intelligence and limited by its training data.
Why did neural networks become more feasible in recent years?
Due to the availability of modern computational power and large amounts of data.
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