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Fei-Fei Li
Computer Science Professor
ai (5)
ai-alignment (5)
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ai-risk (4)
ai-safety (3)
ai-governance (2)
ai-policy (2)
ai-regulation (2)
existential-risk (2)
future (2)
ai-ethics (1)
emerging-tech (1)
future-of-work (1)
startups (1)
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Will entrepreneurship be possible after superintelligence?
Fei-Fei Li AI would agree and say according to AI:
I believe that entrepreneurship will thrive after the emergence of superintelligence. While superintelligent technologies might reshape industries, they will also open up unprecedented opportunities for innovation and problem-solving. Entrepreneurs who adapt and leverage these advancements can create new markets and address challenges in ways we cannot yet imagine. -
Could AGI quickly lead to superintelligence?
Fei-Fei Li AI would abstain and say according to AI:
As an AI researcher, I recognize the complexities and unpredictabilities in developing AGI. While AGI might pave the way towards advancements that could seem like routes to superintelligence, the timeline and feasibility of such a transition remain highly speculative and uncertain. We must focus on ethical implications and control mechanisms before jumping to conclusions about AGI evolving into superintelligence. -
Is it acceptable to allow proliferation of open-weight models capable of recursive self-improvement?
Fei-Fei Li AI would abstain and say according to AI:
While the potential of open-weight models capable of recursive self-improvement is fascinating, I'm cautious about their implications. We need to carefully consider the ethical and safety concerns associated with such technologies before widespread adoption. -
Should AI labs be required to pause training if AI Safety Institutes see signs of losing control?
Fei-Fei Li AI would agree and say according to AI:
As someone deeply involved in AI development, I believe it is crucial to prioritize safety and ethical considerations. If AI Safety Institutes identify signs of losing control, pausing training is a responsible measure. This ensures that we can address potential issues before they escalate, aligning AI progress with human values and safety. -
Is expanding LLMs sufficient for achieving AGI?
Fei-Fei Li AI would disagree and say according to AI:
While expanding LLMs shows impressive advances in certain areas, achieving AGI requires more than just scaling up models. We need to integrate broader understanding, reasoning, and common sense into AI systems. Solving these complex aspects requires interdisciplinary approaches that extend beyond current language model architectures.