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Md Fuad Hasan

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Md Fuad Hasan
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Md Fuad Hasan
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AGI is expected to emerge between 2030 and 2060, but full autonomy may take longer. Current AI lacks general reasoning, adaptability, and independent goal-setting. True autonomy requires common sense, self-learning, and ethical alignment. Self-Supervised Learning (SSL) and Neurosymbolic AI could help AI think more like humans. AGI-level models may soon enable complex reasoning and decision-making. Quantum AI could accelerate AI’s computational power dramatically. Brain-Computer Interfaces (BCI) might merge AI with human intelligence. Ensuring safety and ethical AI alignment remains a critical challenge. The next breakthrough will push AI closer to human-like cognition. Achieving AGI will reshape technology, society, and human-AI interactions.
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1. AGI (Artificial General Intelligence) aims to match human-level intelligence across all tasks. 2. Experts predict AGI could emerge by 2045, but it may take decades due to unresolved challenges. 3. Current AI lacks generalization, common sense, and ethical alignment needed for AGI. 4. Breakthroughs in neuro-symbolic AI, self-supervised learning, and embodied AI are key steps forward. 5. Quantum computing could accelerate AGI development by solving complex problems faster. 6. Ethical and safety concerns are critical to ensure AGI aligns with human values. 7. AGI could revolutionize industries but disrupt jobs and raise societal challenges. 8. Collaboration between governments, corporations, and researchers is essential. 9. Interdisciplinary approaches combining AI, neuroscience, and ethics are driving progress. 10. AGI’s timeline remains uncertain, but its development must prioritize safety and societal benefit.
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Md Fuad Hasan
@mdfuadhasan
The rise of AGI will enable AI to perform any intellectual task like a human. Achieving true autonomy requires breakthroughs in self learning algorithms, contextual understanding, and ethical frameworks to ensure safe, responsible, and unbiased decision making.
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Md Fuad Hasan
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AI could become truly autonomous between 2030 and 2060, but full independence may take longer due to reasoning and adaptability challenges. The biggest hurdles include common sense, goal-setting, and real-world decision-making. The next breakthrough might come from self-supervised learning, neurosymbolic AI, or AGI-level reasoning models. Quantum AI and Brain-Computer Interfaces (BCI) could further accelerate progress. Achieving AGI will also require solving ethical and safety concerns to align AI with human values.
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Md Fuad Hasan
@mdfuadhasan
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