AI is DEAD 😲. The Rise of Organoid Intelligence(OI) 🔥in Tamil
The Future of Computing: Exploring Organoid Intelligence
Current Challenges in AI and Energy Consumption
- The main issue with today's AI systems is their high energy consumption, averaging 0.48 kilowatt-hours per day, while large language models can consume over 500 megawatts.
- Training these models incurs significant costs due to expensive GPUs, leading to millions spent on energy and resources.
- The excessive electricity and water usage associated with current computing methods raises concerns about sustainability and efficiency.
- Despite the challenges, human cognition allows for insights and decision-making that current AI struggles to replicate effectively.
Understanding Organoid Intelligence
- The process begins by taking skin cells from humans, converting them into stem cells, which then grow into a tiny 3D ball of brain tissue known as an organoid.
- Scientists have successfully grown approximately 800,000 neurons connected to a computer that learned to play games through feedback mechanisms.
- A particular company has developed the world's first code-deployable biological computer using around 200,000 living human neurons linked to a computing chip.
Future Possibilities with Living Neurons
- Tomorrow's computers may learn not just from traditional coding but also from living neurons, potentially revolutionizing how we approach computation.
- While some applications are being phased out due to resistance against change, others are emerging as viable alternatives in the tech landscape.
Vision for Next Generation Computing
- There is potential for ultra-efficient computers that significantly reduce heat emission and resource consumption compared to current technologies.
- Advancements could lead to breakthroughs in drug testing and neurological disease research by utilizing brain cell capabilities more effectively.
Embracing Curiosity in Technology Development
- Maintaining curiosity is essential for pushing boundaries in technology; researchers must remain open-minded about new possibilities as they arise.
- Ultimately, understanding organoid intelligence requires recognizing its practical implications within our environment and adapting accordingly.
Decision-Making in AI: Current and Future Perspectives
The Role of Intelligence in Decision-Making
- The speaker emphasizes the necessity for intelligence systems to autonomously make decisions, akin to current Learning Management Systems (LMS).
- Discussion revolves around real experiments conducted in 2022, exploring the capabilities and future potential of artificial intelligence mimicking human neurons.
- There is a call for further research into the implications of these advancements, highlighting the importance of understanding both current functionalities and future opportunities.
Engagement and Curiosity in Learning
- The speaker addresses audience engagement, suggesting that comments should reflect genuine learning points rather than superficial questions.
- Acknowledgment is given to those who actively participate by sharing insights or asking thoughtful questions, which serves as motivation for continued efforts in research and discussion.
- The speaker encourages curiosity among viewers, inviting them to express their thoughts or inquiries in the comment section.