AI Training: Hitting the Limits?
In a recent tweet, Ilya Sutskever, co-founder of OpenAI, mentioned that AI training by scaling currently known classical Large Language Models (LLMs) is running into limits. This statement has sparked a debate within the AI community. On the other hand, Sam Altman, CEO of OpenAI, believes that there is no wall in sight for AI advancements. This divergence in opinions raises an important question: Who should we believe?
Mustafa Suleyman, co-founder of Inflection AI, has expressed his support for Sam Altman, emphasizing Altman’s sincerity about AI safety. Suleyman’s perspective aligns with the cautious optimism surrounding AI’s potential, despite the concerns about its limitations and ethical implications. Microsoft’s Mustafa Suleyman says he loves Sam Altman, believes he’s sincere about AI safety.
The Promise of Quantum Machine Learning (QML)
As the debate on the scalability of classical LLMs continues, the next big leap in AI is anticipated to come from Quantum Machine Learning (QML) on quantum computers. Quantum computers, such as those developed by companies like IonQ, have the potential to revolutionize AI by leveraging the principles of quantum mechanics to process information in ways that classical computers cannot.
John Martinis, former quantum computing lead at Google Quantum AI, explained that building devices that live up to the technology’s incredible promise requires a massive step change in scale and reliability, which in turn requires reliable error correction schemes. Quantum computers are particularly good at simulating other quantum systems, making them ideal for applications that involve interactions between particles, atoms, and molecules. After AI, quantum computing eyes its ‘Sputnik’ moment.
Quantum Computing: A Game Changer
Quantum computing is poised to disrupt various industries, including drug development, materials science, financial modeling, and cryptography. Companies like Microsoft and Quantinuum have made significant advancements in quantum error correction technology, leading to more stable and usable quantum computing systems. This collaboration has demonstrated promising results, with over 14,000 experiments conducted without a single error. Microsoft and Quantinuum say they’ve ushered in the next era of quantum computing.
Challenges and Ethical Considerations
Despite the potential of quantum computing, there are significant challenges and ethical considerations to address. Quantum computers’ ability to crack existing cryptographic systems poses a threat to cybersecurity. Additionally, the impact of quantum computing on job markets and the ethical implications of AI and quantum computing. The EU AI Act and potential U.S. regulations are examples of frameworks being discussed to govern AI development and deployment. This Week in AI: With Chevron’s demise, AI regulation seems dead in the water.
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