Quantum Computing: Unlocking the AI Revolution

There's no doubt that artificial intelligence (AI) is making massive strides, and the recent accomplishments in large pre-trained models are testament to that. However, it's important to remember that the real game-changer in this field is quantum computing, which has the potential to revolutionize not only AI, but also the global economy and technology landscape. We're witnessing a convergence in AI research, as more and more problems are being tackled by training large machine learning models on vast amounts of data. These so-called 'foundation models' or 'large pre-trained models' can perform a wide range of tasks without being explicitly designed for them. They're trained through self-supervision, without relying on manually labeled data, and can adapt to new tasks without further training. Moreover, their capabilities can be improved simply by scaling up their size and training data, without the need for substantial changes to their underlying architecture. Examples of these large pre-trained models include language models like GPT-3, PaLM, OPT, and Chinchilla, which have shown an incredible ability to write coherent paragraphs, explain jokes, and solve math problems. Meanwhile, 'multi-modal' models like DALL-E 2, Imagen, Parti, and Flamingo are capable of generating realistic and artistic images from captions, as well as describing images and answering questions about their content. Some models, like DeepMind's Gato, can even control a real-world robot! Quantum computing has the potential to unlock the true power of these AI systems by significantly accelerating their training and processing capabilities. As a quantum computing evangelist, I believe that investing in quantum technology is crucial for any nation to stay ahead in the AI race and reap the technological and economic benefits that come with it. The time to act is now, or we risk falling behind in this increasingly competitive field.