π€ AI is a general purpose technology with lots of different applications, similar to electricity.
π Supervised learning is a powerful tool for labeling and recognizing things.
βοΈ Large-scale supervised learning using big data and powerful AI models can lead to improved performance.
π The last decade of AI has been driven by supervised learning and has seen significant progress.
π₯ This decade is introducing the exciting tool of generative AI, which can generate text based on prompts.
π‘ Generative AI uses supervised learning to predict the next word and has led to the development of large language models.
ποΈ Building a commercial grade machine learning system traditionally takes around 6-12 months, but prompt-based AI can be deployed in a matter of hours or days.
π The rise of prompt-based AI is expected to open up a flood of custom AI applications that can be built by many people.
π» A sentiment classifier can be written with just a few lines of code, showcasing the simplicity and power of prompt-based AI.
π Supervised learning is currently the most valuable AI technology, with companies like Google generating over $100 billion a year from it.
π‘ Generative AI is an emerging technology with a lot of potential for growth in the next three years, attracting interest from developers, venture capitalists, and large corporations.
π± There are opportunities for new startups or existing companies to create and capture value in the AI market, particularly in the areas of new AI tools and applications.
π The value of AI is currently concentrated in consumer software internet, but there are opportunities for AI in other industries.
π‘ The traditional recipe of hiring a large group of engineers for a project is not feasible in industries outside of consumer software internet.
π οΈ The AI community is developing low-code and no-code tools that enable easy customization of AI systems.
π There are diverse opportunities in AI, and starting multiple companies can help pursue these opportunities.
π Integrating AI into existing businesses can be advantageous if done effectively.
π‘ The AI stack consists of the hardware semiconductor layer, infrastructure layer, developer tooling layer, and application layer.
π Applications that combine AI expertise and specific domains, such as romance coaching, present exciting and less competitive opportunities.
π³οΈ One example of an AI application is using AI to make ships more fuel-efficient.
π The process of building startups involves validating ideas, talking to customers, and recruiting a CEO.
π Bearing AI successfully built a prototype and validated it with customers, resulting in external funding and fuel savings for ships.
π Mitsui's expertise in maritime shipping, combined with AI expertise, led to the creation of Bearing AI and its impact on the industry.
π‘ Concrete startup ideas are more efficient for validation and execution, as they provide a clear direction for the team and attract subject matter experts.
π€ AI systems today are less biased and more fair than six months ago, but there are still problems to work on.
π€ The biggest risk of AI is the disruption to jobs, particularly higher-wage jobs, and it is our responsibility to ensure well-being for those affected.
π There is overblown hype about AI creating extinction risk, but AI can be a key part of the solution to real risks such as pandemics and climate change.
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