How AI Could Empower Any Business" by Andrew Ng, a TED talk.

How AI Could Empower Any Business" by Andrew Ng, a TED talk.

May 6, 2024
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Author: Nick Ning

πŸ€– The Long Tail Problem of AI: Democratizing Access to AI Systems

Artificial Intelligence (AI) has been in the hands of highly skilled AI engineers, who work in big tech companies. Most people have access only to the AI that they built for them. However, I believe that we can build a much richer society if we can enable everyone to help write the future. But why is AI largely concentrated in the big tech companies? Because many of these AI projects have been expensive to build, requiring dozens of highly skilled engineers and costing millions or tens of millions of dollars to build an AI system. The large tech companies, particularly the ones with hundreds of millions or even billions of users, have been better than anyone else at making these investments pay off. However, this recipe for AI does not work once you go outside the tech and internet sectors to other places where, for the most part, there are hardly any projects that apply to 100 million people or that generate comparable economics.

πŸ€” Why is AI Concentrated in Big Tech Companies?

The reason why AI is largely concentrated in big tech companies is that many of these AI projects have been expensive to build. They may require dozens of highly skilled engineers and may cost millions or tens of millions of dollars to build an AI system. The large tech companies, particularly the ones with hundreds of millions or even billions of users, have been better than anyone else at making these investments pay off. For them, a one-size-fits-all AI system, such as one that improves web search or that recommends better products for online shopping, can be applied to this very large number of users to generate a massive amount of revenue.

πŸ• The Long Tail Problem of AI

The long tail problem of AI is that there are millions of projects sitting on the tail of the distribution that no one is working on, but whose aggregate value is massive. For example, a small pizza store could never serve enough customers to justify the cost of hiring an AI team. However, by selling pizza, the owner is generating data that can be taken advantage of. An AI system is good at spotting patterns when given access to the right data. Perhaps an AI system could spot if Mediterranean pizzas sell really well on a Friday night, and suggest to the owner to make more of it on a Friday afternoon.

🀝 Democratizing Access to AI Systems

The emerging new way to build AI systems is to shift the focus from asking people to write lots of code to asking them to focus on providing data. This turns out to be much easier for a lot of people to do. Today, there are multiple companies working on platforms like these. An inspector can take pictures of the fabric and upload it to a platform like this. They can show the AI what tears in the fabric look like by drawing rectangles and what discolorations in the fabric look like by drawing rectangles. By adjusting the data given to the AI, you can help the AI get smarter.

🌟 Highlights

- AI is largely concentrated in big tech companies because many AI projects have been expensive to build.

- The long tail problem of AI is that there are millions of projects sitting on the tail of the distribution that no one is working on, but whose aggregate value is massive.

- The emerging new way to build AI systems is to shift the focus from asking people to write lots of code to asking them to focus on providing data.

- By democratizing access to AI systems, we can start to empower every accountant, every store manager, every buyer, and every quality inspector to build their own AI systems.

❓ FAQ

Q: What is the long tail problem of AI?

A: The long tail problem of AI is that there are millions of projects sitting on the tail of the distribution that no one is working on, but whose aggregate value is massive.

Q: Why is AI largely concentrated in big tech companies?

A: AI is largely concentrated in big tech companies because many AI projects have been expensive to build.

Q: How can we democratize access to AI systems?

A: The emerging new way to build AI systems is to shift the focus from asking people to write lots of code to asking them to focus on providing data. By democratizing access to AI systems, we can start to empower every accountant, every store manager, every buyer, and every quality inspector to build their own AI systems.

Resources:

- https://www.voc.ai/product/ai-chatbot

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