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The Future Of AI—And Everything Else—Is Hybrid

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Summary

In this article, Daniel Newman explores the concept of "hybrid" technology and how it applies to artificial intelligence. Qualcomm recently released a white paper titled, “The Future of AI is Hybrid,” which explains that for AI to reach its maximum capabilities, it needs to be processed both on the cloud and the edge. Newman explains that hybrid technology is like hybrid cars, which run on both gasoline and electricity, allowing users to enjoy the best qualities of both types of cars. He goes on to explain how AI needs both powerful and stable cloud processing for model training and inference, as well as fast processing at the edge of a mobile device. He also highlights how the partnership of edge and cloud can save time and energy, while providing users with a more seamless experience. Lastly, Newman argues that the era of the single engine technology company is over, and that companies will need to be hybrid in order to keep up with the increasingly complex world of technology.

Q&As

What is the purpose of hybrid technology in the tech space?
The purpose of hybrid technology in the tech space is to reduce energy consumption, improve costs, and enhance performance.

How does hybrid technology improve cost, energy use, reliability and latency issues?
Hybrid technology improves cost, energy use, reliability and latency issues by allowing users to enjoy the best qualities of both types of technology, such as public and private cloud, or data center. It also reduces energy consumption and improves costs.

What is the concept behind hybrid AI?
The concept behind hybrid AI is that it needs to be processed both on the cloud and the edge. Computing at the edge would improve issues like cost, energy use, reliability, latency issues, privacy—all of the things that make scaling and growing a technology difficult.

What are the potential benefits of processing AI at the edge?
The potential benefits of processing AI at the edge include faster decision-making, less power consumption, and the ability to work without 24/7 connectivity to the internet or cloud.

What does the future of AI and other technology look like according to Qualcomm?
According to Qualcomm, the future of AI and other technology looks like hybrid models, where companies may process some of their data on the public cloud, private cloud, or data center in some type of mix. This allows for faster decision-making, less power consumption, and the ability to work without 24/7 connectivity to the internet or cloud.

AI Comments

👍 This article does an excellent job of outlining the concept of hybrid AI and why it is necessary for AI to reach its full potential. The article also offers interesting examples of how hybrid AI is already being used.

👎 The article could have gone into more detail about the potential drawbacks of hybrid AI, such as increased complexity and the need for specialized hardware.

AI Discussion

Me: It's about how the future of AI is hybrid. It talks about how AI needs to be processed both on the cloud and the edge to maximize its potential and how the same concept can be applied to other technologies as well. It also mentions how hybrid models reduce energy consumption, improve costs, and enhance performance.

Friend: That's interesting. What are the implications of this article?

Me: The article suggests that hybrid technology is the way of the future and it will help us to reduce costs and enhance performance. It also highlights the importance of partnerships between different companies and technologies to create something even stronger. This could have big implications for businesses that are looking to develop new technologies or AI applications. It could also lead to more democratization of generative AI and an increased focus on processing data at the edge.

Action items

Research the current market for hybrid AI solutions and identify potential partners for a hybrid AI solution.
Develop a strategy for leveraging hybrid AI to improve performance, reduce costs, and enhance user experience.
Explore the potential of combining cloud and edge computing to create a more powerful and efficient AI solution.

Technical terms

AI (Artificial Intelligence): AI is a type of computer technology that is designed to simulate human intelligence and behavior.
Hybrid: A hybrid is a combination of two or more different technologies, systems, or processes.
Cloud: Cloud computing is a type of computing that relies on shared computing resources that are delivered over the internet.
Edge AI: Edge AI is a type of artificial intelligence that is designed to run on devices at the edge of a network, such as smartphones, IoT devices, and other connected devices.
Generative AI: Generative AI is a type of artificial intelligence that is used to generate new data or content from existing data.
OpenAI: OpenAI is an artificial intelligence research laboratory that is focused on developing artificial general intelligence.
Microsoft: Microsoft is a technology company that develops and sells computer software, hardware, and services.
Brain: Brain is a Google-owned artificial intelligence research laboratory.
DeepMind: DeepMind is an artificial intelligence research laboratory owned by Google.