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AW

Alexandr Wang

11/14/23

@ Accel

The bottleneck for AI development isn't the algorithms or technical limitations; it's actually the availability of data.

Video

A

Scale AI’s Alexandr Wang | Our Most Powerful Tech | Spotlight On: AI | S1E5 | AccelVC

@ Accel

Scale AI’s Alexandr Wang | Our Most Powerful Tech | Spotlight On: AI | S1E5 | AccelVC

11/14/23

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Trenton Bricken

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The bottleneck for AI development may shift from generating solutions to verifying their accuracy and reliability.

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A lot of the current bottlenecks in AI deployment stem from inadequate tooling and the need for proper sandboxing.

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Eric Schmidt

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The future of AI will require not only more data centers but also the ability to generate new data, as we are running out of existing data to train AI systems effectively.

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Sergey Brin

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Both algorithmic improvements and computational advancements, such as better chips and larger data centers, are essential for progress in AI.

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Shyam Sankar

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The challenge in AI lies in balancing supply and demand; while we invest in building models, we must also focus on how to effectively utilize these models for economic and mission advantages.

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Carl Eschenbach

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Data is the new user interface for AI, and having highly curated data is crucial for achieving great outcomes with AI agents.

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Demis Hassabis

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The bottleneck in robotics is not the hardware but the software intelligence that drives it.

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Andrew Bosworth

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When consumers encounter limitations with AI, it reveals opportunities for developers to create solutions that meet those needs.

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AI is imminent, not just inevitable, as the necessary conditions such as compute, networks, data, distribution, and talent are already in place.