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a

a16z Cast

02/07/25

@ a16z

The model itself may not be the primary focus; instead, the integration of models into applications could dictate their relevance in the market.

Video

a

What DeepSeek Means For The Future Of AI | Tech Veterans Weigh In

@ a16z

What DeepSeek Means For The Future Of AI | Tech Veterans Weigh In

02/07/25

Related Takeaways

MZ

Mark Zuckerberg

04/30/25

@ Dwarkesh Patel

As AI becomes more integrated into various applications, we need to optimize for specific internal use cases, which may lead us to use other models if they better serve those needs.

a

a16z Cast

02/07/25

@ a16z

The current AI models are impressive on their own, but they need to be integrated into applications that enhance user engagement and retention.

A

Anthropic Cast

02/13/25

@ Anthropic

If your product's success depends solely on the models getting smarter, you're likely building the wrong thing. Instead, create something that improves as the models advance.

LQ

Lin Qiao

05/19/25

@ Sequoia Capital

Many app developers currently rely on off-the-shelf models, but infusing product knowledge into these models through prompt engineering is a new and necessary skill.

YC

Y Combinator Cast

11/15/24

@ Y Combinator

AI advancements may not commoditize technology; instead, the strongest technical teams will capture the most value by leveraging new models effectively.

WW

Winston Weinberg

03/11/25

@ Sequoia Capital

As an application layer company, we must adapt to the rapidly changing landscape of AI model providers and ensure we are testing and integrating the best models available.

SC

Sequoia Capital Cast

05/07/25

@ Sequoia Capital

The application layer is where value will ultimately accrue in AI, as companies create customer-focused solutions that leverage foundational models.

MK

Mike Krieger

05/09/25

@ Sequoia Capital

A surprising number of AI-native products fail to expose the necessary application primitives to the models, limiting their effectiveness.

SA

Sam Altman

04/15/24

@ 20VC with Harry Stebbings

The commoditization of AI models is inevitable, but the enduring value will come from a small number of providers who can deliver highly personalized and context-aware models.