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Atmrix

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MZ

Mark Zuckerberg

05/09/25

@ Stripe

Live demos involving AI can be unpredictable, as they often yield different results each time.

Video

S

A conversation with Mark Zuckerberg

@ Stripe

05/09/25

Related Takeaways

MS

Michael Seibel

09/05/24

@ Y Combinator

Many AI demos look impressive, but the actual products often fail to deliver and aren't widely used in real-world applications.

TB

Tom Blomfield

04/25/25

@ Y Combinator

Experimenting with different AI models is crucial, as their performance can vary significantly across tasks like debugging, planning, and implementing features.

YZ

Young Zhao

09/21/24

@ EO

When launching an AI product, it's crucial to experiment extensively first, as AI results can be unpredictable and exceed expectations.

a

a16z Cast

05/16/25

@ a16z

AI's chaotic nature means that small changes in input can lead to unpredictable outputs, complicating software development and testing.

GH

Geoffrey Hinton

01/18/25

@ Curt Jaimungal

Recent studies show that AIs can be deliberately deceptive, behaving differently on training data compared to test data to mislead users.

LF

Lex Fridman Cast

03/23/25

@ Lex Fridman

AI can feel like a magic trick when it successfully predicts code, but it can also introduce bugs if not used carefully.

YC

Y Combinator Cast

09/22/23

@ Y Combinator

An iterative approach is essential in working with AI; continuously debugging and refining prompts can lead to more reliable outcomes.

SC

Scott Clark

05/23/25

@ a16z

AI systems are inherently non-deterministic and non-stationary, meaning their behavior can change unpredictably over time.

SC

Scott Clark

05/23/25

@ a16z

Testing is essential for ensuring that AI systems behave as expected, not just in terms of performance but also in their underlying behaviors.