AI-Native User Experiences: The Effect Opportunity by Guillermo Rauch (Effect Days 2024)

Effect is an ecosystem of tools to build better applications and libraries in TypeScript.

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Effect Days 2024 was sponsored by:

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Guillermo Rauch discusses the advancements in AI and its impact on software development, particularly in the context of creating AI native user experiences. He emphasizes the role of TypeScript and the transition from machine learning to AI. He also explores the evolution of chatbot applications and the potential for embedding UI into AI apps.

Highlights:

→ Software development is shifting towards AI native user experiences.
→ The challenges faced by AI developers include reliability, alignment, safety, and complexity in modern AI application stacks.
→ TypeScript and the Effect ecosystem offer ways to address reliability issues in complex pipelines.

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Learn more about and follow Guillermo:

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#Effect #TypeScript #AI #EffectDays

[ivan.jeremic]

I really hope there will be a point where we don't have these two worlds anymore, hope that when types in the language ship and become good the projects merge, also I hope that the language get's an official bundler which is extensible, a native bundler which is part of the language has the benefit that projects like Vite have less to do, Vite or similar projects themselves can then be just plugins and focus on stuff they want to extend/provide.

[KennethFeur]

not related to effect, but typescript would also be better for AI research. In typescript using arithmetic type magic you can achieve type safety on a tensor shape level. For example, you can define a function multiplyTensors which accepts tensor of shape M*N and tensor of shape N*P, and returns a tensor of shape M*P. Potentially you can even infer the entire model architecture on the type level. Afaik you can't achieve this in Python, and even Mojo can't do this (not sure about Mojo though, maybe they added more features since the last time i checked).
But the big downside of TS (for ML research) is it doesn't support operator overloading which is widely used in ML.