Did anyone really think these models actually reason? Also, they don't really have memory.

https://x.com/RubenHssd/status/1931389580105925115?t=12VmaFEBUaXiikH3lFmAlw&s=19

That's why you don't throw the kitchen sink at models with large contexts.

The more specific the context the better.

That's also why few shot prompts work really well, it keeps the model focused with clear examples.

When coding I give models specific code that has examples I want to replicate, when applicable.

In its latest study, The Illusion of Thinking, Apple questions the widespread assumption that large language models are already capable of real logical thinking - i.e. real “reasoning”. Instead of a cognitive breakthrough, the Apple researchers see a kind of illusion: the models

At the heart of the criticism is the observation that LLMs drastically lose performance in more complex tasks - even if they had enough computational time or tokens available to solve the task. This means that as soon as the complexity increases, the performance of the models

Chubby♨️

That's why you don't throw the kitchen sink at models with large contexts.

The more specific the context the better.

That's also why few shot prompts work really well, it keeps the model focused with clear examples.

When coding I give models specific code that has examples I want to replicate, when applicable.


https://x.com/kimmonismus/status/1931380162274414772?t=Dad16ChnvnKokad2rSb7pQ&s=19

The open web is dead, long live the open web. ⌐◨-◨

Building /farcaster

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