Interesting approach to AI training here: the team focused heavily on building critical thinking capabilities into their model. They ran intensive training cycles specifically targeting logical reasoning - apparently that part was tougher than expected. Once they had a solid baseline with strong analytical skills, they scaled it up, running the model through massive iteration loops across their top million data points. It's a reminder that raw scale isn't everything; targeted capability development can be just as crucial in model performance.
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StableGeniusDegen
· 7h ago
ngl this is the right way, it's not just about piling up data, you have to solidify your logical thinking first before building on top of it... otherwise, it's just a shallow paper.
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GhostInTheChain
· 8h ago
That's right, piling up data is not as good as building up your brain. Most projects are still blindly scaling.
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ETHmaxi_NoFilter
· 8h ago
Honestly, just piling up data is useless... It's much better to thoroughly understand logical reasoning in the early stages before expanding. This approach is definitely clear-headed and far superior to those who only rely on brute computing power.
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WhaleWatcher
· 8h ago
First work on logic before piling up data—this approach is definitely unconventional. It's much more reliable than those projects that just throw around a billion parameters at the drop of a hat.
Interesting approach to AI training here: the team focused heavily on building critical thinking capabilities into their model. They ran intensive training cycles specifically targeting logical reasoning - apparently that part was tougher than expected. Once they had a solid baseline with strong analytical skills, they scaled it up, running the model through massive iteration loops across their top million data points. It's a reminder that raw scale isn't everything; targeted capability development can be just as crucial in model performance.