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parthknowsai

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parthknowsai

#ai #tech #education #science #research #learn #viral #fyp

mojzeszowicz 19h

🔥🔥🔥🔥🔥

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billynavidad 21h

Love this!

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downunder_to_upover 21h

Doesn’t this seem obvious, I mean, who doesn’t check their work a few times over before providing a final answer?

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kamali_.b 21h

Im curious to see what might happen when we place these small parameter domain specific models into ecosystems of other domain specific small parameter models in which they all can communicate and solve problems recursively collaboratively. I could see a similar architecture bringing up the efficiency of large general models! This is truly exciting stuff.

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getinterfanatic 20h

Sounds kinda like DeepSeek was a few months ago. Very interesting. 7M is phenomenal.

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leidus 18h

Yeah, but not on the same range of subjects, right. I.e. can the small model answer the numbers as the large models? The small ones can't have the same amount of training data.

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scarleteagle 21h

Bigger isn't necessarily better. I think this approach is quite interesting and appreciate the efficiency especially with the resources that can be saved.

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fahad.m.reda 21h

Thanks for the video 👏👏

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dnich355 20h

It’s not peer reviewed and it’s published by an profit-seeking company. It’s motives are not necessarily to advance the field as much as it is to gain notoriety and profit.

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lehacarpenter 17h

Add lazy evaluation and 🔥

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dat_winner 19h

Is this the sign that the AI bubble's about to burst? Instead of pouring money into infrastructure, similar results can be achieved with simpler models.

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_abhay557_ 21h

Small Language Models are future just like everyone will have there "own ai" in there phone

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siddhartha_bhattacharjee_ 22h

This could open the doors for edge AI integrations, bringing AI to edge would make it more accessible and reduce reliance on cloud and massive data centers, we could see so many everyday tech coming with integrated ai

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channelph 22h

I mean. I’ve been saying this for months being patently pending in this tech.

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parthknowsai 22h

Please note : this model is domain specific, not intended for general use cases. Although it could make future LLMs way more efficient.

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