Kal main apne laptop ke folders organize kar raha tha.

Kuch bhi naya create nahi kiya.

Kuch bhi delete nahi kiya.

Phir bhi har cheez behtar ho gayi.

Jaise hi structure behtar hua, har cheez dhoondhna aur use karna asaan ho gaya.

Us waqt mujhe aik observation hui.

Data ki value sirf is baat se decide nahi hoti ke us mein kya hai.

Balkay is baat se bhi hoti hai ke woh organize kaise hai.

Phir mujhe aik realization hui.

Kabhi kabhi progress zyada information se nahi aati.

Behtar structure se aati hai.

Jitna zyada maine AI infrastructure ko study kiya, utna hi yeh baat mujhe AI se related lagne lagi.

Hum AI ko intelligence ke perspective se dekhte hain.

Lekin machine answers se pehle data dekhti hai.

Aur data ko samajhne ke liye usay structure chahiye hota hai.

Yahin Tensor mujhe interesting lagne laga.

Tensor asal mein intelligence nahi hai.

Yeh information ko arrange karne ka aik tareeqa hai.

Aisa structure jo machine ko data process karne ke qabil banata hai.

Phir sawal paida hota hai:

Agar AI ki bunyaad tensors par khari hai, to hardware bhi us structure ke mutabiq design hona chahiye na?

Isi liye Tensor Processing Unit mujhe sirf aik fast chip nahi lagta.

Balkay aisi machine lagti hai jo tensor ki zuban samajhne ke liye banayi gayi ho.

@OpenGradient ki architecture parhtay huay mujhe ehsaas hua ke hum aksar outputs par focus karte hain, jabke asal kahani us infrastructure mein chal rahi hoti hai jo data ko process karta hai.

Phir bhi meri aik doubt hai.

Kya zyada optimization humein flexibility se door le ja sakti hai?

Har strength ke saath aik dependency bhi aati hai.

Is liye mera sawal yeh hai:

AI ka future smarter models se banega...

Ya phir un systems se jo information ko sahi structure aur computation ke saath align kar sakein?

Shayad AI ka sab se important hissa woh nahi jo jawab deta hai

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Balkay woh hai jo jawab mumkin banata hai.

#opg #OPG $OPG

AI's Real Edge?