Arsalan

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Arsalan

Arsalan

@bum_py

Wordcel, ex Shape Rotator; prev @IIM_Calcutta @iitkgp

Bangalore Katılım Ekim 2013
165 Takip Edilen156 Takipçiler
Air India Express
Air India Express@AirIndiaX·
@bum_py Hi! We apologize for the inconvenience caused. Kindly allow us some time as we are looking into your concern and will get back to you shortly.
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Arsalan
Arsalan@bum_py·
The flight has been delayed by 5:50 hours, just 10 mins earlier than the stipulated delay criteria for full refund. This is the level of fraud these supposedly public airlines operate at. @MoCA_GoI
Air India Express@AirIndiaX

@bum_py Hi Arsalan, we are sorry to hear this. Could you please DM us your PNR and elaborate on your concern so we can look into it? twitter.com/messages/compo…

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Arsalan
Arsalan@bum_py·
@AirIndiaX People are stuck since 3 hours here. How does a 30-min rain cause such a huge delay?
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Arsalan
Arsalan@bum_py·
@AirIndiaX is the worst airline rn. Feels like I’m travelling train. Pathetic service
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Arsalan
Arsalan@bum_py·
@anounymesss Girl brain is the opposite of product manager lol. It’s like a client who expects you to (accurately) infer their requirements with little info
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Arsalan
Arsalan@bum_py·
Blr T2 is so inaccessible that fucking Starbucks is the cheapest option
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Arsalan
Arsalan@bum_py·
Nice
Arsalan tweet media
Anish Moonka@AnishA_Moonka

If you're an AI startup in India, renting processing power from the government to train your model costs about $0.7 per hour. The same hardware on Amazon Web Services costs $3.7. On Microsoft Azure, $6.6. The Indian government is subsidizing AI infrastructure at rates that would make most Western startups do a double-take. I read all 26 pages of the white paper this tweet links to. The numbers inside are wild. The IndiaAI Mission has a budget of about $1.2 billion over five years, approved in March 2024. Almost half of that, roughly $500 million, goes straight to building the processing power AI companies need to train their models. The original plan was to deploy 10,000 processors. By December 2025, they had 38,000 running. 3.8x what they promised. A government open call in January 2025 pulled 506 proposals. The four startups picked first were Sarvam AI, Soket AI, Gnani AI, and Gan AI. Eight more were added by September. India now has 12 separate teams building AI models, ranging from tiny ones for basic chatbots to massive ones rivaling those from the US and China. They cover language, voice, vision, medical diagnosis, material science, and even brain-computer interfaces. The one I keep coming back to is Sarvam AI. They raised $41 million from Lightspeed, Peak XV, and Khosla Ventures. In May 2025, they released a model built on top of a French AI system (Mistral Small) and customized for Indian languages. It got roasted online. Critics said it was a foreign model in Indian clothing. So they went back and built Sarvam-105B completely from scratch, using Indian hardware under the government mission. It outperformed China's DeepSeek-R1 on certain tests, even though it was a model six times larger. Both were released for anyone to download and use in March 2026. There's something else buried in the paper I haven't seen another country try at this scale. India is building a copyright system specifically for AI training data. Under a December 2025 government proposal, AI companies can train their models on any copyrighted content they can legally access, books, articles, music, anything. Creators cannot say no. But the moment an AI product makes money, royalties are collected by a centralized government body and distributed back to creators. Singapore allows AI companies to use content without payment. China requires strict consent before training. India is trying a middle path, and publishers are already calling it forced participation. Stanford's AI Vibrancy Index, which measures a country's overall AI strength across research, talent, infrastructure, and investment, ranked India third globally in 2025. Up from seventh in 2023. But the actual scores tell you how far the gap still is: US at 79, China at 37, India at 22. And India's $1.2 billion budget sits next to China's $47.5 billion semiconductor fund and Saudi Arabia's $100 billion Project Transcendence. India is currently spending 40x less than the frontrunners. This white paper is the most detailed public bet yet that smart infrastructure design can close that gap.

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Arsalan
Arsalan@bum_py·
Used 5.4 in codex for prompt generation at scale. Findings: - context rot is real. After a few compactions, the model goes haywire - 1M context is still raw. Speed and performance take a nosedive before you even reach 500K
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Arsalan
Arsalan@bum_py·
They lobotomised codex
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