Hello, Human Guide

Today, we will talk about these THREE stories:

Your phone is no longer taking photos. It’s generating them.

According to TechRadar, the upcoming Galaxy S26 is expected to feature Samsung’s most advanced AI-powered camera system yet, blending capture, editing, enhancement, and even scene reconstruction into one pipeline. The report suggests AI will intervene at multiple stages of image processing, not just post-editing, positioning the S26 as Samsung’s most computationally aggressive camera release to date.

What stands out is how invisible the AI is becoming. This isn’t about filters anymore. It’s about your phone deciding exposure, detail, composition, and sometimes even filling in missing elements while you’re still standing there, screen glowing in your hand at 11:42 p.m. The camera stops being a lens and starts being a co-creator.

If this works, smartphone photography shifts from documentation to interpretation. And once interpretation is automated, originality gets blurry fast.

If your phone is rewriting reality before you even see the shot, the real question is what “authentic” photography even means anymore.

Meta is buying more AI chips. A lot more.

The Financial Times reports that Meta has secured a new multibillion-dollar deal with NVIDIA, reinforcing its reliance on NVIDIA GPUs as it scales AI infrastructure. This comes as Meta continues aggressive AI spending, even after attempts to develop in-house chips and diversify supply.

What struck me is how this signals surrender and acceleration at the same time. Meta tried building custom silicon. It’s still experimenting. But when deadlines hit and models need training at scale, the industry keeps circling back to NVIDIA. You can almost hear the quiet hum of server racks at 2 a.m., fans spinning, billions of parameters crunching through green-lit data halls.

This isn’t just about hardware supply. It’s about power concentration. If the most advanced AI systems depend on one dominant chipmaker, leverage shifts upstream.

If NVIDIA remains the choke point for advanced AI compute, the real question is who truly controls the pace of innovation.

India is no longer watching the AI race.

At the India AI Impact Summit 2026 in New Delhi, Microsoft pledged $50 billion in AI investments by 2030, alongside infrastructure commitments from major players, according to The Times of India. The summit reportedly included large-scale policy announcements, global partnerships, and record-setting participation signaling India’s ambition to become a global AI hub.

I think this is less about headlines and more about positioning. When a country commits tens of billions, it’s building compute, talent pipelines, startup ecosystems, and geopolitical leverage at the same time. You can feel the shift: AI is no longer just Silicon Valley’s experiment; it’s a national strategy lit up on conference stages at 9 a.m. under bright white LEDs.

Infrastructure is destiny in AI. Compute clusters determine who trains frontier models, who hosts them, and who builds the next layer of tools on top.

If AI becomes as foundational as electricity, the harder question is which countries control the grid.