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NVIDIA’s next big play in inference
Plus: Fake photos meet their first real test
Rimsha Bhardwaj, Hasan Toor & Ihtesham Haider
November 10, 2025
Hello, Prohuman
Today, we will talk about these stories:
The quiet revolution inside data centers
The new front in A.I. detection
Gamma’s 52-person team hits $2.1B
No coding. No tech degree. No problem.
On Saturday, 11th November at 9 AM EST, something different is happening.
Imagine this:
Someone with zero coding skills builds an AI agent that replies to emails, schedules meetings, posts on social media, and runs 40+ apps in perfect sync —
All in one morning.
Not a fantasy.
Not a Silicon Valley story.
Just a Masterclass that shows how anyone — yes, anyone — can build smart systems that automate the boring stuff and unlock hours of freedom.
AI agents aren’t the future.
They’re the quiet edge behind every productive creator today.
This is the blueprint.
NVIDIA Dynamo rewrites how inference scales
Image Credits: NVIDIA
AI inference just hit cluster scale, and NVIDIA wants to own the orchestration layer.
Its new Dynamo integrations connect directly with major cloud platforms like AWS, Google Cloud, and OCI, enabling multi-node inference managed through Kubernetes. The goal: to serve millions of concurrent users without adding more hardware.
Dynamo’s latest feature, Grove, lets engineers define entire inference systems in one line specifying how GPUs handle prefill and decode tasks, and letting the platform automate the rest. In tests, Baseten doubled inference speed for long-context code generation using Dynamo alone.
The underlying shift is from single-GPU efficiency to distributed intelligence. With disaggregated serving, models like DeepSeek-R1 now run across hundreds of GPUs, optimizing each step of reasoning at scale.
Inside a humming data hall, GPUs no longer just compute. They cooperate and NVIDIA’s software is what’s teaching them how.
Copyleaks moves from words to pixels
Image Credits: Copyleaks
A.I. made faking text easy. Now it’s doing the same to images and Copyleaks wants to catch it.
The plagiarism-detection firm just launched a tool that scores how much of an image was AI-generated, even highlighting which parts were machine-made. It’s aimed at a growing mess of fake receipts, doctored insurance claims, and manipulated media.
CEO Alon Yamin says the goal is simple: restore trust in what we see. But even Copyleaks admits the work is messy. Early tests show it flags some fake documents while missing others, and sometimes calls real photos fake.
Institutions will pay by volume, and the company plans to extend detection to audio and video by 2026. It’s already eyeing education, finance, and publishing as entry points.
“Seeing is believing” used to hold up. Now, belief needs a detector.
A 52-person A.I. startup just passed $2 billion
Gamma started as a fix for PowerPoint fatigue. Now it’s a profitable A.I. engine worth $2.1 billion.
Founded in 2020, Gamma lets users turn text into finished decks, websites, and posts in minutes. It just raised $68 million from Andreessen Horowitz, with 70 million users and $100 million in annual revenue.
The surprise isn’t the valuation. It’s the math. Gamma has only 52 employees and hasn’t touched the $12 million it raised last year. In a field burning cash, this one is printing it.
The new money will push Gamma deeper into enterprise accounts, where it’s already charging $480 per seat, and into global markets where Canva and Beautiful.ai are crowding the lane.
A.I. has turned slide decks into software battles. And Gamma’s next pitch might be to buy the companies it once competed with.
Prohuman team
Covers emerging technology, AI models, and the people building the next layer of the internet. |  Founder |
Writes about how new interfaces, reasoning models, and automation are reshaping human work. |  Founder |
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