In the age of AI, Real engagement, real contribution, and real skin in the game matter more than ever. What was missing is an end-to-end, verifiable way to attribute actions and attest to influence. The creator economy shouldn't be dead. It was a bad incentives design that killed it. Excited to be building an ungameable reward layer for creator campaigns with @Punk9277 and @KaitoAI team.

The most revealing thing about this essay is who's missing from it: the individual user. Satya is right. Own your evals, your traces, your learning loop, your right to train on your own outputs. But he frames all of it as an enterprise problem, as if billions of ordinary users facing the same paradox with zero negotiating power is just a given, not a problem. Here's the deal the old internet actually ran on: human scale use was free, machine scale reuse was restricted. You could read anything, act on anything, do whatever you wanted with what you found. Scraping and bulk reuse were for companies, and companies got restricted. That contract made sense when only companies operated at machine scale. Personal AI breaks that assumption completely. Training a model on my own conversation history is now the personal use case. It's the new version of rereading my own notes. Yet the terms of service treat me like a scraper of my own life. And notice the sleight of hand. The labs tell you that you own the outputs. Then they attach a covenant banning the single most valuable thing you could do with them. Ownership that excludes the most valuable use isn't ownership at all. It's custody. The irony runs deeper. These same labs trained on the open web under fair use, arguing that machine learning from data is like reading. Fine, I actually agree. But then learning from model outputs is like reading too. Fair use for me, breach of contract for thee. California won't even enforce noncompetes. A researcher can quit tomorrow and build a rival with everything in their head. We privilege human memory over machine memory, right up until it's the labs doing the machine learning on everyone else's output. When learning only flows in one direction, that is not a market anymore. It is enclosure. If "what you create should belong to you," then we should make it law/new regulation that fits the new AI era. An unwaivable user right to own and reuse the outputs of your own AI interactions, including to train your own models or whatever the fuck you want (even selling it). Otherwise we get a future where a handful of companies own how everyone else learns.

Our on-prem @ethereum ZK Proof cluster is live. Proving on self-owned hardware is how Ethereum stays decentralized without centralized cloud chokepoint and how real-time ZK proving scales. Very proud to be the first team up-and-running in this initiative, with a generous grant from the Ethereum Foundation.

Our CSO @succinct_li did it again 🔥 We've been building an AI agent for fully automatic software performance optimization. First real test: we pointed it at our own stack — code hand-tuned for years by some of the best performance engineers in ZK. It still found an amazing 11% speedups. Then we gave it a single round on the open quantum computing benchmark by @eigencloud and @gajesh and it briefly took #1# on the leaderboard. Then we pointed it at @GPU_MODE. Top 20, in short order. ZK proving. Quantum circuits. GPU kernels. Three completely different frontiers all driven by one AutoEng agent. Performance engineering is one of the scarcest, most expert-driven skills in software. An agent that does it automatically doesn't just save engineering time: it changes the economics of building fast systems.

It was truly inspiring to hear from Marsel, a professional photography artist, about the importance of proving what is real in the age of AI. I really enjoyed recording this podcast with you sir! More to come!

Our team has been working on this for the last few months! Brevis Pico can now prove 99.9% @ethereum blocks in real time. We are live on @eth_proofs Let's get that 100X scaling on @ethereum L1 this year!

Say Hi to Brevis team at @BNBCHAIN Super Meetup Hong Kong! I will be hosting a panel on RWA x Privacy with amazing speakers from @OndoFinance @StableStock @UTechStables and CMBI.

In the age of AI, seeing is no longer believing. We solve this challenge with Brevis Vera today. Deepfake generators improve rapidly, and detection systems struggle to keep up. Detection is a never ending arms race. So instead of trying to guess which media is fake, we asked a different question. What if real media could prove itself? Today we are excited to introduce Brevis Vera. Brevis Vera allows images and videos captured on real devices to carry cryptographic proof of their origin and transformation. Starting from the moment of capture, Vera can generate verifiable proofs that the published media came from a real capture and that only permitted edits were applied. Importantly, the original raw media stays private. Vera proves the editing process without revealing the source content or the editorial workflow. Instead of asking “Does this look real?”, we can finally ask:“Can this media prove where it came from and how it was edited?” If you are curious, you can try a demo today:👉 Show me the proof.

As the BNB Chain ecosystem grows, so does the need for smarter privacy design. Join us for an X Space with privacy builders @brevis_zk, @0xbowio, @RAILGUN_Project, @zERC20io to discuss zk infrastructure and real-world use cases and adoption. 🗓️ Mar 4, 12PM UTC 🔗

We secure Pico in a defense-in-depth approach. Security audit, bug bounty, formal verification, and finally, operational security are all working together to deliver a bullet-proof proving system for the next 1000X Ethereum L1 scaling. Thank you @ethereumfndn for the support!