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I think the best case is to make the "monitor" as un-agentic as possible. We don't mind being "monitored" by various random tiny insects we don't even notice, even guard dogs are fine, but we really do mind if it's a globally connected networked system. And the intermediate case, human security guards with no recording equipment, we mind only a medium amount. The best idea I've come up with so far is to make these monitoring devices out of open-source verifiable hardware that has etched on it an open-weight LLM that classifies for a limited number of activities (basically, just violence; sorry, no scanning for jaywalking or not wearing a mask or drugs or unauthorized manufacturing or illegal immigrants, really just violence) and only records and forwards if that's what it sees. The device has no storage, no ability to load new algorithms, this is all it does. Also, a hash of every recording is published onchain (and a device can't record the next one until it sees confirmation of the previous one) so we can all count how much recording is done. Finally, everyone has a legal right to take any such device they see and grab it and dissassemble and verify the hardware themselves. Explicitly fund university clubs, hacker groups, etc to regularly do this.

After recording 25 PTS & 10 REB in his last game, Yaxel Lendeborg locks in before tonight's @emirates NBA Cup West Group C action in San Antonio! 🍿 Warriors/Spurs 📺 9:30pm/et, Prime

Here’s the recap of @cz_binance’s fireside with Anthony Pompliano at Cantor Convergence in Miami: He showed up in Miami just weeks after the biggest hack in crypto history and still looked calm. No stress, no drama. Just there. What stood out: Trust gets built when things go wrong, not when everything is perfect. @cz_binance basically said resilience matters more than never getting hit. That’s how you actually move Bitcoin forward. He also talked about AI and regulation. “Any new technology will go through a phase we can’t make regulation ahead of time. It moves too fast.” Crypto already went through this. AI is going through it now. And security. The $6.3B hack showed the industry (and even banks) hasn’t been taking this seriously enough. AI is making attacks faster. The only real answer is fighting AI with AI and actually working together as an industry instead of everyone doing their own thing. No full recording out yet but @cz_binance said it should be somewhere. While most people are still panicking or pointing fingers, @cz_binance is still focused on the long game. Protecting users and building through the noise. That’s why a lot of us still trust him. 🔶

Gemini 4 Carbon is now rolling out to developers, enterprises, scientists, and consumers! We built it to be a true partner for your hardest coding, research, and engineering workflows. Here's a fun example where Carbon read research papers on how songbirds sing and built an interactive model of a bird’s vocal organ…tuning the live audio physics against real bird recordings so you can hear 6 species sing or play it like a music synthesizer.

I told the team at @every that with Fable 5.2, one person can build professional software. Nobody believed me. Three days later a video editor was live for the team. It’s called Everycut. It has screen recording, a timeline, a transcript you cut by its words, a mixer, and an agent that presses the same buttons I press. I pitched it as Descript, Screen Studio, After Effects and Premiere in one. A week in, we held a team meeting in it. The first time I used it for real, I typed one sentence into Claude and it made the video. The audio and agent engines came from my ambient DAW. Whatever we can dream can now be built, so we should dream bigger.

And yeah @fermah_xyz started with a problem that sits deep inside the ZK stack. Zero knowledge applications can prove that a computation was done correctly, but producing those proofs at scale takes serious infrastructure: specialised hardware, several proving systems, workload scheduling, and reliability and cost controls. A team building a ZK rollup, zkVM, bridge or coprocessor cannot simply ask for "a proof" and move on. Fermah's first answer was a universal proof generation layer. Provers with GPUs and other hardware supply capacity, applications that need proofs create the demand, and Fermah matches the two. That marketplace is now called Froben. The problem behind the proof Running this in production exposed something bigger. A proof is one step in a longer sequence. Something has to trigger the work, the work has to run, the result has to be verified, and then the result usually has to start the next action. Fermah's argument is that blockchains are good at recording state and weak at starting what happens next. Take a lending position that crosses its liquidation threshold. The chain records the fact, but nothing forces the liquidation. A keeper, bot or backend still has to notice the condition, build the transaction and submit it. Consensus settles what happened, and a human run service still decides what happens after. Fermah calls the missing piece protocol agency: a protocol's ability to act on a verifiable condition without depending on an outside operator. What Kernel does Kernel is Fermah's Protocol Agency Engine, and its pitch is short: Define. Execute. Attest. A developer defines a workflow, Kernel runs it, and the result is published onchain with a cryptographic proof. Three design choices matter here: -Typed nodes. Workflows are built from a library of verified building blocks such as HTTP calls, onchain reads, price feeds and math functions. The type system validates how they connect before anything runs. -Sandboxed execution. Workflows run in an isolated environment built for untrusted code, and the same inputs always produce the same output. - AI where it helps, code where it counts. Fermah says AI agents can compose workflows, but deterministic code executes them, with no LLM in the execution path. Kernel can work as an oracle too. A smart contract requests a workflow, Kernel runs it, and the contract receives the result with a proof that the workflow ran exactly as written. Froben and Flashcast Fermah did not walk away from ZK. Froben still runs, now on top of Kernel, and its paying customers include ZKsync Era and Abstract. In Froben, a workflow defines the proving pipeline and Kernel schedules the work across the prover fleet. Flashcast Social shows a different use of the same engine. A user posts a question, and within seconds it becomes a live prediction market. Kernel then runs the resolution workflow and settles the market automatically when the event happens, with no committee and no dispute window. Proof generation and market resolution have little in common on the surface. What they share is a condition that has to produce an action, and that is the workload Kernel is built around. Fermah also lists data aggregation, pricing oracles and cross chain coordination as things Kernel can run. Where agents fit Fermah's latest thinking extends this to autonomous software agents. An agent working onchain needs to find available actions, check whether it is allowed to run them, pay, execute, and use the output as the input to its next step. Fermah describes this as action manifests, which make actions machine readable across discovery, eligibility, execution, payment and output. The shift in one line The old question was how to generate ZK proofs efficiently at scale. The new one is how a protocol can turn a verifiable condition into a complete, executable sequence. Proving is still part of the system, but it is now one workload among several that Kernel coordinates.

DYK: Huawei has been ranked No. 1 among Patent Cooperation Treaty (PCT) applicants by the World Intellectual Property Organization (WIPO) for the past 9 consecutive years, most recently recording 7,523 published international patent applications in 2025.

NEW: Cornell 7 frat brother Matthew Ingalls is accusing 'Jane Doe' of r*ping him, citing that he was too intoxicated to give consent. Ingalls reportedly told Cornell investigators that he was too intoxicated from alcohol and ketamine to give consent. "During Cornell’s investigation, [Ingalls] said he was too intoxicated to consent and suggested that Jane Doe actually assaulted him, according to school records..." ABC News reported. Ingalls reportedly told Doe on the phone that she told him that she was completely sober. "You did tell me you were sober, by the way. You did, you said you hadn’t been anywhere," he said, according to a recording. According to documents released by the Tompkins County DA's office, Ingalls, who was allegedly under the influence of alcohol and drugs, fell asleep during the s*xual encounter. He was later woken up and rejoined.

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