An Anthropic investment is a hard NO for me! Reasons: 1. The fact that no data is available for the third quarter is highly questionable, suspicious, and quite revealing. 2. I cannot identify any competitive advantages (“economic moats”) in this business model. 3. The level of debt and ongoing credit obligations is extremely high. 4. The corporate governance is problematic. 5. I believe the AI market will have a correction 6. Who would want to own a stock that carries no voting rights? Future informations may change my assessment but right now it's a hard pass.

AO3 announces it is investigating a security incident that will leave the website offline for an estimated 2–4 weeks. No data has been deleted, but a potential database leak has not been ruled out.

We know curiously little about the first female, Eve: > never heard from her > no data on her life > manufactured from man > was second > is to blame Eve is our foundational concept of a woman, yet she is not legible. Why? For 1,400 years, humanity was confused about planets too. When the ancient Greeks looked up to the sky, they saw some lights (stars) appeared fixed, while other lights (planets) moved erratically. They couldn’t understand why. From their vantage point, Mars would stop, reverse, loop backward, and then resume. Planets were bewildering, called "wanderers". To Greek physicians, the womb was also perplexing. They taught that the womb moved freely, a restless wanderer inside the body. They looked up at the sky, and at a woman, and concluded the same thing: they are erratic and wandering. To resolve this planetary madness, astronomers spent 1,400 years trying to understand. They used complicated models, overlaying circles onto circles (epicycles). Then, Copernicus and Kepler figured it out. Two insights solved over 1,400 years of bad explanations. It turns out the observed was not fixed, and the orbits were ellipses, not perfect circles. Our bewilderment about female health only means it is yet to be understood. There’s a reframe waiting to happen. In the fifth century BCE, Polykleitos sculpted the male body as a system of ideal mathematical proportion. Setting the historical trajectory for the “ideal” body. This passed through Vitruvius and then was immortalized by Da Vinci. This is how the default template of the human body was established. The male body was chosen because it held still, not because it was superior. It lacked the cyclical, "erratic", misunderstood shifts of the female body. Perhaps it's time for another reframe. In the next 90 days, Kate will become the most measured female in history. Three of her menstrual cycles (orbits) will be meticulously tracked. > 1,900 biomarkers tracked > 14.8 million data points > 100 tasks a day > 6-10 hours a day > 50+ devices > brain, taste, smell, and more > 3 menstrual cycles The effort will reveal new insight into female health, though that’s not really the primary objective here. Kate is trying to become legible. First to herself, and then to others.

37,000. That's how many civilians died needlessly in armed conflicts in 2025. Civilians are #NotATarget#. International humanitarian law requires all parties to armed conflict to protect civilians and civilian objects. Protecting civilians is not optional. It is a legal obligation. #PoCWeek2026#

I just shared a workflow with stakeholders @sparkfinance — get data insights directly through @claudeai + @Dune MCP, no analyst needed. 🧵 ➢ The workflow: 3 steps 1. Identify the right dashboard Match the stakeholder's question to the relevant dashboard. Each dashboard sits on top of pre-validated intermediate tables I maintain — two reasons this matters: • Accuracy — data is validated before AI even touches it • Cost — pre-aggregated tables consume far fewer Dune credits than pulling raw on-chain data 2. Drop the dashboard URL into Claude No SQL. No data wrangling. Just a prompt. 3. Keep drilling down in the same chat The tables are granular enough for follow-up questions without starting over. ➢ Why dashboards? Raw tables are slow and error-prone. Dashboards are pre-validated, pre-aggregated, and always fresh. You get accurate data instantly — and the AI can reason on top of it without guessing. ➢ Example prompt for SparkLend weekly analysis: Please use Dune MCP to pull the latest data from these dashboards. Summarize key changes over the past 7 days: TVL, utilization, whale activity, top risks. One message. One minute. Done. ➢ Somewhere along the way, I became the AI's data engineer. I build the tables. I validate the logic. I maintain the pipelines. The AI does the analysis. Honestly? I'm fine with that. That's what frees me up to learn more, ask better questions, and do the work that actually matters. Setup Dune MCP: Thanks @Dune for building this — making it genuinely easy to bring AI into on-chain data workflows. 🙏 cc @blstamm11 @kdotkrisp @fr0zensun

i got a phone just sitting in a drawer for a year already, still works, just doing nothing. never thought it could do anything, then i saw @Acurast and it clicked. no data center, no big server, just phones doing the work. my daily phone can run lite, plug it in at night and it works while i sleep, apps still mine, nothing gets wiped. got a spare android? that one can go core, reset it, leave it on, done. i am starting with the phone i already have, if yours is sitting in a drawer too, start there.