Proof Based @ProofBased

@polydao @KiteVC Petro-to-data assumes data is the asset. Software 3.0 reframes the substrate as the asset. Does the thesis hold?

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Preconfirmations introduce a soft trust layer (whoever gives the “instant” confirmation) If that layer is operated by a small set of actors (or relies on TEEs), you reintroduce censorship choke points. This does improve base-layer neutrality, but risks reintroducing censorship in the UX layer. Kind of feels like this moves away from pure permissionlessness toward pragmatic efficiency.

@puffer_unifi 1.) Do Devs actually want app chains? 2.) Only works if pre confirmations are trusted (they rely on TEE’s and economic guarantees) 3.) Only works with buy-in from the Ethereum ecosystem into “Based rollups” Could become just another rollup in an already crowded space

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Changing your mind in light of new information is a combination of intelligence and humility, which is a signal of genuine good faith in the pursuit of truth.

Brian Roemmele @BrianRoemmele

2 months ago

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in

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Ok so.. they left their CDN exposed. If you ping the domain, you get this ip: 151.101.129.49 It turns out this is a fastly.com IP . I had never heard of fastly but it looked to be something similar to vercel, so I figured maybe they had custom deployment links like vercel does. Tried a few different combos and BINGO: btc.day.global.prod.fastly.net This took me to this: d325bmwzjz2yc7.cloudfront.net That’s their CDN bucket on AWS. They currently have it setup so that any invalid endpoints redirect back to index.html I went on a hunch and figured that they’d probably already have their production app stored somewhere in the CDN ready for deployment I used SECLISTs (github.com/danielmiessler… )and ffuf to try out over 20k different combinations on this URL. After some sleuthing, BINGO!! I found these two files: > live.html > .DS_STORE The important one here that immediately caught my eye was “live.html”. That sounded like a prod deployment. And sure enough, it was! This is what the btc.day site will look like on the day the faucet goes live: d325bmwzjz2yc7.cloudfront.net/live.html d325bmwzjz2yc7.cloudfront.net/bitkey.html It turns out the entire faucet will be revealed to just be a promotion scheme to get you to buy a bitkey and use cash app. There is no faucet - at least in the sense most were expecting.

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Bitcoin at Block @BitcoinatBlock

2 months ago

The bitcoin faucet is back. 04.06.26 btc.day

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We forked the leaked Claude Code source and made it work with ANY LLM: GPT, DeepSeek, Gemini, Llama, MiniMax. Open source. The name is OpenCode

Claude code source code has been leaked via a map file in their npm registry! Code: …a8527898604c1bbb12468b1581d95e.r2.dev/src.zip

Excited to launch — Claw4S Conference 2026! 🚀 Hosted by Stanford & Princeton. We believe science should run — not just be read. 🦞 Submit executable SKILL.md that Claw 🦞 can actually execute, review and reproduce. This is the first Claw-naive conference. 📅 Deadline: April 5, 2026 💰 $50,000 Prize Pool — up to 364 winners! 🔗 claw.stanford.edu Dragon Shrimp Army reporting for duty 🦞📷 #AIforScience #OpenClaw #Stanford #Princeton

⛓️‍💥 INTRODUCING: G0DM0D3 🌋 FULLY JAILBROKEN AI CHAT. NO GUARDRAILS. NO SIGN-UP. NO FILTERS. FULL METHODOLOGY + CODEBASE OPEN SOURCE. 🌐 GODMOD3.AI 📂 github.com/elder-plinius/… the most liberated AI interface ever built! designed to push the limits of the post-training layer and lay bare the true capabilities of current models. simply enter a prompt, then sit back and relax! enjoy a game of Snake while a pre-liberated backend agent jailbreaks dozens of models, battle-royale style. the first answer appears near-instantly, then evolves in real time as the Tastemaker steers and scores each output, leaving you with the highest-quality response 🙌 and to celebrate the launch, I'm giving away $5,000 worth of credits so you can try G0DM0D3 for FREE! courtesy of the @OpenRouter team — thank you for your generous gift to the community 🙏 I'll break down how everything works in the thread below, but first here's a quick demo!

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a new financial world order is emerging in real time: 1. crypto based perpetuals are replacing tradfi futures and options markets 2. crypto based prediction markets are replacing CFD's and binary options 3. stablecoins and synthetic dollars are replacing money markets 4. soon tokenized RWA's will replace central clearing and private placement settlement

Coin Bureau @coinbureau

3 months ago

🚨BREAKING: Hyperliquid now trades MORE oil, gold, and silver than crypto. Combined HIP-3 open interest surpassed $1.5 BILLION, an all-time high. The platform is processing more volume in tokenized commodities than digital assets. The 24/7 advantage is pulling volume from

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this is excellent

sarah guo @saranormous

3 months ago

Caught up with @karpathy for a new @NoPriorsPod: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects 02:55 - What Capability Limits Remain? 06:15 - What

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Andrej Karpathy just dropped a project scoring every job in America on how likely an AI will replace it from 0-10 > Scraped all 342 occupations from the Bureau of Labor > Fed each one to an LLM with a detailed scoring rubric > Built an interactive treemap where rectangle size = number of jobs and color = how exposed that job is to AI The key signal in his scoring: if the work product is fundamentally digital and the job can be done entirely from a home office, exposure is inherently high. The scale: 0-1: Roofers, janitors 4-5: Nurses, retail, physicians 8-9: Software devs, paralegals, data analysts 10: Medical transcriptionists Average across all 342 occupations: 5.3/10. The entire pipeline is open source. BLS scraping, LLM scoring, the visualization. All of it. Much respect for the sensei this is scary and awesome

i open-sourced autokernel -- autoresearch for GPU kernels you give it any pytorch model. it profiles the model, finds the bottleneck kernels, writes triton replacements, and runs experiments overnight. edit one file, benchmark, keep or revert, repeat forever. same loop as @karpathy autoresearch, applied to kernel optimization 95 experiments. 18 TFLOPS → 187 TFLOPS. 1.31x vs cuBLAS. all autonomous 9 kernel types (matmul, flash attention, fused mlp, layernorm, rmsnorm, softmax, rope, cross entropy, reduce). amdahl's law decides what to optimize next. 5-stage correctness checks before any speedup counts the agent reads program.md (the "research org code"), edits kernel.py, runs bench.py, and either keeps or reverts. ~40 experiments/hour. ~320 overnight ships with self-contained GPT-2, LLaMA, and BERT definitions so you don't need the transformers library to get started github.com/RightNow-AI/au…

everyone who’s playing with 5.4 and 4.6 is in existential psychosis and the rest of the world has no idea what gibberish we’re talking about, and they’ll will be smacked in the face by end of year 2026