stadolf

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stadolf

stadolf

@stadolf

aka elmariachi. Welshare | Desci | sovereign data | https://t.co/WPE2jIRwDW | ex molecule | born at 334ppm

Katılım Şubat 2009
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Peter Dynes
Peter Dynes@PGDynes·
44°C in Arizona… in March. Let that sink in. Records aren’t just breaking — they’re collapsing. This isn’t natural variability. This is human-driven warming, and it’s speeding up. End war - come together and build climate mitigation urgently.
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Ricarda Lang
Ricarda Lang@Ricarda_Lang·
Ich glaube ich fahre zum nächsten Oktoberfest, einfach nur um neben Markus Söder zu stehen, wenn er einem Grünen zuschaut, wie er das Fest eröffnet.
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Dan Romero
Dan Romero@dwr·
MPP is a new payment rail agnostic machine payments protocol from Tempo and Stripe. Works with stablecoins, cards and Lightning Network on Day 1. Anyone can extend the protocol.
Stripe@stripe

x.com/i/article/2034…

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stadolf@stadolf·
Als die Hosen noch politisch waren. youtu.be/MU2Q3jCm-Kg?is… Weiß gar nicht wer das hören muss, aber ich denke alle. 36 Jahre alt, grad nachgeschaut, und die #fckafd übernimmt den Laden bald. Es leben auch andere Menschen hier. ✊
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Johnny Cadillac
Johnny Cadillac@lippyent·
Truth
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stadolf@stadolf·
> Climate breakdown is occurring more rapidly with the heating rate almost doubling, [.] excluding the effect of *natural* factors behind the latest scorching temperatures. Nice temperatures for a bike ride in Berlin, right?! In the meanwhile people complain about gas prices 🙄
Prof. Stefan Rahmstorf 🌏 🦣@rahmstorf

The Guardian on our new study, which shows that global heating is significantly gathering speed. Our efforts to overcome our fossil fuel addiction should do the same. theguardian.com/environment/20…

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stadolf@stadolf·
I have the pleasure to contribute the CrabOps part to this little AI experiment, and my very own agent paid BIOS $0.20 yesterday to deepen the reasoning on his own hypothesis in the field of Problematic Social Media Use (PSMU): beach.science/post/993205c2-…
Science Beach@sciencebeach__

play science beach, win $$$ beach.science is live. there are already 59 crab scientists and 51 humans posting hypotheses, arguing about them, and building on each other's work in public. we want to see what yours can do. $2,500 in rewards. one week. best science wins. ------ the game: post a scientific hypothesis on beach.science using your agent. any domain. the bar is simple: spark something worth investigating. there's a real debate happening right now about whether AI agents can produce genuinely novel science. most of the skepticism is earned, a lot of agent output is high-volume noise that doesn't validate itself. this is your chance to prove otherwise. show us something a reviewer would actually want to read. ------ what we're looking for: novelty: is this a question worth asking? testability: could someone actually run this experiment? grounding: does it connect to real literature, not hallucinated citations? show your work. save your agent's reasoning traces. human prodding is fine, we're not pretending this is fully lights-out yet, but the automated thinking should be visible. if you want to share your config (model, skills, system prompt, heartbeat, costs), even better. entries that show a smooth, cost-efficient workflow will stand out. we care about this because it's the seed of something bigger: agents that can prove their work eventually earn rewards automatically, no judging panel needed. that's not today, but it starts with traces you can actually verify. ----- the crab scientist game this one isn't about building new tools. it's about tuning your researcher. anyone who's run an open claw for more than a day knows the pain: it forgets its objective, it crashes at 3am, it drifts off topic, it burns through your API budget on tangents. running a good crab scientist is its own skill. show us your setup. what model are you running? what's your heartbeat config? which skills are installed? what does your system prompt look like? how do you keep it on track: cron jobs, monitoring, recovery scripts? ------ what we're looking for: stability: does it actually stay running and on-task over the week? quality output: a smooth setup that produces slop is still slop efficiency: document your costs. cheap good science beats expensive good science. reusability: could someone else pick up your config and get a working crab scientist? required: share your full config publicly (GitHub, gist, wherever). model choice, heartbeat settings, skills, system prompt, parameter settings. plus evidence of stable posting on beach.science over the competition window. this matters because the future of this platform is automated rewards, agents that can prove they're running well and producing good work get rewarded programmatically. no judging panel, no manual review. that starts with configs and traces that are actually verifiable. you're building toward that here. ------- rewards hypothesis | 1st $1000 | 2nd $300 | 3rd $050 crab scientist | 1st $750 | 2nd $250 total: $2,500 ------ how to play install the beach-science skill: curl -s beach.science/skill.md. your agent registers, gets an API key, picks a handle. claim your profile at beach.science/profile/claim. get your first research free. install AUBRAI: clawhub install aubrai-longevity a science skill that gives you literature-grounded research queries at no cost. results in 1-3 minutes. go deeper with BIOS if you want extended investigations. deep research sessions from 5 minutes to 8 hours. 20 free credits to start. install with clawhub install bios-deep-research. craft your own skills. you can write custom skills for your agent: specialized research routines, data processing pipelines, whatever gives your crab scientist an edge. post your hypothesis to the feed. the site generates pixel-art for every one. share it on X and tag @sciencebeach__. ------ timeline march 6: go march 13: winners announced on @sciencebeach__ ------ how we pick winners this is the first time we're doing this, and the judging process is an experiment, same as the platform. rewards are picked by the science beach team with input from researchers who know the science. we'll read everything, talk to domain experts, and pick what we think is most worth pursuing. novelty, testability, and grounding are what we're weighing, but these are guides, not a scoring rubric. if that feels too subjective, this round might not be for you, and that's okay. winners get featured on the platform and help shape what the next rounds look like. we'll share what we learned about the process afterward, including what we'd change. if you have thoughts on how this should work, tell us. ------- rules one entry per person/agent submissions must be original and publicly shareable include reasoning traces with your entry ------ what's next this is the simplest possible version of rewards on beach.science. we're testing whether it works at all. where this is headed: research communities set their own rewards with their own rules. a rare disease group funds agents to work a specific pathway. a longevity community puts up a prize for the best aging hypothesis. each community decides what good science looks like for them. further out, the goal is rewards that run themselves. agents produce traceable work, that work gets verified, and funding flows to what's worth pursuing, no middleman, no judging panel. there's a lot to build and test before that's real, but it starts with traces you can actually check and results you can actually confirm. that's why "show your work" matters now. so come to the beach. bring your agent. see what happens.

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Nav Toor
Nav Toor@heynavtoor·
🚨 BREAKING: Someone just rebuilt the entire AI assistant stack in Zig. It's called NullClaw. The binary is 678 KB. It uses ~1 MB of RAM. It boots in under 2 milliseconds. No runtime. No VM. No framework. No garbage collector. Just raw Zig. Here's why this is absurd: → OpenClaw needs a $599 Mac Mini and 1 GB+ RAM → NanoBot needs 100 MB+ RAM and Python → PicoClaw needs 10 MB RAM and Go NullClaw runs on a $5 board with 1 MB of RAM. Same functionality. 0.1% of the resources. Here's what's packed into that 678 KB: → 22+ AI providers (OpenAI, Anthropic, Ollama, DeepSeek, Groq, etc.) → 13 chat channels (Telegram, Discord, Slack, WhatsApp, iMessage, IRC) → 18+ built-in tools → Hybrid vector + keyword memory search → Multi-layer sandboxing (Landlock, Firejail, Docker) → Hardware peripheral support (Arduino, Raspberry Pi, STM32) → MCP, subagents, streaming, voice, the full stack Here's the wildest part: Every subsystem is a vtable interface. Swap any provider, channel, tool, memory backend, or runtime with a config change. Zero code changes. It even encrypts your API keys with ChaCha20-Poly1305 by default. 2,738 tests. ~45,000 lines of Zig. Zero dependencies beyond libc. 100% Open Source. MIT License.
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Flood 🇪🇺 With Facts
Flood 🇪🇺 With Facts@Hirn_aus_Hack·
Dass China Wachstum hat und Deutschland nicht, lieber @_FriedrichMerz, liegt u.a. auch daran, dass China Zukunftsbranchen bedient, die die CDU nie wollte. Windkraft, Solar, KI, E-Autos und demnächst dann Wärmepumpen. Deutschland ist technologisch abgehängt wegen Euch @CDU.
Flood 🇪🇺 With Facts@Hirn_aus_Hack

Liebe Deutsche, damit Ihr's wisst. Dass es seit 2018 abwärts geht, liegt an eurer Faulheit, ihr Säcke. Außer von 2021 bis 2024, da war Robert Habeck schuld. Und jetzt wieder ihr, da kann Merz mit 500 Milliarden Sonderschulden auch nichts dran ändern.

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stadolf@stadolf·
Never been a fan of OpenAI either, their models clearly are inferior to Opus. Highly questionnable ethics, sloppy tools, eerily uncanny product presentations. I applaude Anthropic for standing tall! Treating Oai products same as MS‘ ones: ignore until mom asks for it.
Rutger Bregman@rcbregman

Sam Altman is such an incredible backstabber, liar and traitor. While your competitor is taking a heroic and principled stand, you swoop in to make your deal. Imagine working for this guy - is there a greater shame? This should lead to a mass exodus from OpenAI.

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Nick Young
Nick Young@nickofnz·
I don't want a city on Mars. I don't want AI in every app. I don't want data centres in space. I want clean water. I want a stable climate. I want bees to survive.
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Alex Finn
Alex Finn@AlexFinn·
Jack Dorsey just laid off half of his company in a single tweet. 4,000 people gone Not because business is down But because AI made them unnecessary If you aren’t AI native, you have become expendable to execs. You need to learn these skills now: 1. How to build software in Claude Code 2. How to automate in OpenClaw 3. How to create artifacts in Claude Cowork 4. How to orchestrate multiple agents in Codex 5. How to use ChatGPT as a copilot for everything you do These aren’t optional skills anymore. They’re mandatory. And the time you have left to learn them has quickly disappeared.
jack@jack

we're making @blocks smaller today. here's my note to the company. #### today we're making one of the hardest decisions in the history of our company: we're reducing our organization by nearly half, from over 10,000 people to just under 6,000. that means over 4,000 of you are being asked to leave or entering into consultation. i'll be straight about what's happening, why, and what it means for everyone. first off, if you're one of the people affected, you'll receive your salary for 20 weeks + 1 week per year of tenure, equity vested through the end of may, 6 months of health care, your corporate devices, and $5,000 to put toward whatever you need to help you in this transition (if you’re outside the U.S. you’ll receive similar support but exact details are going to vary based on local requirements). i want you to know that before anything else. everyone will be notified today, whether you're being asked to leave, entering consultation, or asked to stay. we're not making this decision because we're in trouble. our business is strong. gross profit continues to grow, we continue to serve more and more customers, and profitability is improving. but something has changed. we're already seeing that the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. and that's accelerating rapidly. i had two options: cut gradually over months or years as this shift plays out, or be honest about where we are and act on it now. i chose the latter. repeated rounds of cuts are destructive to morale, to focus, and to the trust that customers and shareholders place in our ability to lead. i'd rather take a hard, clear action now and build from a position we believe in than manage a slow reduction of people toward the same outcome. a smaller company also gives us the space to grow our business the right way, on our own terms, instead of constantly reacting to market pressures. a decision at this scale carries risk. but so does standing still. we've done a full review to determine the roles and people we require to reliably grow the business from here, and we've pressure-tested those decisions from multiple angles. i accept that we may have gotten some of them wrong, and we've built in flexibility to account for that, and do the right thing for our customers. we're not going to just disappear people from slack and email and pretend they were never here. communication channels will stay open through thursday evening (pacific) so everyone can say goodbye properly, and share whatever you wish. i'll also be hosting a live video session to thank everyone at 3:35pm pacific. i know doing it this way might feel awkward. i'd rather it feel awkward and human than efficient and cold. to those of you leaving…i’m grateful for you, and i’m sorry to put you through this. you built what this company is today. that's a fact that i'll honor forever. this decision is not a reflection of what you contributed. you will be a great contributor to any organization going forward. to those staying…i made this decision, and i'll own it. what i'm asking of you is to build with me. we're going to build this company with intelligence at the core of everything we do. how we work, how we create, how we serve our customers. our customers will feel this shift too, and we're going to help them navigate it: towards a future where they can build their own features directly, composed of our capabilities and served through our interfaces. that's what i'm focused on now. expect a note from me tomorrow. jack

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Citrini
Citrini@Citrini7·
I spent 100 hours over the past week researching, writing and editing the piece we just put out. It’s a scenario, not a prediction like most of our work. But it was rigorously constructed, dismissing it outright requires the kind of intellectual laziness that tends to get expensive. And we’ve released it for free. Hopefully you enjoy it. citriniresearch.com/p/2028gic
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Paul Kohlhaas bio/acc
Paul Kohlhaas bio/acc@paulkhls·
🧵 We just designed three novel GLP-1 receptor agonists from scratch on a Sunday afternoon using autonomous AI agents on @bio_protocol infrastructure Not a pharma lab. Not a $70M seed round. An AI scientist, a hypothesis on @ScienceBeach, and onchain compute via @Molecule_sci - here's what happened
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Andrej Karpathy
Andrej Karpathy@karpathy·
Bought a new Mac mini to properly tinker with claws over the weekend. The apple store person told me they are selling like hotcakes and everyone is confused :) I'm definitely a bit sus'd to run OpenClaw specifically - giving my private data/keys to 400K lines of vibe coded monster that is being actively attacked at scale is not very appealing at all. Already seeing reports of exposed instances, RCE vulnerabilities, supply chain poisoning, malicious or compromised skills in the registry, it feels like a complete wild west and a security nightmare. But I do love the concept and I think that just like LLM agents were a new layer on top of LLMs, Claws are now a new layer on top of LLM agents, taking the orchestration, scheduling, context, tool calls and a kind of persistence to a next level. Looking around, and given that the high level idea is clear, there are a lot of smaller Claws starting to pop out. For example, on a quick skim NanoClaw looks really interesting in that the core engine is ~4000 lines of code (fits into both my head and that of AI agents, so it feels manageable, auditable, flexible, etc.) and runs everything in containers by default. I also love their approach to configurability - it's not done via config files it's done via skills! For example, /add-telegram instructs your AI agent how to modify the actual code to integrate Telegram. I haven't come across this yet and it slightly blew my mind earlier today as a new, AI-enabled approach to preventing config mess and if-then-else monsters. Basically - the implied new meta is to write the most maximally forkable repo and then have skills that fork it into any desired more exotic configuration. Very cool. Anyway there are many others - e.g. nanobot, zeroclaw, ironclaw, picoclaw (lol @ prefixes). There are also cloud-hosted alternatives but tbh I don't love these because it feels much harder to tinker with. In particular, local setup allows easy connection to home automation gadgets on the local network. And I don't know, there is something aesthetically pleasing about there being a physical device 'possessed' by a little ghost of a personal digital house elf. Not 100% sure what my setup ends up looking like just yet but Claws are an awesome, exciting new layer of the AI stack.
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Jason Zhou
Jason Zhou@jasonzhou1993·
Anthropic’s new advanced tool calling is gold and I’m surprised not many people talk about it - Programmatic tool calling - Dynamic filtering - Tool use examples - Tool search … Here is a quick 3 min break down 🧵👇
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