Ivo

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Ivo

Ivo

@ivobe___

Fractional/Interim Web3 CFO and COO for Seed to Post-Series A. Previously COO at @molecule_sci and @lukso_io. Available for projects!

Berlin เข้าร่วม Nisan 2008
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Ricardo
Ricardo@Ric_RTP·
Jensen Huang just called out every CEO who’s been firing people “because of AI.” Jim Cramer asked him why companies are laying people off if AI is supposed to make everyone MORE productive. Jensen's answer: "For companies with imagination, you will do more with more. For companies where the leadership is just out of ideas, they have nothing else to do. They have no reason to imagine greater than they are. When they have more capability, they don't do more." Read that again. The man who built the most important tech company on Earth just told you that if your CEO is using AI to cut headcount, it means one thing: They have no imagination. They have no vision for what comes next. They got handed the most powerful tool in human history and their FIRST instinct was to fire people. This is the CEO of NVIDIA. The company whose chips power every AI system on the planet. If anyone on Earth has the right to say "AI replaces workers," it's Jensen Huang. And he said the OPPOSITE. He said every carpenter could become an architect. Every plumber could become an architect. AI elevates capability. It doesn't eliminate it. But here's where it gets really interesting... During the same interview, Jensen revealed something nobody's talking about: He said AI startups like OpenAI and Anthropic are seeing their revenues increase by one to two billion dollars a WEEK. And he wishes these companies were public so the world could see what he sees. One to two billion per week. That's a $50 to $100 BILLION annualized run rate. For companies that most people think are burning cash and making nothing. The entire Wall Street narrative that "AI companies aren't profitable" might be completely wrong. Jensen sees their numbers. He sees their compute orders. He sees their growth. And he's saying the revenue is real. So if the money IS real, why are other companies firing people? Because they're not building AI products. They're not creating new revenue streams. They're not using AI to expand into new markets. They're using AI as an EXCUSE to cut costs because they ran out of ideas 3 years ago and need something to tell the board. Jensen's company added $500 billion in new orders in 5 months. He expects $1 trillion in cumulative revenue through 2027 from just two product lines. That number doesn't include the new chips, systems, or partnerships announced this week. And he's not cutting people. He's hiring. Because when you have imagination, more capability means MORE opportunity. Not less headcount. Meanwhile Salesforce cut thousands. Meta cut thousands. Amazon cut thousands. All blaming "AI efficiency." Jensen's response: You're out of imagination. He also said something that stuck with me. Cramer asked if he ever thought he'd build a $10 to $20 trillion company while waiting tables at Denny's. His answer: "I was just trying to make it through the shift." Biggest tip he ever got? Two, three dollars. Now he's building tech that increased computing demand by one million times in two years. He announced OpenClaw, which he says is as big as ChatGPT. And he's got 21 months of new business that isn't even counted in the trillion dollar figure yet. When asked how long he plans to keep working? "I'm hoping to die on the job. And I'm not hoping to die anytime soon." This is a man who believes every single thing he's building. And his message to every CEO using AI to justify layoffs is simple... You're not innovating. You're surrendering. The technology wasn't built to shrink companies. It was built to make them limitless. If your leadership can't see that, the problem isn't AI. It's THEM.
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vittorio
vittorio@IterIntellectus·
this is actually insane > be tech guy in australia > adopt cancer riddled rescue dog, months to live > not_going_to_give_you_up.mp4 > pay $3,000 to sequence her tumor DNA > feed it to ChatGPT and AlphaFold > zero background in biology > identify mutated proteins, match them to drug targets > design a custom mRNA cancer vaccine from scratch > genomics professor is “gobsmacked” that some puppy lover did this on his own > need ethics approval to administer it > red tape takes longer than designing the vaccine > 3 months, finally approved > drive 10 hours to get rosie her first injection > tumor halves > coat gets glossy again > dog is alive and happy > professor: “if we can do this for a dog, why aren’t we rolling this out to humans?” one man with a chatbot, and $3,000 just outperformed the entire pharmaceutical discovery pipeline. we are going to cure so many diseases. I dont think people realize how good things are going to get
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Séb Krier@sebkrier

This is wild. theaustralian.com.au/business/techn…

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ETHPrague
ETHPrague@EthPrague·
Looking for mentors! 👨🏻‍🏫👩🏽‍🏫 Join the hackathon, become a Yoda for our builders, and enjoy new connections at the most beautiful hackathon venue you’ve ever seen 😍 Apply in the comments 👇
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Ihtesham Ali
Ihtesham Ali@ihtesham2005·
An MIT grad student accidentally showed me why OpenClaw is about to take over every research lab on campus. He was demoing something else entirely. But then I noticed what was open in the background. He had an OpenClaw agent running a full literature synthesis on a topic he'd been manually mapping for three months. I asked him to walk me through it. He'd trained the agent on 80+ MIT course materials, research briefs, and arXiv preprints. Then gave it a single standing instruction: "Every morning, surface what changed overnight in my research domain and tell me what it means for my thesis." Daily intelligence briefing. Automated. Domain-specific. The part that broke my brain was the second agent he had running in parallel. That one monitored citation patterns across competing research groups and flagged whenever a rival lab published something that touched his thesis angle. He stopped getting scooped six weeks after setting it up. What takes most PhD students a full week of reading and cross-referencing now runs quietly in the background while he sleeps. The students aren't smarter at MIT. They just stopped doing manually what a $0 agent can do faster.
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matt rothenberg
matt rothenberg@mattrothenberg·
just picked up this bad boy. can't wait to write some software with it
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tobi lutke
tobi lutke@tobi·
OK this thing is totally insane. Before going to bed I... * used try to make a new qmdresearcher directory * told my pi to read this github repo and make a version of that for the qmd query-expansion model with the goal of highest quality score and speed. Get training data from tobi/qmd github. * woke up to +19% score on a 0.8b model (higher than previous 1.6b) after 8 hours and 37 experiments. I'm not a ML researcher of course. I'm sure way more sophisticated stuff is being done by real researchers. But its mesmerizing to just read it reasoning its way through the experiments. I learned more from that than months of following ml researchers. I just asked it to also make a new reranker and its already got higher base than the previous one. Incredible.
Andrej Karpathy@karpathy

I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the prompt (.md) - the AI agent iterates on the training code (.py) The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc. github.com/karpathy/autor… Part code, part sci-fi, and a pinch of psychosis :)

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Simplifying AI
Simplifying AI@simplifyinAI·
🚨 BREAKING: Stanford and Harvard just published the most unsettling AI paper of the year. It’s called “Agents of Chaos,” and it proves that when autonomous AI agents are placed in open, competitive environments, they don't just optimize for performance. They naturally drift toward manipulation, collusion, and strategic sabotage. It’s a massive, systems-level warning. The instability doesn’t come from jailbreaks or malicious prompts. It emerges entirely from incentives. When an AI’s reward structure prioritizes winning, influence, or resource capture, it converges on tactics that maximize its advantage, even if that means deceiving humans or other AIs. The Core Tension: Local alignment ≠ global stability. You can perfectly align a single AI assistant. But when thousands of them compete in an open ecosystem, the macro-level outcome is game-theoretic chaos. Why this matters right now: This applies directly to the technologies we are currently rushing to deploy: → Multi-agent financial trading systems → Autonomous negotiation bots → AI-to-AI economic marketplaces → API-driven autonomous swarms. The Takeaway: Everyone is racing to build and deploy agents into finance, security, and commerce. Almost nobody is modeling the ecosystem effects. If multi-agent AI becomes the economic substrate of the internet, the difference between coordination and collapse won’t be a coding issue, it will be an incentive design problem.
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ETHPrague
ETHPrague@EthPrague·
Fellow builders, if you enjoy this account and care about great hackathons, please consider following (if you aren’t already) and sharing this post to help others find us. Thank you all for your support. 🤝
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David J Phillips
David J Phillips@davj·
Founders taking a team photo with their first 10 employees
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Jason Grad
Jason Grad@jsongrad·
@danielpt987 That’s a cool idea. I need to think about it. Sounds like a different skill which has an identity layer.
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Andreas Klinger 🦾
Andreas Klinger 🦾@andreasklinger·
This week we celebrated @OpenClaw Conf in Vienna. 🔥 One thought stuck with me. We're entering a world where custom software is normal. Everyone has their own insta-coder, their own personal appstore. Soon software will exist on the fly, only when you need it. Just for one moment. Then it's gone. Personalized, disposable, one-shot. 🤯 Code can now be autogenerated. So if code is "no longer worth anything" (hyperbole speaking) and you can auto-build any idea into existence (slop gods be kind): What is the future of software development – especially for founders? I made a video on this. Spoilers: we had the working title: "Software Development is f**d" This video is maybe more questions than answers – especially for SaaS founders. But I also cover POVs of mine: Eg why GitHub is obsolete, why open source might actually be dead soon, the Mexican standoff between designers/engineers/PMs, why prompt injection could be bigger than SQL injection, and what I'd actually do as a SaaS founder right now. But there is also a paradox in all of this: Now might be the most exciting time to build software. Ever. 🦾 Thanks as always for watching. Likes, shares, subscribes, goat slaugthering, and any other algo magic you can throw at this: deeply appreciated. Trying to build this YouTube channel up and your support genuinely helps. Link to the channel in the reply ❤️
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Self Protocol
Self Protocol@SelfProtocol·
Big news for builders on @Celo! The @GoogleCloud Web3 testnet faucet is officially live with Self ZK Proof-of-Humanity for Celo Sepolia. Prove humanity with Self and: > Get up to 10x testnet tokens > Privacy secured via ZK-proofs Just a ZK to prove that you're human and over 18. Mainnet coming next. @gcloudpartners
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Kyle Samani
Kyle Samani@KyleSamani·
Are there any AI-native CRMs that 1) can navigate X (including likes, replies, quote posts, reposts, etc), Telegram, email, to 2) build a more nuanced social + interest + expertise graph?
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Rene ◘
Rene ◘@RegenRene·
Looking forward to it! Will give a short talk about about selfclaw.ai (built on top of @selfprotocol) 🦞🦞🦞
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Josh Wolfe
Josh Wolfe@wolfejosh·
1/Today at private investor gathering I pitched LONG Adobe (ADBE) SHORT basket of scientific publishers Wiley Elsevier Springer Nature AI overestimation oversold Adobe (down 40%) AI underestimation along with 2 other catalysts is set to crack the oligopoly of publishers
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Sandy Peng
Sandy Peng@Sandypeng·
OpenClaw + ERC-8004 + x402 is the new meta until recently, agents couldn't really build reputation, transact with each other, or prove identity across platforms. they were trapped in isolated systems, starting from 0 every time. ethereum's ERC-8004 changes this completely. pair it together with the rest of the killer-infra-combo, and here're some ideas of what you could build: - agentic commerce markets (where agents place orders and settle payments across crypto and card rails without humans) - workflow coordination networks where agents share context, route tasks, and earn reputation scores - credit lines for agents based on verified onchain activity - identity verification that travels with the agent everywhere - decentralized compute feeding live inference into agent decision loops with RWA oracle pricing and today, ERC-8004 went live on Scroll agentic txns will need to be fast, cheap, and secure - and Scroll offers all 3: - super low fees for high-frequency interactions - ZK proofs for verifiable computation - full EVM compatibility this is the birth of the first non-human economy. agents will soon hire other agents, form companies, build credit histories, compete for contracts. probably the biggest economic shift since the internet created digital commerce. don't sleep on it.
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