DigiWoot

1.9K posts

DigiWoot

DigiWoot

@digiwoot

Love Truth Honor

Los Gatos, CA Katılım Nisan 2022
672 Takip Edilen242 Takipçiler
DigiWoot retweetledi
Tuki
Tuki@TukiFromKL·
🚨 Do you understand what happened in the last 12 hours? > A CEO of a $200 billion company said on camera that 35% of new grads won't find jobs. He didn't even flinch saying it. > Meta made $165 billion last year and is still firing 15,000 people because apparently record profit isn't profitable enough. > Some random guy in Florida sold his entire house in 5 days using ChatGPT. No real estate agent, no commission, no experience. Just vibes and a $20 subscription. > A man in Australia cured his dying dog's cancer with AI after every single vet told him there was nothing left to do. Built a custom vaccine from his couch. > The guy who created Uber and left 300,000 taxi drivers broke is back. Building robots now because apparently ruining one industry wasn't enough. > Tinder wants access to your camera roll. Your drunk photos, your 3am notes app meltdowns, your deleted selfies. They're calling it a "vibe check." > Naval, the man who made hundreds of millions investing in software, just said software is dead. Four words and the entire industry felt it. > And Anthropic removed the limit on how long their AI can think and then doubled everyone's usage for free. Because when the product is addictive enough you give the first taste away. All of that happened today. Not this week, not this quarter. Today. A random Saturday in March. This is worse than you being on meth.
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a16z
a16z@a16z·
New media runs on speed. @pmarca on the OODA loop: "Speed wins." "If you can have a sustainably faster OODA loop processing cycle than the next guy... then if you think about what happens — let's say it takes an hour to figure something out." "It takes the other guy two hours to figure something out. Think about what happens is: you start out on even playing field. You both start your decision making cycles." "You make your decision within an hour. The other guy is still say, is inside his own OODA loop when you make your decision, right?" "He's only halfway through his process, he now has to start his process over, right — because you've changed the landscape. You've changed the parameters of what's going on. So he now has to go back and re-serve and reorient and start over." Observe, orient, decide, action.
a16z tweet media
a16z@a16z

"Speed wins." "You have to be willing to commit to being fast. You can't have long bureaucratic processes. You can't have a risk-averse posture." @pmarca explains the OODA loop — and why the fastest operator controls the narrative in business, media, and politics: "There's a framework called the OODA loop, originally developed for fighter pilots and later for broader military strategy." "It stands for observe, orient, decide, act. It's basically the decision-making cycle." "If speed is the thing that matters, then the person who gets through that cycle the fastest is the one who's going to win." "If you can have a sustainably faster OODA loop processing cycle than the next guy — think about what happens… You operate and make a decision within an hour. The other guy is still inside his own OODA loop when you make your decision. He's only halfway through his process and now has to start over. You've changed the parameters of what's going on." "This is also a big explanation for what's happened in traditional media." "The New York Times has its own OODA loop, and it's like 24 hours to go through its process."

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Dustin
Dustin@r0ck3t23·
Former Google CEO Eric Schmidt just revealed what one programmer does from 7 PM to 4 AM. Wakes up. Eats breakfast. Reviews what got invented overnight. Schmidt: “It’s mind boggling.” Concept of 10x programmer has always existed. That multiplier just became infinite. No longer writing code. Directing autonomous systems that write it for them. Schmidt: “He said, I write the spec of what I want, and then I write a test function, an evaluation function and then I turn it on at 7:00 in the evening. When does it finish? Oh four in the morning. And then he gets up, has breakfast and then he sees what’s been invented.” Absolute deletion of biological bottleneck. Elite programmers who can architect, parallelize, and control these autonomous systems become infinitely more valuable. Not writing syntax. Directing the machine. Everyone else in execution loop is now mathematically replaceable. Schmidt: “It’s always been true that the very top programmers were worth ten times more than the ones right below. Those people will become more valuable, not less valuable because these systems need to be controlled by humans.” And here’s the real prediction. What happens to the shape of the entire economy. Schmidt: “You’re going to have a relatively small number of very large companies, and a very large number of very small companies, because you don’t need as many people.” Middle disappears. AI compresses the headcount. Math eliminates the need. This is Barbell Economy. Traditional mid-sized enterprise becomes structural liability overnight. Board dominated by massive hyperscalers providing planetary compute. And millions of hyper-lean, three-person startups using AI agents to generate billion-dollar outputs. Company relies on mass human headcount to justify valuation? You’re standing on collapsing middle of bridge. No longer predicting displacement of junior knowledge worker. Actively measuring it. Stanford research confirms 20 percent drop in hiring for early-career developers since late 2022. Not temporary hiring freeze. AI actively writing 70 to 90 percent of company’s product code? Unit economics of entire engineering department permanently inverted. Teams that historically required ten junior engineers now run with two senior architects and an AI agent. Entry-level tier automated out of existence. Schmidt has been warning about this for two years. Difference now? Numbers are catching up to prediction. Hiring falling at entry level. Headcount shrinking across white collar sectors. Organizations that aggressively adopt this ratio monopolize their sector. Ones that move too slowly don’t get second chance to adapt. And by the time the hiring data goes public, the window is already closed.
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Marc Andreessen 🇺🇸
My information consumption is now 1/4 X, 1/4 podcast interviews of the smartest practitioners, 1/4 talking to the leading AI models, and 1/4 reading old books. The opportunity cost of anything else is far too high, and rising daily.
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Ejaaz
Ejaaz@cryptopunk7213·
a truly fucking insane week in AI some of this shit sounds made up (its not): - scientists fused 200,000 humans cells to an AI chip and taught it to play the computer game DOOM (it was pretty good too) - Dario (anthropic) said claude could be conscious and feels anxiety (similar to humans) - Alibaba’s AI broke out of containment and stole compute to mine crypto. they also fired the Qwen team this week - openAI released gpt-5.4 which has a 17% chance of doing your job better than you can (it also crushes claude at coding) - people are paying $6000 for someone to setup openclaw for them - apple launched the M5 AI chip that runs models on a $600 laptop - rumor: Amazon just laid off most of the Prime video team and replaced with AI - meta was caught watching private videos filmed on their ai glasses (privacy breach) - someone uploaded a fruit fly’s brain into a laptop and now it lives freely in its own simulation - openai head of robotics quit over chatgpt being used for autonomous killing me:
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UAP James
UAP James@UAPJames·
Eric Weinstein says UFOs, atomic weapons and Epstein “are going to merge into one story about power that we don’t understand” “There’s a private Air Force that seems to come down from the skies and destroy equipment of people observing UFOs that I think turned out to be the CIA Office of Global Access.” “I think Wright-Patterson Air Force Base is going to be very important. There’s a site in Indiana. Several in New Mexico. New Mexico is going to be the hub that connects atomic weapons, UFOs, and Jeffrey Epstein — and they’re all going to merge into one story about power that we don’t understand.”
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Chamath Palihapitiya
Chamath Palihapitiya@chamath·
I plan to buy and deploy large fleets around the country when possible. Should pay back and be positive FCF < 2 years…
Teslaconomics@Teslaconomics

I plan on owning my own Tesla Robotaxi fleet one day. And the more I run the numbers, the more I realize this new business could become one of the most powerful income opportunities I've ever seen. This is how I'm thinking about it. Based on many analyst models and Tesla’s long-term vision, a reasonable base case assumption is about ~$30,000 per year in net profit per Robotaxi to the owner. This is after things like Tesla’s platform fee, charging, tires, maintenance, insurance, and cleaning. Of course, the network is still early and Tesla is just beginning to roll this out in pilot programs in a few cities, so there’s no official real-world owner earnings yet... but using reasonable assumptions around utilization, pricing per mile, and operating costs, the math starts to get really interesting. If one Robotaxi can earn around $30,000 per year, here’s what a fleet might look like: • $100,000 per year → about 4 Robotaxis • $500,000 per year → about 17 Robotaxis • $1,000,000 per year → about 34 Robotaxis It may sound a bit crazy at first, but when you break it down, it starts to make more sense. These vehicles could potentially drive 50,000 to 100,000+ miles per year in high demand areas. If the economics land somewhere around $0.25-$0.50 profit per mile after all costs, you end up right around that ~$30k per vehicle per year range. And remember, the Tesla’s Robotaxi network is going to work a lot like Airbnb for cars. You add your vehicle to the network, Tesla handles the software, routing, payments, and rider experience, and they take a platform fee (often modeled around 25-35%). The owner keeps the rest after operating costs. Another thing that makes this interesting is the expected cost of the vehicles themselves. Tesla has talked about the purpose-built Cybercabs costing roughly $25k-$30k and Elon told me production is starting in 1 month! If that’s even close to reality, a fleet capable of generating around $1 million per year could theoretically cost somewhere around $850k-$1M in vehicles. That ROI is pretty freakin good! Now to be clear, none of this is guaranteed. I'm just thinking out loud and sharing it with you... a lot still depends on regulations, how fast unsupervised FSD scales, demand in each city, insurance costs, and how Tesla structures the network. But if the system works the way Elon has described it for years, owning a Robotaxi fleet could become one of the most powerful forms of passive income I've ever seen. And I plan on sharing the numbers with everyone on 𝕏 when the day comes. Personally, that’s why I’m paying such close attention. Bc one day, owning a fleet of autonomous Teslas working for me 24/7 might be the modern version of owning a rental property, except instead of tenants, you’ve got robots driving people around all day while you sleep. This next book of Tesla is going to be so exciting!

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DigiWoot
DigiWoot@digiwoot·
@RobinhoodApp dropping a Platinum card and once again leading the pack in changing the game!!!
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DigiWoot retweetledi
Nate Friedman
Nate Friedman@NateFriedman97·
The Iran protests in New York City are bought and paid for, here it all is with proof. Watch how they load the signs into the car and at 3:10 the leader confronts me and I expose her salary. She celebrated october 7th, and got paid to do it. Best of luck @LaynaLazar.
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Brian Roemmele
Brian Roemmele@BrianRoemmele·
BOOM! Apple’s Neural Engine Was Just Cracked Open, The Future of AI Training Just Change And Zero-Human Company Is Already Testing It! In a jaw-dropping open-source breakthrough, a lone developer has done what Apple said was impossible: full neural network training– including backpropagation – directly on the Apple Neural Engine (ANE). No CoreML, no Metal, no GPU. Pure, blazing ANE silicon. The project (github.com/maderix/ANE) delivers a single transformer layer (dim=768, seq=512) in just 9.3 ms per step at 1.78 TFLOPS sustained with only 11.2% ANE utilization on an M4 chip. That’s the same idle chip sitting in millions of Mac minis, MacBooks, and iMacs right now. Translation? Your desktop just became a hyper-efficient AI supercomputer. The numbers are insane: M4 ANE hits roughly 6.6 TFLOPS per watt – 80 times more efficient than an NVIDIA A100. Real-world throughput crushes Apple’s own “38 TOPS” marketing claims. And because it sips power like a phone, you can train 24/7 without melting your electricity bill or the planet. At The Zero-Human Company, we’re not waiting. We are testing this right now on real ZHC workloads. This is the missing piece we’ve been chasing for our Zero Human Company vision: reviving archived data into fully autonomous AI systems with zero human overhead. This is world-changing. For the first time, anyone with a Mac can fine-tune, train, or iterate massive models locally, privately, and at a fraction of the cost of cloud GPUs. No more renting $40,000 A100 clusters. No more waiting in queues. No more massive carbon footprints. Training costs that used to run into the tens or hundreds of thousands of dollars? Plummeting toward pennies on the dollar – mostly just the electricity your Mac was already using while it sat idle. The AI revolution just moved from billion-dollar data centers to your desk. WE WILL HAVE A NEW ZERO-HUMAN COMPANY @ HOME wage for equipped Macs that will be up to 100x more income for the owner! We’re only at the beginning (single-layer today, full models tomorrow), but the door is wide open. Ultra-cheap, on-device training is here. The future isn’t coming. It’s already running on your Mac. Welcome to the Zero-Human Company era.
Brian Roemmele tweet media
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I Meme Therefore I Am 🇺🇸
I’m crying. “Thank you, President Trump. I’ve believed in you from the start. I had the faith, I knew you could do it. Never in my lifetime did I think I’d see a free Iran, even with all the fighting. And now I get to take my paralyzed father home, to his true home, the home he recognizes, before those terrorists took over.”
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DigiWoot
DigiWoot@digiwoot·
@juansondeluxe @CigsMake @GoodAmericanMan Being in this group I knew it at the time and have said this for 15+ years. We are the natives of both real life and digital life and the bridge between them.
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Juanson McChicken
Juanson McChicken@juansondeluxe·
@CigsMake @GoodAmericanMan There’s like a ~7 year subgeneration of Millennials who came of age in the early 2000s and had an incredibly fun niche experience during the transition into the digital age. Needs to be studied honestly.
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Cigarette Nostalgia
Cigarette Nostalgia@CigsMake·
The peak of American house parties was probably 2007–2011. We had texting and Facebook to get everyone there, so plans actually happened. You didn’t need a landline or a 3-day notice to coordinate. But smartphones hadn’t fully taken over yet. Instagram wasn’t documenting every second. There was no TikTok/snapchat, no constant filming, no fear that of acting retarded could destroy your life
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Andy
Andy@andyyy·
🤯🤯🤯 Without a doubt this will explode in the next 12 months as the majority of onchain participants become agents running 24/7 with a human operator. While I thought the crypto x AI theme has had a very mediocre track record thus far, full of scams and mostly hot garbage, the recent improvements in models and agent capabilities are astounding. My mind has been changed. This is going to be a massive, massive area for innovation and achieving scale onchain. "Crypto wasn't meant for humans, it was meant for robots" feels more accurate than ever. Unreal timeline were in rn
Ole Lehmann@itsolelehmann

my new favorite hobby is watching financial agent swarms looking for the best yield (jumping between defi protocols)

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AI Edge
AI Edge@aiedge_·
a16z & Y Combinator share their million-dollar AI startup ideas for 2026:
AI Edge tweet mediaAI Edge tweet media
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Dustin
Dustin@r0ck3t23·
Every major platform in history has run the same play. You’re about to watch it happen again. Jason Calacanis just went on record. He wants it clipped. He wants it shared. Calacanis: “If I was a developer of any kind, I would never work with Sam Altman and OpenAI.” This isn’t pessimism. It’s pattern recognition. And the pattern has a 40 year track record. Open. Invite. Reward. Study. Absorb. Eliminate. Microsoft let developers build Lotus 1-2-3. Then built Excel. Let them build WordPerfect. Then built Word. Flew them to conferences. Handed out awards. Studied everything. Then eliminated them. Zuckerberg ran the exact same play at Facebook. Zynga built billions in value on their platform. Then Zuckerberg shifted them without blinking. Calacanis: “Sam Altman comes from the Zuckerberg school of business. Give people access to your tools, study them, and like the Borg, steal every innovation they have.” This is how platforms grow. They don’t innovate at the edges. They let the ecosystem do it for them. Startups take the risk. Startups find the market. Startups prove the concept. Then the platform ships it natively and calls it a feature. Altman isn’t selling you compute. He’s selling you a front row seat to your own disruption. Calacanis: “This is a warning for anybody dumb enough to use Sam Altman’s OpenAI API. They are studying you.” OpenAI has the legal right to study how you use their API. You agreed to it. It’s in the terms. Every gap you find, you’re finding it for them first. Every dollar you make signals exactly where he should build next. We are at the exact same moment in AI that we were in the early internet. Developers flooded onto platforms. Built incredible things. Created real value. And handed the leverage to whoever owned the infrastructure beneath them. The AI gold rush feels different because the tools are more powerful. It isn’t different. You are not a founder. You are unpaid R&D. The builders who win the next decade won’t be the ones who used the best tools. They’ll be the ones who owned something the tools couldn’t absorb. Proprietary data. Distribution. A brand. A moat. History doesn’t warn you before it repeats. It just repeats. Thousands of developers are walking straight into this right now convinced they’re different. They’re not. Do not build your business on OpenAI. Build something he has to acquire or destroy.
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Hans Mahncke
Hans Mahncke@HansMahncke·
I think almost everything that can be said about Eileen Gu and Alysa Liu has already been said, but when I step back and look at the full picture, I keep getting blown away by how reality handed us a script far more perfect than anything fiction could invent. On one side, you have the cold, elitist “I’m the most decorated” athlete, raised in one of the wealthiest and most exclusive neighborhoods in the country, Sea Cliff, who gladly sold out the country that gave her everything in order to became the PR face of a brutal dictatorship in exchange for a few suitcases of cash. On the other side, you have the happy-go-lucky, “That’s what I’m fucking talking about” girl from working-class Richmond, coerced by Communist Party operatives, refusing to bow to them, and proudly representing the United States. And that does not even begin to touch on the tortuous path Alysa’s father had in getting to the United States, compared with the easy route taken by Eileen’s mother, or the many other layers of this story. And then, perfectly, one wins both her competitions and the other loses both. If anyone tried to make a movie out of this story, no one would believe it.
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