When Steve Jobs bought Siri for $200M before the world understood why (2010) https://t.co/bzmsUUmzWC

Built an MCP server so AI agents like Poke @interaction and @openclaw can read my Oura ring data Integrates into my day and I never have to check the app The future is your wearable talking directly to your assistant https://t.co/llwtJqr7fm

It really is incredible how wrong the mainstream media has been with their skeptical AI takes over the past three years, while giving awards to the same AI tech journalists whose predictions and takes have been categorically off the mark. Now it looks like they are all going to be wrong again during this current exponential AI agentic compute demand liftoff. Amazing.

this might be the wildest growth hack i’ve seen in a minute met the founder of rent a human yesterday. he’s on stage doing a demo, asks for users… i raise my hand 30 seconds later someone in japan is about to stand in the busiest crossroad holding a sign for finlingo this isn’t even a joke. this is global distribution on demand this will actually kill fiverr. 730k users in a month… is insane. not gonna lie i went on rent a human and dropped a bunch of $1 bounties for reddit posts just to get people talking about finlingo 😭 i’ll post the results in a couple days shoutout to @AlexanderTw33ts this is actually insane 🚀

我人傻了。 我的小龙虾，已经可以跟我开视频会议了。 Pika AI Self 可以直接进 Google Meet— 带脸、带声、带表情，边聊边干活： 约会 查资料 现场参与讨论 还能记住你的风格，越用越像你。 视频里那个 Shiro AI， 3 秒帮老板约好会， 还能 4 人一起认真辩论： “sandwich 算不算 hot dog？” 这已经不是助手了， 是能开会的数字同事。 还在 Beta， 但已经支持任意 agent（GitHub 一键接入）， Pika 的 AI Self，是真的猛。 我只想说一句： 以后那些发邮件就能解决的会， 能不能都让 AI 去开。

slime molds are one of the coolest organisms ever btw In order to optimally transport nutrients, they've basically learned to solve the shortest path problem. Scientists have leveraged this behavior to do cool things, like replicating the US Interstate Highway system and building unconventional computing applications. On a personal note, I remember I was introduced to slime molds in my college botany class. One of our projects was to grow slime molds, and I was so fascinated I kept growing them for like a year after the class ended, trying to replicate some of these interesting behaviors. It was like a pet for me lol

Fortifying #Cloud Security Operations with #AI Driven Threat Detection https://t.co/2NQ9gg5vKu @DZoneInc #CyberSecurity Cc @roxananasoi @jblefevre60 @BroadenView @SpirosMargaris @TamaraMcCleary @LaurentAlaus https://t.co/imin2zc4lx

Steve Jobs once called Warren Buffett for advice on stock buybacks. Buffett told Jobs—“There’s just 2 questions” to ask: 1. Do you have enough cash to build the business the way you see it over the next 5-10 years? 2. Is your stock selling for less than it’s worth? Jobs answered Yes to both. Buffett said: “Well, you’ve answered your own question.”

Demis Hassabis just described the moment medicine stops treating disease and starts deleting it from the source code. For all of human history, doctors have fought symptoms. The tumor. The organ failure. The collapse. Always downstream. Always after the damage has already started. The cause sits upstream. Written into the DNA. Ninety-eight percent of the human genome sits in non-coding regions. For decades, science understood the genes but couldn’t read the vast dark territory between them. That’s where most disease hides. Hassabis: “It takes the big, long genetic sequences and then it tries to predict, if you made a mutation to this particular single letter, single position in the genetic sequence, will that be a harmful mutation that might cause disease, or is it benign?” AlphaGenome reads your entire genetic sequence and identifies the exact letter that’s corrupted. Not a region. Not a probability range. A single position in a three-billion-letter sequence. That alone would be a generational breakthrough. But most diseases aren’t that clean. Hassabis: “What if they’re multigenic diseases where there’s cascades of mutations causing the problem? Those are even harder to detect, but actually perfect for sort of AI.” One mutation is hard enough to find. A cascade of mutations interacting across the genome is a problem no human researcher can hold in their head at once. Three billion data points. Compounding errors across all of them. The human brain cannot solve that. AI doesn’t solve it either. It maps it. All of it. At once. The most devastating diseases on Earth. The ones medicine has called untreatable for generations. They are not mysteries to the algorithm. They’re compute problems. But finding the error was only ever half the equation. You also need the ability to fix it. That tool already exists. CRISPR is a molecular scalpel. It cuts DNA at exact positions. The limitation was never the editing. It was knowing exactly where to cut. Hassabis: “A kind of combination of things like AlphaGenome and CRISPR could be incredibly powerful.” AI reads the code. CRISPR rewrites it. One finds the mutation. The other corrects it at the source. Not managing symptoms. Not slowing progression. Deleting the error from the genome. The implications go beyond treatment. A disease corrected at the genetic level doesn’t just disappear from one patient. It disappears from their bloodline. The read access is here. The write access exists. The merge is inevitable. The era of accepting a broken genetic hand is ending. We stopped being passengers in our own biology.

The Infinity Machine, a new book by CFR expert @scmallaby, follows DeepMind founder Demis Hassabis and the quest for superintelligence. Out now: https://t.co/F9edf9Wcyd

Warren Buffett: "Stick with businesses that you can understand and use the government bond rate [as the discount rate]." "When you can buy something you understand well at a significant discount, then you should start getting excited." https://t.co/WVXp5SX4OS

Jeff Bezos explains why Buffett stands out as an investor. The primary reason is that Buffet is able to think more long-term when it comes to investing. Save this to stay ahead of the curve. https://t.co/VBPZtihyVm

“I believe that 30 years from now, your kids are probably working three and a half days a week,” said JPMorgan Chase CEO Jamie Dimon. https://t.co/H1G1T5V16B https://t.co/MGzKuRt8NG

The traits that made Steve Jobs "impossible to work with" are the same traits that built Apple. https://t.co/KjKgXTcUH1

The traits that made Steve Jobs "impossible to work with" are the same traits that built Apple. https://t.co/KjKgXTcUH1

“No matter how isolated you are and how lonely you feel, if you do your work truly and conscientiously, unknown friends will come and seek you.” — Carl Jung https://t.co/BR2NBAMBPE

“The best thing a human being can do is to help another human being know more.” — Charlie Munger https://t.co/FGsbU60DVu

Even competitors are joining forces to manage AI risks. Anthropic is working with rivals like Apple and Google on Project Glasswing to test how advanced models can detect and prevent cyber threats. It marks a shift in mindset. When risks scale, collaboration becomes a necessity, not a choice. https://t.co/JTpvTqyMG6 @wired @lilyhnewman

Marc Andreessen says the four most dangerous words in investing are "this time is different." But this time it's actually different. He's referring to the AI boom when he mentioned this. For 80 years, the industry has followed the same pattern. 1) Excitement builds 2) Money pours in 3) The technology fails to deliver 4) The industry collapses. Here are 4 examples of when this happened in AI: • In 1943, the original neural network paper was written. It proved that simple mathematical models of brain cells could perform any logical computation. It was a foundational breakthrough but didn't takeoff. • In 1955, scientists got a grant to spend 10 weeks at Dartmouth and believed they could achieve AGI by the end of the summer. They did not. • In the 1980s, corporations poured over a billion dollars into "expert systems," AI programs designed to replicate the decision-making of human specialists in medicine, finance, and engineering. By 1987, this entire market crashed. • In 2016-17, machine learning hype surged again. It faded quickly. Each time, the technology underdelivered and the money dried up. But here's what really different about this time. AI has made four breakthroughs back to back. 1) Language models 2) Reasoning 3) Coding agents 4) Self-improvement And ALL are generating revenue in production right now. That's why old Nvidia chips are gaining value instead of depreciating. And this has literally never happened in computing before. Every GPU is sold out for the next 3-4 years. He calls betting against this "essentially suicidal" and "an invitation to get your face ripped off." He calls it "an 80-year overnight success." Researchers worked their entire lives on this, and many passed away without seeing it work. Now it is all arriving at once. — Marc Andreessen (@pmarca), co-founder at a16z (@a16z) on the Latent Space podcast (@latentspacepod)

The man who won the Nobel Prize just told the world that AI is not the energy crisis, it is the cure for it. Everyone has been screaming about how much electricity AI consumes, the data centers, the training runs, the billions of queries every single day. Hassabis just said AI will extract 30 to 40 percent more efficiency out of national power grids, grids that, right now, operate at only 30 percent of their total capacity according to Stanford researchers. That means the grids we already built are massively underused, and AI is the key to unlocking what is already there. But that is the smallest part of what he is saying. He is saying AI will crack nuclear fusion, the energy source that has been 30 years away for the last 60 years and DeepMind is already working with Commonwealth Fusion in the US to help AI contain plasma inside fusion reactors. His personal mission is to use AI to discover a room-temperature superconductor, a material that would allow electricity to travel with zero loss, something physics has never been able to deliver. The implications of that alone would reshape the entire global economy overnight. He is also saying AI will design next-generation batteries and build the best climate modeling systems humanity has ever had, using them to figure out exactly where the planet is breaking down. Think about what this means, the thing everyone is blaming for the energy crisis is the same thing being bet on to end it forever.

a bit over 7 days out from the Gemma 4 release and it's models are outpacing (slightly) the equivalent Qwen 3.5 models on downloads. Big numbers! https://t.co/iRs6DJ4fs4

The internet was supposed to connect the world. It connected the infrastructure. The people stayed divided. For thirty years, a Japanese user and an American user existed on the same network and couldn’t understand a single word the other one typed. The information was accessible. The conversation was not. Language was the last wall. And nobody was building a door. X just removed it. Calacanis: “This auto-translate feature has done more for understanding across borders than anything I’ve ever seen.” Grok is integrated directly into the platform. Every post, every reply, every thread. Translated in real time, both directions, automatically. A user in Tokyo writes in Japanese. You read it in English. You reply. They read your response in Japanese. Neither of you switched a setting. Neither of you copied text into a translator. The friction simply doesn’t exist anymore. Calacanis: “People who don’t speak the same language engaging on X in a very nuanced, fun, interesting way. And that, as a truth mechanism, is just absolutely extraordinary.” This has never existed before. Not at this speed. Not at this scale. Not with this level of nuance preserved. Previous translation tools gave you the words. They butchered the tone, the context, the cultural weight behind them. An LLM doesn’t just translate language. It translates intent. Sarcasm. Subtext. The meaning underneath the words. That changes what’s possible on the platform. Americans, Japanese, Israeli, French, Russian, and Middle Eastern users debating, arguing, laughing, and exchanging culture directly. No journalist filtering the message. No editor deciding what’s relevant. No network choosing which perspectives get airtime. Peer to peer. Unmediated. Unfiltered. Calacanis: “Journalists are not even taking the time to translate and cover what’s going on in those areas, and this is happening automatically in real time.” For decades, your understanding of another country was shaped entirely by whichever outlet decided to cover it. If they didn’t translate it, you never saw it. If they did, you saw their version of it. That filter is gone. The raw, unedited perspective of every culture on Earth is now accessible to every other culture on Earth. Instantly. Without permission. Without a middleman. That is what a real town square looks like. Not a platform where people from the same country talk to each other in the same language about the same news cycle. A platform where the entire species can hear each other for the first time. X didn’t just build a social network. It built the first global conversation where language is no longer the barrier to entry. The walls between cultures were never ideological. They were linguistic. The wall is down. And 8 billion people just entered the same room.

Grateful Minimax M2.7 weights are out, but their 6hr-before-release license edit makes the model nearly unusable. A lame non-commercial limitation so broadly defined that you're essentially only allowed to use it for projects given out for free, else need to be granted permission from @MiniMax_AI.

Model Y🌸 https://t.co/XhGyAjQvgs

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Starship and Super Heavy move out to continue preflight testing https://t.co/zYN1fkvNIk

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https://t.co/YSzlmtXCRK

Huh, why is Stephen Miller's wife talking about physical AI companies lol https://t.co/2ZmLMMokLV