frank z993
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Every Big Tech company is racing to build AI assistants. A startup called Nori just showed the first one that actually runs a household.
SuperNori auto-restocks groceries, books travel, plans weekly meals around your family's nutrition goals, and controls smart home devices. All without being asked.
The real moat in AI isn't the model. It's who owns the daily routine.
Isaac@IsaacDrgn
Most AI helps you write, design, code, and ship faster at work. Nothing was built for the person quietly holding the family together. Introducing SuperNori: the first Proactive Family AI Agent built for the family caretaker in every family. Here's how it works: youtu.be/qNYG00sveyI
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@elonmusk @yunta_tsai I wish I could use more great keywords because they’re greatness
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The cheapest place to put AI will be space.
Elon Musk says solar panels in space produce 5 times more power than on the ground. No atmosphere, no clouds, no day-night cycle. No batteries needed. And critically, no permits.
Scaling energy on Earth means fighting land use regulations, environmental reviews, and grid interconnection queues that take years. Space has none of that.
The math gets wild fast. SpaceX could launch hundreds of gigawatts of AI compute into orbit annually. That's more compute than currently exists on Earth. Ten thousand Starship launches per year. One launch every hour. And you only need 20 to 30 ships to sustain that cadence.
Earth gets about half a billionth of the Sun's total energy output. A millionth of the Sun's energy is 100,000 times all of civilization's current electricity production.
The AI race is not a software race. It is a power plant race. And software people are about to get a very hard lesson in hardware.
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There's large numbers of people who think work should be lost because of AI are actually imposing people from work.
unusual_whales@unusual_whales
‘AI is going to create a labor shortage,' Jeff Bezos has said.
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@heyshrutimishra if you want to build fast i think closed models are the best chooice
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When Anthropic shut down Fable, every product, every agent, every integration that depended on it went dark overnight.
Not because of a technical failure. A government directive forced it, and because Anthropic couldn't segment access fast enough, they switched it off for everyone. Worldwide.
This is the clearest proof we've ever gotten that building on closed models means renting, not owning.
Bloomberg called it a win for sovereign AI. Fortune reported a global scramble for alternatives. CNBC called it a turning point. They're all right, but for a reason most people are missing.
The argument for open models used to be about cost and avoiding vendor lock-in. This week it became something bigger. When a single government directive can wipe out an entire model capability across every country simultaneously, the case for open weights isn't about saving money anymore. It's about resilience.
Countries building their own AI stacks aren't being protectionist. They're being rational. If your healthcare system, your financial infrastructure, or your defense apparatus runs on a model that someone else can turn off, you don't have an AI strategy. You have a dependency.
The open model ecosystem has been closing the gap on performance for months. Models like Nemotron are already competing at the frontier. This week it closed the gap on urgency.
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@Jayyanginspires leverage is there but who can use it well will compete with who doesn't
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I analyzed the software stack behind autonomous robots, and here's what actually makes them work:
It's 50+ tools working together like a symphony.
Think of a robot like a human:
1. Eyes (Perception)
OpenCV, TensorFlow – Help robots "see" the world
2. Brain (AI & Learning)
OpenAI Gym, Ray RLlib – Make decisions and learn from mistakes
3. Memory (Mapping)
ORB-SLAM, Cartographer – Remember locations and build mental maps
4. Muscles (Control)
PID Controllers, ROS – Turn thoughts into physical movements
5. Nervous System (Communication)
MQTT, gRPC – Connect all parts together
6. Support Team (Cloud)
AWS RoboMaker – Manage entire fleets remotely
7. Safety Net (Compliance)
Watchdog Systems – Prevent disasters
The magic isn't in any single piece.
It's in how they ALL talk to each other.
A self-driving car uses 20+ of these simultaneously. A warehouse robot? Another 15.
The craziest part?
Most of these are open-source.
What surprises you most about this stack? 👇

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The great lie is that society is divided between rich and poor.
The great truth, as David Friedberg puts it, is makers vs takers.
Makers build, create, and deliver real value: houses, software, art, businesses, and everything that moves civilization forward.
Takers watch, criticize, analyze, and politic. They push the lie that the rich hoard unfairly so the poor must seize it… all while positioning themselves to rule the chaos.
As @friedberg tells his kids: “At the end of the day, if you made something and someone else valued it, you were a maker. That was an amazing achievement. That is a great day.”
Takers thrive on division. Makers drive progress.
Time to choose your side.
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@heyshrutimishra so far no one can do it now and elon musk is a prophet
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Elon Musk says Optimus is the infinite money glitch.
Not because robots are valuable. Because robots can make more robots.
Musk explained that humanoid robots improve through three exponential trends multiplied together: digital intelligence, AI chip capability, and electromechanical dexterity. But the real unlock is that the robot can start making the robots.
"So you have a recursive multiplicative exponential," he said. "This is a supernova."
Musk's thesis is that once you have a physical robot capable of manufacturing, the production curve stops being linear and becomes self-replicating. Every robot built accelerates the building of the next one.
The implication is that the companies that control physical manufacturing will control AI's future, not the ones with the best models. The bottleneck is not intelligence. It is atoms.
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