- Wayne Allyn Roo Wayne Root - Wayne Al

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- Wayne Allyn Roo Wayne Root - Wayne Al

- Wayne Allyn Roo Wayne Root - Wayne Al

@AllynAl95108

Watch@ RealAmericasVoice TV Sat Noon ET/9 AM PT & daily 6 pm ET on https://t.co/T6fmKIgKjW and https://t.co/rzVLp2BZJJ. Or go to: https://t.co/vb5XfKRVto

Uk Katılım Nisan 2026
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🌿@earthserenityy·
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SpaceX
SpaceX@SpaceX·
Falcon 9 launches 25 @Starlink satellites from California
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VIEW@viewsoff·
Mount Fuji, Japan 🇯🇵
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Elon Musk
Elon Musk@elonmusk·
Accurate
The All-In Podcast@theallinpod

David Sacks: Nonprofits need to manufacture problems in America to stay in business David Sacks: “Here's the systemic problem with nonprofits and NGOs. Let me just contrast it with business. In business, you set up a company, the company has to make revenue, it has to make profits. And if it doesn't, it's going to go out of business, right? Because it'll lose money. So there's a feedback mechanism from the market. With an NGO, nonprofit, what have you, they raise money. They don't sell things. They fundraise from donors in order to engage in an activity, but what happens over time is the actual activities may stop mattering, and all that really matters is they're able to keep fundraising, right? Because they're just trying to figure out a justification to keep going back to donors to get more and more money out of them. That's what perpetuates the organization.” Chamath: “ Why wouldn't the Southern Poverty Law Center focus on southern poverty? Which is an issue that actually still exists in some shape or form. Why do you call it one thing, focus on racism, and then all of a sudden whip up fake racism?” Sacks: “I do think that at one time in this country, civil rights was a noble cause, a very legitimate cause. We had the legacy of segregation and Jim Crow, and there were groups that were set up to basically change that, and they succeeded. But again, no one in an NGO or a nonprofit ever declares victory. When Obama got elected in 2008, regardless of whether you liked Obama or not, or agreed with his politics, I thought that at that point, most people could see that this was not a racist country. Whatever else you could say, the fact that the highest office in the land was not denied to anybody showed that this country was not holding people back based on their skin color. And instead of just basically packing up shop and saying, ‘Okay, we've achieved our goal,’ the goalposts all got moved. Remember, that's when the whole anti-racism thing started, was around Obama's second term. If they just said at that time, ‘You know what, we're going to move the goalposts from equality of opportunity to equality of results. We're going to basically make everyone equal at the finish line,’ which is to say, identity socialism. People would've said, ‘Eh, no, we're not on board for that.’ So instead, they created this whole new terminology to justify it. And it's taken us years to unpack that and realize what's really going on.”

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Elon Musk
Elon Musk@elonmusk·
FSD 14.3 release notes @Tesla_AI
Tesla AI@Tesla_AI

New release of FSD Supervised now starting to roll out This update brings 20% faster reaction time to further increase safety, among many other improvements Full release notes below Full Self-Driving (Supervised) v14.3 includes - Upgraded the Reinforcement Learning (RL) stage of training the FSD neural network, resulting in improvements in a wide variety of driving scenarios. - Upgraded the neural network vision encoder, improving understanding in rare and low-visibility scenarios, strengthening 3D geometry understanding, and expanding traffic sign understanding. - Rewrote the AI compiler and runtime from the ground up with MLIR, resulting in 20% faster reaction time and improving model iteration speed. - Mitigated unnecessary lane biasing and minor tailgating behaviors. - Increased decisiveness of parking spot selection and maneuvering. - Improved parking location pin prediction, now shown on a map with a (P) icon. - Enhanced response to emergency vehicles, school buses, right-of-way violators, and other rare vehicles. - Improved handling of small animals by focusing RL training on harder examples and adding rewards for better proactive safety. - Improved traffic light handling at complex intersections with compound lights, curved roads, and yellow light stopping – driven by training on hard RL examples sourced from the Tesla fleet. - Improved handling for rare and unusual objects extending, hanging, or leaning into the vehicle path by sourcing infrequent events from the fleet. - Improved handling of temporary system degradations by maintaining control and automatically recovering without driver intervention, reducing unnecessary disengagements. Upcoming Improvements - Expand reasoning to all behaviors beyond destination handling. - Add pothole avoidance. - Improve driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.

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