Twitter v2.0 - powered by Elon

[mraki]

Elon opet imao neke rasistsičke i antisemitističke ispade. 
IBM i Apple povuki oglase sa Tvitera.

[Roger Sanchez]

 

[Weenie Pooh]

17 minutes ago, Roger Sanchez said:

 

 

 

 

 

[Lord Protector]

 

From the author of Steve Jobs and other bestselling biographies, this is the astonishingly intimate story of the most fascinating and controversial innovator of our era—a rule-breaking visionary who helped to lead the world into the era of electric vehicles, private space exploration, and artificial intelligence. 

 

 

 

[dragance]

Ala su ga tuširali u fotošopu  

[Lord Protector]

Moram da postujem delove iz knjige, jako je zanimljiva

[dragance]

Čim čujem da ga neko smatra vizionarom, znam da je sci-fi.

[Weenie Pooh]

9 minutes ago, dragance said:

Ala su ga tuširali u fotošopu  

 

Celu sliku generisala AI sto posto, vidi ga kakav je chad.

 

Mnogo je dobro ovo kako je Musk uveo svet u "doba električnih vozila, privatnog istraživanja svemira, i veštačke inteligencije".

 

Igrom slučaja, to doba postoji samo u glavama njegovih fanova. Samo oko 1.5% vozila je na struju, turistički letovi milijardera u svemir nisu nikakvo istraživanje, a ovo što se danas zove AI ne zaslužuje slovo I.

[mustang]

18%

[Lord Protector]

Lonely and determined

 

At 7:30 on the morning of June 28, 1971, Maye Musk gave birth to an eight pound, eight-ounce boy with a very large head. At first she and Errol were going to name him Nice, after the town in France where he was conceived. History may have been different, or at least amused, if the boy had to go through life with the name Nice Musk. Instead, in the hope of making the Haldemans happy, Errol agreed that the boy would have names from that side of the family: Elon, after Maye’s grandfather J. Elon Haldeman, and Reeve, the maiden name of Maye’s maternal grandmother. Errol liked the name Elon because it was biblical, and he later claimed that he had been prescient. As a child, he says, he heard about a science fiction book by the rocket scientist Wernher von Braun called Project Mars, which describes a colony on the planet run by an executive known as “the Elon.” Elon cried a lot, ate a lot, and slept little. At one point Maye decided to just let him cry until he fell asleep, but she changed her mind after neighbors called the police. His moods switched rapidly; when he wasn’t crying, his mother says, he was really sweet.

 

Edited November 24, 2023 by Lord Protector

[Lord Protector]

Quote

 

AI for Cars Tesla, 2022–2023

 

Cars that learn from humans

 

“It’s like ChatGPT, but for cars,” Dhaval Shroff told Musk. He was comparing his project at Tesla to the artificial intelligence chatbot that had just been released by OpenAI, the lab that Musk had cofounded with Sam Altman in 2015. For almost a decade, Musk had been working on various forms of artificial intelligence, including self-driving cars, Optimus the robot, and the Neuralink brain-machine interface. Shroff’s project involved the latest machine-learning frontier: devising a self-driving car system that would learn from human behavior. “We process an enormous amount of data on how real humans acted in a complex driving situation, and then we train a computer’s neural network to mimic that.” Musk had asked to meet with Shroff—who had occasionally served as a fourth musketeer with James, Andrew, and Ross—because he was thinking about persuading him to leave Tesla’s Autopilot team and come work at Twitter. Shroff was hoping to avoid that by convincing Musk of the crucial importance, to Tesla and to the world, of the project he was working on, a “learn-from-humans” component to Tesla’s self-driving software that they were calling “the neural network path planner.” Their meeting was scheduled for a day that turned out to be so wildly crammed with plot lines that it would seem too contrived if it were part of a screenplay: Friday, December 2, 2022, which was when the first set of Twitter Files was due to be posted by Matt Taibbi. Shroff arrived at Twitter headquarters that morning, as requested, but Musk, who had just come back from unveiling the Cybertruck in Nevada, apologized. He had forgotten that he was due to fly to New Orleans to meet with President Macron to talk about European content moderation regulations. He asked Shroff to come back that evening. As he was waiting for Macron, Musk sent Shroff texts pushing their meeting later. “I’m going to be delayed by four hours,” Musk texted at one point. “Do you mind waiting?” That’s also when he texted Bari Weiss and Nellie Bowles out of the blue asking them to fly up to San Francisco and meet him that night to help with the Twitter Files. When Musk arrived back in San Francisco late that night, he finally got a chance to sit down with Shroff, who explained the details of the neural network planner project he was working on. “I think it’s super important that I continue doing what I’m doing,” Shroff said. Listening to him, Musk got excited again about the project and agreed. In the future, he realized, Tesla was going to be not just a car company and not just a clean-energy company. With Full Self-Driving and the Optimus robot and the Dojo machine-learning supercomputer, it was going to be an artificial intelligence company—one that operated not only in the virtual world of chatbots but also in the physical real world of factories and roads. He was already thinking about hiring a group of AI experts to compete with OpenAI, and Tesla’s neural network planning team would complement their work. For years, Tesla’s Autopilot system relied on a rules-based approach. It took visual data from a car’s cameras and identified such things as lane markings, pedestrians, vehicles, traffic signals, and anything else in range of the eight cameras. Then the software applied a set of rules, such as Stop when the light is red; Go when it’s green; Stay in the middle of the lane markers; Don’t cross double-yellow lines into incoming traf ic; Proceed through an intersection only when there are no cars coming fast enough to hit you; and so on. Tesla’s engineers manually wrote and updated hundreds of thousands of lines of C++ code to apply these rules to complex situations. The neural network planner project that Shroff was working on would add a new layer. “Instead of determining the proper path of the car based only on rules,” Shroff says, “we determine the car’s proper path by also relying on a neural network that learns from millions of examples of what humans have done.” In other words, it’s human imitation. Faced with a situation, the neural network chooses a path based on what humans have done in thousands of similar situations. It’s like the way humans learn to speak and drive and play chess and eat spaghetti and do almost everything else; we might be given a set of rules to follow, but mainly we pick up the skills by observing how other people do them. It was the approach to machine learning envisioned by Alan Turing in his 1950 paper, “Computing Machinery and Intelligence.” Tesla had one of the world’s largest supercomputers to train neural networks. It was powered by graphics processing units (GPUs) made by the chipmaker Nvidia. Musk’s goal for 2023 was to transition to using Dojo, the supercomputer that Tesla was building from the ground up, to use video data to train the AI system. With chips and infrastructure designed in-house by Tesla’s AI team, it has nearly eight exaflops (10 18 operations per second) of processing power, making it 

the world’s most powerful computer for that purpose. It would be used for both self-driving software and for Optimus the robot. “It’s interesting to work on them together,” Musk says. “They are both trying to navigate the world.” By early 2023, the neural network planner project had analyzed 10 million frames of video collected from the cars of Tesla customers. Does that mean it would merely be as good as the average of human drivers? “No, because we only use data from humans when they handled a situation well,” Shroff explains. Human labelers, many of them based in Buffalo, New York, assessed the videos and gave them grades. Musk told them to look for things “a five-star Uber driver would do,” and those were the videos used to train the computer. Musk regularly walked through Tesla’s Palo Alto building, where the Autopilot engineers sat in an open workspace, and he would kneel down next to them for impromptu discussions. One day Shroff showed him the progress they were making. Musk was impressed, but he had a question: Was this whole new approach truly needed? Might it be a bit of overkill? One of his maxims was that you should never use a cruise missile to kill a fly; just use a flyswatter. Was using a neural network to plan paths an unnecessarily complicated way to deal with a few very unlikely edge cases? Shroff showed Musk instances where a neural network planner would work better than a rules-based approach. The demo had a road littered with trash cans, fallen traffic cones, and random debris. A car guided by the neural network planner was able to skitter around the obstacles, crossing the lane lines and breaking some rules as necessary. “Here’s what happens when we move from rules-based to network-path-based,” Shroff told him. “The car will never get into a collision if you turn this thing on, even in unstructured environments.” It was the type of leap into the future that excited Musk. “We should do a James Bond– style demonstration,” he said, “where there are bombs exploding on all sides and a UFO is falling from the sky while the car speeds through without hitting anything.” Machine-learning systems generally need a goal or metric that guides them as they train themselves. Musk, who liked to manage by decreeing what metrics should be paramount, gave them their lodestar: the number of miles that cars with Tesla Full Self-Driving were able to travel without a human intervening. “I want the latest data on miles per intervention to be the starting slide at each of our meetings,” he decreed. “If we’re training AI, what do we optimize? The answer is higher miles between interventions.” He told them to make it like a video game where they could see their score every day. “Video games without a score are boring, so it will be motivating to watch each day as the miles per intervention increases.” Members of the team installed massive eighty-five-inch television monitors in their workspace that displayed in real time how many miles the FSD cars were driving on average without interventions. Whenever they would see a type of intervention recurring—such as drivers grabbing the wheel during a lane change or a merge or a turn into a complex intersection—they would work with both the rules and the neural network planner to make a fix. They put a gong near their desks, and whenever they successfully solved a problem causing an intervention, they got to bang the gong.

 

 

To je ono što mnogi ne razumeju, Elon umrežava sve svoje kompanije u jedan veliki data pool koji koristi podatke i modele iz jedne firme da bi trenirao AI modele u drugim. To jedan BMW, Mercedes ili Toyota ne mogu da isprate, ograničeni su svojom uskom specilizacijom. Da ne pominjem koliko mu pomaže know-how novih materijala za SpaceX koje koristi u pravljenju novih mehaničkih i elektronskih komponenti za autoindustriju.

Sve konvergira ka autonomnim agentima, sve postaje robot.

Edited November 24, 2023 by Lord Protector

[mustang]

Kad bude uzleteo niko ga vise nece stici. Ovo sto smo pokupovali tesle, pokupovali. Steta za spaceX IPO sto ne mogu da uzmem, rado bih, al se ne kvalifikujem. Za 5-10 godina bice potpuna dominacija. Mark my words. Osim ako ga ne uklone.

[Lord Protector]

28 minutes ago, mustang said:

Kad bude uzleteo niko ga vise nece stici. Ovo sto smo pokupovali tesle, pokupovali. Steta za spaceX IPO sto ne mogu da uzmem, rado bih, al se ne kvalifikujem. Za 5-10 godina bice potpuna dominacija. Mark my words. Osim ako ga ne uklone.

 

Posebno su bitna dva projekta: Neurolink i Grok. Tu koncentraciju znanja iz AI i neuralnih mreža neće imati ni jedan OpenAI. Trenutno su bitni podaci, ogromne količine podataka, koje on dobija u realnom vremenu sa svih platformi: sa automobila, sa Twittera, sa senzora iz SpaceX... niko to nema. Da ne spominjem kvalitet inženjerskog kadra svih mogućih oblasti koji trenutno radi za njega. 

 

Samo Kinezi imaju toliku količinu kvalitetnih podataka i resursa, ali samo na državnom nivou.

 

 

Edited November 24, 2023 by Lord Protector

[mustang]

Ne sekiram se za kineze iako su pokupili najbolje iz evrope i amerike od strucnjaka za dizajn i izgradnju byd na primer. Kina ce imati drugih problema uskoro kada krene pucanje unutar drzave, previse se polarizovalo, a i doprinece i sto se biznisi prebacuju u indiju i druge azijske zemlje.  

 

Ti i ja se razumemo oko elonovih projekata, nasi prijatelji ovde su ipak skepticni ne shvatajuci da je ovaj Put neminovan. Cekam da uvede telefon sa nekom sjajnom kamerom  ....

Edited November 24, 2023 by mustang

[Lezilebovich]

39 minutes ago, mustang said:

Kad bude uzleteo niko ga vise nece stici. Ovo sto smo pokupovali tesle, pokupovali. Steta za spaceX IPO sto ne mogu da uzmem, rado bih, al se ne kvalifikujem. Za 5-10 godina bice potpuna dominacija. Mark my words. Osim ako ga ne uklone.

Ovo prorocantsvo ne moze da omane. Ako uspe super, ako ne uspe - sigurno su ga mocnici uklonili 

Nema mogucnosti da Elon ne uspe zbog toga sto prosto pravi nevidjene gluposti ?

 

 

edit : dodao upitnik na kraju

 

Edited November 24, 2023 by Lezilebovich