Microsoft’s interest in expanding its Azure cloud computing service to include artificial intelligence (AI) supercomputing technologies has led to a new partnership agreement with the Elon Musk-backed company, OpenAI. An investment of $1 billion dollars was recently made by Microsoft into the venture to develop an Azure-based hardware and software platform that will scale to artificial general intelligence (AGI). In turn, OpenAI will use Microsoft as their exclusive cloud provider.
OpenAI is a nonprofit AI research organization co-founded by Musk, serial entrepreneur Peter Thiel, and Y Combinator’s Sam Altman with the goal of developing beneficial, open source AI to combat any future rise of harmful AI. Musk stepped down from the Board of Directors in early 2018 to avoid any conflicts with Tesla’s Autopilot program; however, he still remains as a benefactor and advisor. Tesla’s Director of AI and Autopilot Vision, Andrej Karpathy, previously worked as a neural network researcher for OpenAI.
While the venture is backed by significant private investment, the long-term goals of OpenAI require even greater resources. The company’s motivation to create the new investment partnership with Microsoft was partially due to financial constraints caused by computing hardware needs. The financial requirements to retain top talent are also significant – OpenAI’s tax filings from 2016 revealed its top researcher was paid a $1.9 million dollar salary, with others receiving significant amounts as well.

“OpenAI is producing a sequence of increasingly powerful AI technologies, which requires a lot of capital for computational power. The most obvious way to cover costs is to build a product, but that would mean changing our focus. Instead, we intend to license some of our pre-AGI technologies, with Microsoft becoming our preferred partner for commercializing them,” OpenAI’s press release announcing the new partnership explained.
The connection between Microsoft and OpenAI is not new. In 2016, the companies jointly announced they were working together to run most of OpenAI’s large-scale experiments on Azure, making it their primary cloud platform for deep learning and AI. Azure had hardware configurations optimized for AI computing needs and a roadmap to expand those capabilities even further. One of the stated joint goals between Microsoft and OpenAI is the democratization of AI, and cloud computing is a large part of making that a reality as hardware and software resources are no longer required to be local to the user.
OpenAI has already created some impressive AI capabilities. In August last year, company bots created for the video game Dota 2 defeated a team of highly skilled human players in two games out of three. To accomplish the task, serious amounts of hardware and training were required. The nonprofit research lab employed a scaled-up version of Proximal Policy Optimization running on 256 GPUs and 128,000 cores to complete roughly 180 years worth of gameplay every day through reinforcement learning, which allowed the bots to develop advanced skills for the game. An open source gym for training AI with games was also released by the company.
In 2017, OpenAI announced that it had successfully trained its AI-powered robots to perform a task after watching it once in virtual reality. After showing a robot how to stack a series of colored blocks in a virtual reality simulation, it was then able to successfully mimic the actions. To accomplish this, OpenAI trained the robot in a simulated, virtual environment with nuances like lighting, shadows and backgrounds noise so that when in the real environment, it knew to filter out noise and focus on only important elements as a human brain would.
OpenAI also successfully taught AI bots to create their own language for communicating with each other in 2017. A paper was published on the topic which explained how the bots used reinforcement learning to accomplish simple goals through trial and error. After being given clues such as “Go to” or “Look at” by the researchers, the bots were then required to create their own machine language to communicate with each other.
The company’s latest commitment to Microsoft will now expand their access to resources to achieve even more impressive artificial intelligence feats.
Elon Musk
Tesla shows what Roadster drivers will see on screen before thruster activation
Tesla’s Roadster video reveals a fighter jet inspired cockpit with a 5,500 PSI thruster gauge.
Tesla has given future owners their clearest look yet at the cockpit of its next generation Roadster. In a 34 second video posted to X on Friday afternoon, the company walked through the car’s touchscreen with a caption: “Inspired by fighter jet cockpits, Roadster’s interface was designed around the pilot.”
The clip opens on a black screen with red graphics and a 3D wireframe of the car, which sits beside the Roadster’s squared off yoke. Tapping parts of the model brings up controls for the rear wing, including low drag and high downforce positions, along with a charging page with a charge limit bar and a small music player. A row of tabs along the bottom reads Home, Vehicle, Listen, Climate and Navigate.
Most of the video is spent in Track Mode. The dashboard shows a live circuit map, a list of session lap times, brake and motor temperatures, and pressure and temperature readouts for each tire. A setup page lets the driver pick Auto, Low Drag, High Downforce or Custom aero modes, adjust aero balance and brake balance, and switch stability and traction control off. Along the bottom, a status bar reads “Thruster · 5,500 PSI” next to a “Boost Ready” indicator.
That gauge ties the software to the hardware Tesla showed off near Waco, Texas on October 15. The Thrust and Rocket versions use cold gas thrusters fed by carbon overwrapped pressure vessels, and Tesla lists 0 to 60 mph times of under 0.9 seconds and under 0.59 seconds for them, as Teslarati detailed in its breakdown of the three Roadster configurations. The base Performance car relies on a fan and ground sealing system for grip, and the aero settings on screen match the active wings and suction setup covered in our look at how the Roadster generates downforce.
The Roadster layout is a departure from the rest of Tesla’s lineup. Instead of a map centered screen, the Roadster puts the car itself at the center of the home page, and Tesla’s Roadster page lists two smaller forward displays alongside the main touchscreen. Tesla has not said whether any of the Track Mode telemetry will make its way to the Model 3 Performance or other vehicles.
The interface could still change before deliveries. Elon Musk said at the event that Roadster production will begin in 2028, and Tesla says the flagship Rocket version is not approved for public road use. Reservations are open with a $50,000 payment, while Thrust is listed as a limited release and Rocket is invite only.
Those who want to see the car in person will get their first chance this weekend. The Roadster goes on display in the lobby of the Petersen Automotive Museum in Los Angeles from October 24 to 27, according to Sawyer Merritt, the first time the public will be able to view it up close.
Elon Musk
Tesla reveals Optimus Academy, where robots teach themselves
Tesla has begun building production quality Optimus robots in Fremont and revealed its training plan.
Tesla has started building Optimus on the high volume line it set up inside its Fremont factory, and the company says the robots coming off it are the first that meet the bar for a real product. “The bots coming off this line are the first production-quality bots that we have manufactured,” Tesla wrote in its third quarter shareholder letter, adding that it has “proven that the current manufacturing process for Optimus is suitable for a commercial product.”
The line sits in space that built the Model S and Model X until this spring. Tesla cleared the old vehicle line in 46 days, as Teslarati reported in July, to make room for robot production sized for one million units a year. On Wednesday’s earnings call, Elon Musk said most of the equipment for that capacity is already in Fremont, with output set to climb toward roughly 20,000 robots a week as the line ramps.
Musk described the ramp as a classic S curve. “The growth of Optimus is an S curve, but the initial curve is a shallow slope,” he said. The team is now refining the robot’s AI, electromechanical design, reliability and service life, and Musk expects that work to be finished by the end of next year, when Tesla plans to start delivering Optimus to outside companies for dangerous, repetitive and around the clock jobs.
The most interesting part of the call was how Tesla plans to teach the robots. Its cars send real driving data back to the AI team from millions of vehicles, but Optimus has no fleet like that yet. “A big difference with Optimus versus the cars is we don’t have this vast fleet of cars from which we can gather training data,” Musk said. Tesla’s answer is an Optimus Academy, where 10,000 to 20,000 robots will practice a wide range of tasks and feed what they learn into the next version of the model. Every unit off the Fremont line becomes a source of that training data.
Smarter hardware is on the way too. Tesla plans to put its AI5 chip into Optimus next year, and Musk said a new Optimus video should arrive within one or two months showing the robot completing tasks driven by AI rather than preprogrammed motions. He took aim at rival humanoid demos that only run scripted routines, saying those would not hold up in the real world.
The supply chain is lining up behind the program. In September, Tesla certified Tuopu, Joyson and Sanhua as mass production partners for Optimus components. A far larger Optimus factory is also rising at Giga Texas, where drone footage from Joe Tegtmeyer showed the steel frame nearing completion, and Musk has pegged that plant’s long term target at 10 million robots a year.
Tesla executives also said Optimus production costs are trending toward the expected manufacturing cost of Cybercab, a sign the robot is being engineered for volume from the start. The hands remain the toughest piece of the design, a point Musk also made at the X Takeover event earlier this month, as Teslarati covered at the time, and that is where much of the current engineering effort is focused.
Elon Musk
The Starship moon landing number NASA and Elon Musk can’t agree on
Musk disputes NASA estimate of 22 Starship launches for Moon landing, predicting 6 to 8.
Elon Musk is disputing a new NASA safety panel estimate of how many Starship launches it will take to put astronauts on the Moon, saying the real number will be less than half the panel’s figure.
On Thursday, NASA’s Aerospace Safety Advisory Panel held its quarterly public meeting. Panel member Charlie Precourt, a former NASA astronaut, flagged the fueling process for SpaceX’s lunar lander as a major risk for Artemis IV, the mission planned to land a crew on the Moon in 2028. “We need to keep our eyes on numerous required fuelings for the lander,” Precourt said, according to Ars Technica. “I think the last estimate is around 22 flights.”
Ars Technica’s Eric Berger posted the comment on X, and Musk replied. “That’s way too high,” Musk wrote. “Actual number will be more like 6 to 8.”
The disagreement comes down to a basic problem with sending a ship as large as Starship to the Moon. Starship burns nearly all of its propellant just reaching Earth orbit, so it cannot continue on to the Moon without stopping for a refill. SpaceX’s answer is a gas station in space. First, a Starship that works as a storage tank, called a depot, is launched into orbit. Then a series of tanker Starships launch one at a time, dock with the depot and pump their leftover propellant into it. Once the depot is full, the lunar lander version of Starship launches, docks, fills up and heads for the Moon.
Every tanker trip is its own full rocket launch, which is why the count matters. More launches mean more time, more cost and more chances for something to go wrong before astronauts ever leave Earth. Berger estimated that even if SpaceX reaches twice weekly Starship launches by the end of 2027, filling a depot at the panel’s number would still take roughly three months.
How many tankers are needed depends mostly on how much propellant each one can carry to orbit and how much is lost along the way. Starship’s fuel and oxygen are stored at extremely cold temperatures, and some of it slowly boils off while waiting in orbit. More is lost in each transfer. NASA appears to be working from what Starship can lift today, while Musk’s range assumes a more capable rocket.
Musk has pushed back on higher counts before. In 2021, after a government document suggested 16 launches, he called that “extremely unlikely” and said eight tankers would be the most required.
Much of the answer depends on hardware SpaceX has not finished flying. As Teslarati noted earlier this year, the company plans to carry out the refueling process with its upgraded V3 Starship, and Precourt described Artemis IV as carrying “a large number of firsts.” He also praised NASA Administrator Jared Isaacman’s team for working to clear obstacles for both SpaceX and Blue Origin, whose Blue Moon lander does not rely on orbital refueling for its first mission.