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
SpaceX’s Starship FL launch site will witness scenes once reserved for sci-fi films
A Starship that launches from the Florida site could touch down on the same site years later.
The Department of the Air Force (DAF) has released its Final Environmental Impact Statement for SpaceX’s efforts to launch and land Starship and its Super Heavy booster at Cape Canaveral Space Force Station’s SLC-37.
According to the Impact Statement, Starship could launch up to 76 times per year on the site, with Super Heavy boosters returning within minutes of liftoff and Starship upper stages landing back on the same pad in a timeframe that was once only possible in sci-fi movies.
Booster in Minutes, Ship in (possibly) years
The EIS explicitly referenced a never-before-seen operational concept: Super Heavy boosters will launch, reach orbit, and be caught by the tower chopsticks roughly seven minutes after liftoff. Meanwhile, the Starship upper stage will complete its mission, whether a short orbital test, lunar landing, or a multi-year Mars cargo run, and return to the exact same SLC-37 pad upon mission completion.
“The Super Heavy booster landings would occur within a few minutes of launch, while the Starship landings would occur upon completion of the Starship missions, which could last hours or years,” the EIS read.
This means a Starship that departs the Florida site in, say, 2027, could touch down on the same site in 2030 or later, right beside a brand-new stack preparing for its own journey, as noted in a Talk Of Titusville report. The 214-page document treats these multi-year round trips as standard procedure, effectively turning the location into one of the world’s first true interplanetary spaceports.
Noise and emissions flagged but deemed manageable
While the project received a clean bill of health overall, the EIS identified two areas requiring ongoing mitigation. Sonic booms from Super Heavy booster and Starship returns will cause significant community annoyance” particularly during nighttime operations, though structural damage is not expected. Nitrogen oxide emissions during launches will also exceed federal de minimis thresholds, prompting an adaptive management plan with real-time monitoring.
Other impacts, such as traffic, wildlife (including southeastern beach mouse and Florida scrub-jay), wetlands, and historic sites, were deemed manageable under existing permits and mitigation strategies. The Air Force is expected to issue its Record of Decision within weeks, followed by FAA concurrence, setting the stage for rapid redevelopment of the former site into a dual-tower Starship complex.
SpaceX Starship Environmental Impact Statement by Simon Alvarez
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Tesla Full Self-Driving (FSD) testing gains major ground in Spain
Based on information posted by the Dirección General de Tráfico (DGT), it appears that Tesla is already busy testing FSD in the country.
Tesla’s Full Self-Driving (Supervised) program is accelerating across Europe, with Spain emerging as a key testing hub under the country’s new ES-AV framework program.
Based on information posted by the Dirección General de Tráfico (DGT), it appears that Tesla is already busy testing FSD in the country.
Spain’s ES-AV framework
Spain’s DGT launched the ES-AV Program in July 2025 to standardize testing for automated vehicles from prototypes to pre-homologation stages. The DGT described the purpose of the program on its official website.
“The program is designed to complement and enhance oversight, regulation, research, and transparency efforts, as well as to support innovation and advancements in automotive technology and industry. This framework also aims to capitalize on the opportunity to position Spain as a pioneer and leader in automated vehicle technology, seeking to provide solutions that help overcome or alleviate certain shortcomings or negative externalities of the current transportation system,” the DGT wrote.
The program identifies three testing phases based on technological maturity and the scope of a company’s operations. Each phase has a set of minimum eligibility requirements, and applicants must indicate which phase they wish to participate in, at least based on their specific technological development.

Tesla FSD tests
As noted by Tesla watcher Kees Roelandschap on X, the DGT’s new framework effectively gives the green flight for nationwide FSD testing. So far, Tesla Spain has a total of 19 vehicles authorized to test FSD on the country’s roads, though it would not be surprising if this fleet grows in the coming months.
The start date for the program is listed at November 27, 2025 to November 26, 2027. The DGT also noted that unlimited FSD tests could be done across Spain on any national route. And since Tesla is already in Phase 3 of the ES-AV Program, onboard safety operators are optional. Remote monitoring would also be allowed.
Tesla’s FSD tests in Spain could help the company gain a lot of real-world data on the country’s roads. Considering the scope of tests that are allowed for the electric vehicle maker, it seems like Spain would be one of the European countries that would be friendly to FSD’s operations. So far, Tesla’s FSD push in Europe is notable, with the company holding FSD demonstrations in Germany, France, and Italy. Tesla is also pushing for national approval in the Netherlands in early 2026.
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Tesla FSD V14.2.1 is earning rave reviews from users in diverse conditions
Tesla’s Full Self-Driving (Supervised) software continues its rapid evolution, with the latest V14.2.1 update drawing widespread praise.
Tesla’s Full Self-Driving (Supervised) software continues its rapid evolution, with the latest V14.2.1 update drawing widespread praise for its smoother performance and smarter decision-making.
Videos and firsthand accounts from Tesla owners highlight V14.2.1 as an update that improves navigation responsiveness, sign recognition, and overall fluidity, among other things. Some drivers have even described it as “more alive than ever,” hinting at the system eventually feeling “sentient,” as Elon Musk has predicted.
FSD V14.2.1 first impressions
Early adopters are buzzing about how V14.2.1 feels less intrusive while staying vigilant. In a post shared on X, Tesla owner @LactoseLunatic described the update as a “huge leap forward,” adding that the system remains “incredibly assertive but still safe.”
Another Tesla driver, Devin Olsenn, who logged ~600 km on V14.2.1, reported no safety disengagements, with the car feeling “more alive than ever.” The Tesla owner noted that his wife now defaults to using FSD V14, as the system is already very smooth and refined.
Adverse weather and regulatory zones are testing grounds where V14.2.1 shines, at least according to testers in snow areas. Tesla watcher Sawyer Merritt shared a video of his first snowy drive on unplowed rural roads in New Hampshire, where FSD did great and erred on the side of caution. As per Merritt, FSD V14.2.1 was “extra cautious” but it performed well overall.
Sign recognition and freeway prowess
Sign recognition also seemed to show improvements with FSD V14.2.1. Longtime FSD tester Chuck Cook highlighted a clip from his upcoming first-impressions video, showcasing improved school zone behavior. “I think it read the signs better,” he observed, though in standard mode, it didn’t fully drop to 15 mph within the short timeframe. This nuance points to V14.2.1’s growing awareness of temporal rules, a step toward fewer false positives in dynamic environments.
FSD V14.2.1 also seems to excel in high-stress highway scenarios. Fellow FSD tester @BLKMDL3 posted a video of FSD V14.2.1 managing a multi-lane freeway closure due to a police chase-related accident. “Perfectly handles all lanes of the freeway merging into one,” the Tesla owner noted in his post on X.
FSD V14.2.1 was released on Thanksgiving, much to the pleasant surprise of Tesla owners. The update’s release notes are almost identical to the system’s previous iteration, save for one line item read, “Camera visibility can lead to increased attention monitoring sensitivity.”
