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Elon Musk-founded OpenAI gets $1 billion boost from Microsoft investment

[Source: OpenAI]

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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.

Harry Shuman of Microsoft and Sam Altman of OpenAI discuss their new partnership and the future of AI. | Image: Microsoft/YouTube

“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.

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The company’s latest commitment to Microsoft will now expand their access to resources to achieve even more impressive artificial intelligence feats.

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Elon Musk

Tesla CEO Elon Musk denies ridiculous Gigafactory Shanghai rumor

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(Credit: Tesla)

Tesla CEO Elon Musk took to his social media platform X on Thursday night to deny a ridiculous rumor regarding the sale of the company’s Chinese vehicle production plant, Gigafactory Shanghai.

On Thursday, the Wall Street Journal, citing sources familiar with the matter, claimed in a scathing new report that Tesla was exploring a potential sale of the entire China business in an effort to help bolster a potential merger between SpaceX and Tesla.

Musk immediately denied the rumor not once but twice, initially calling it “fake news,” and then calling it “absurdly fake news” in a separate post just a few moments later:

The original poster of the Wall Street Journal article that Musk saw deleted the initial post sharing the headline and the rumored sale of Tesla’s China business.

The report seemed absolutely and unequivocally false to begin with; Tesla’s business in China is among the most important pieces of the company’s business. Not only does the factory supply vehicles for the domestic market, but also for various other markets in Asia and Europe.

China is also one of the largest automotive markets in the world, and Tesla has performed well there despite the robust competition.

The speculation regarding a Tesla and SpaceX merger has started to gain steam this year as the space exploration company went public just a month ago. There has been speculation that Musk will bridge all of his companies under one “umbrella company,” and analysts believe this could happen before the end of the decade.

The Tesla and SpaceX merger everyone is talking about is quietly building

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This is the latest iteration of Musk’s very evident war on mainstream media. Reports regarding any of Musk’s companies are quick to get the dreaded “false” or “fake news” response from the CEO when they are unfounded.

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Tesla AI boss reveals how big Optimus is going to get

Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.

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Tesla Optimus Gen 3 [Credit: Tesla]

Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”

The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.

The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.

Tesla Optimus project fires up as Musk sees production line progress

Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.

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Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.

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Autonomous vehicle red tape gets slashed by Trump Administration

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Credit: Zoox

The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.

The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.

Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.

There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.

Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:

  1. Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
    This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances.
  2. Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
    This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years.
  3. Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
    This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant.
  4. Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
    By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS).
  5. Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
    NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.

Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:

  • FMVSS 102 – Transmission shifting
  • FMVSS 103/104 – Windshield defrosting and wiping
  • FMVSS 110 – Tire placards
  • FMVSS 135 – Braking systems
  • FMVSS 101 – Controls and displays
  • FMVSS 108 – Vehicle lighting
  • FMVSS 111 – Mirrors and rearview display
  • FMVSS 126 – Electronic stability control systems
  • FMVSS 201/208 – Sun visors and warning labels

These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.

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