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.
Tesla (NASDAQ: TSLA) will report its earnings for the second quarter of 2026 this evening after market close, and investors and analysts are waiting anxiously to see what the company will report for the second three-month span of the year.
Analysts have already put out their expectations from a financial standpoint for the company’s second quarter, but what’s unknown is what Tesla plans to discuss during the call.
Financial Expectations
Wall Street consensus expectations put Tesla’s Earnings Per Share (EPS) at $0.53, while revenues are expected to come in around $26.4 billion.
This would compare to an EPS of $0.39 and $22.19 billion compared to Tesla’s Q2 2025. Last quarter, EPS came in at $0.41 on $22.387 billion of revenue. Additionally in Q1, Tesla beat analyst expectations, but shares dropped over 3 percent the following trading day.
What We Expect
In terms of discussions, Tesla earnings are pretty sporadic and depend on a handful of things, including current events, investor questions, and more.
Tesla uses a platform called Say to field questions from investors and analysts. These questions are what will be used during the call. Here are the top 5 from the Retail side and top 3 from the Institutional side:
Retail:
“Tesla has missed short-term guidance on robotaxi 3 earnings reports in a row, from 50% coverage of USA by end of 2025 to most recently 7 new cities in 1H26. What is keeping Tesla back from accomplishing these short term goals that they’ve set for themselves?”
“What are the main constraints to expanding robotaxi operations faster, and how do you see that lining up with Cybercab production?”
“What’s the current status of Optimus Gen 3 production ramp, initial deployment in factories, and external sales timeline/volume for 2027? What tasks can we expect the Optimus to perform by end of 2027?”
“To reward long-term Tesla retail shareholders for their loyalty, can you commit to achieving at least half of the goals outlined in your 2025 compensation plan before considering any offers to acquire or merge Tesla?”
“Why has growth of robotaxi vehicles stalled? When will we see cybercab start customer rides?”
Institutional
“Previously, you’ve said Tesla would lead the R&D while SpaceX would lead production for Terafab. Can you provide an update on how that division of responsibilities is evolving, and any additional clarity on the expected capital contributions from Tesla and SpaceX?”
“For autonomous driving, Tesla’s fleet created a huge data advantage by collecting billions of real-world miles. That advantage doesn’t yet exist for Optimus. How should we think about data availability and its impact on Optimus development?”
“Why is it necessary to limit robotaxi operations within specific zones within cities to start? Will every city have to be rolled out this way?”
Tesla will report earnings for Q2 this evening with the Shareholder Deck at 4 p.m. ET, with the call starting around 5:30 p.m. ET.
Elon Musk
Elon Musk handed Grok something no other AI company can get their hands on
Elon Musk says SpaceX will feed engineering data into Grok’s next model, avoiding restricted material.
Elon Musk said Tuesday that SpaceX will feed its internal engineering data into the next major training run for Grok, the AI model now folded into SpaceX following February’s merger. In a post on X, Musk wrote that SpaceX’s “massive corpus of world-class engineering data,” excluding anything restricted under U.S. arms export law, will be added during supplemental training of what he called the “2T run,” a reference to a roughly two trillion parameter model that would nearly double the parameters behind the latest Grok 4.5 that’s rolling out.
SpaceX’s massive corpus of world-class engineering data (excluding material blocked by ITAR) will be added during supplemental training of the 2T run.
This will dramatically improve Grok’s engineering capabilities. https://t.co/BbQEViFByn
— Elon Musk (@elonmusk) July 21, 2026
The excluded material that Musk is referring to would fall under the International Traffic in Arms Regulations (ITAR), which restricts export of technical data tied to defense and space hardware. That likely rules out propulsion specifics for Merlin and Raptor engines along with guidance and control details for SpaceX’s launch vehicles, but leaves manufacturing knowledge, materials science, and Starlink hardware design on the table.
The announcement extends a pattern that has been building since SpaceX’s Nasdaq debut in June, when the company went public with Grok and xAI’s Colossus supercomputer folded into the pitch to investors.
Days after that listing, SpaceX closed its $60 billion all stock acquisition of coding startup Cursor, giving xAI both enterprise software distribution and a stream of real world developer data to train on. Grok 4.5 launched July 8 running partly on that Cursor training data, with Musk describing it as roughly comparable to Anthropic’s Opus 4.7 but faster and cheaper to run.
Feeding SpaceX’s own engineering data into the next AI model follows the same logic Musk has applied across xAI’s sister companies. Tesla supplies real world driving data and manufacturing expertise, X supplies conversational data, and now SpaceX supplies aerospace engineering data built up since 2002.
Musk did not give a release date for the upcoming AI model, referred to elsewhere as Grok 4.6. He has said the two trillion parameter run is in its final training phase and expected to wrap this week.
Tesla has extended its Bay Area ride-hailing service to include pickups and drop-offs at San Francisco International Airport (SFO). The update, shared via the company’s official channels on July 21, allows users in the region to request rides directly to and from one of California’s busiest airports.
The expansion builds on Tesla’s secured limousine permit for SFO operations. Public records show the permit became effective March 20, 2026, and remains active through January 31, 2027. Tesla vehicles operating the service now display authorized limousine permits issued by the City and County of San Francisco.
Our Bay Area rideshare service now goes to SFO ✈️
— Tesla AI (@Tesla_AI) July 21, 2026
Tesla’s ride-hailing program in California relies on Model Y vehicles equipped with Full Self-Driving (Supervised) technology. Human safety drivers remain present in compliance with state regulations, distinguishing the service from fully driverless operations.
The Bay Area geofence covers a broad area spanning north of San Francisco to south of San Jose, offering extensive connectivity across the region.
UPDATE: Elon Musk reveals why Tesla didn’t say ‘Robotaxi’ upon California launch
This SFO addition follows earlier progress at other Bay Area airports. Tesla previously expanded service to San Jose Mineta International Airport (SJC) in late 2025. The company had engaged with SFO, SJC, and Oakland International Airport officials as early as September 2025 to secure necessary approvals for passenger transport.
The service provides a new option for travelers seeking electric, app-based transportation integrated with Tesla’s ecosystem. Rides are booked through Tesla’s dedicated ride-hailing application, which handles matching, routing, and payments. Pricing follows standard ride-hailing models, with potential adjustments based on distance, time, and demand.
Tesla’s California ride-hailing program launched in July 2025 with an initial invite-only rollout in the Bay Area. It started alongside operations in Austin, Texas, marking the company’s second major U.S. market.
The Bay Area remains a primary focus in California, with service centered on high-demand corridors connecting residential, commercial, and now major transportation hubs. This latest airport integration represents a practical step in Tesla’s broader mobility ambitions within the state.
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