Nvidia is expanding the reach of its GPUs, focusing on a novel destination: the moon.

On Thursday, Lunar Outpost, a startup developing robotics for extraterrestrial infrastructure, revealed that its upcoming lunar rover will utilize Jetson chips to manage its lidar system. This could mark the first GPU on the surface of the moon.

“We’re assessing the Nvidia Jetson in comparison to our flight compute platform, which has a greater spaceflight legacy,” stated Justin Cyrus, CEO of Lunar Outpost. “[We’re] evaluating the advantages and disadvantages. Our goal is to integrate these advanced GPU-driven systems into extreme environments.”

NASA has initiated a program to incentivize private enterprises to survey the lunar landscape, preparing for the return of human astronauts, potentially as early as 2028. The strategy is based on its collaboration with SpaceX, urging tech firms to create vehicles equipped with scientific sensors to explore the moon’s surface to analyze its geography and search for resources like water that could be beneficial or lucrative for extraction.

Recently, Nvidia announced a partnership with Firefly Aerospace, the first private entity to successfully land a robot on the moon, which will enable the Jetson platform to function on a satellite orbiting the moon for image processing. This satellite is intended to gather data for researchers attempting to chart the moon, while also monitoring the increasing number of robots on its surface.

The next rover from Lunar Outpost is set to be delivered via a lander designed by Intuitive Machines, another tech company focused on lunar exploration. This rover is engineered to transport a suite of sensors into craters and other challenging areas that are hard to investigate from orbit. The subsequent mission will target a region known as Reiner Gamma, where scientists have been perplexed by a magnetic anomaly.

Each mission is slated to launch on a Falcon 9 rocket by year’s end.

While Nvidia’s Jetson platform may not be as recognized as AI powerhouses like Blackwell and Vera Rubin, it plays a crucial role in numerous physical AI applications. Designed to be space-efficient and compact, Jetson enables robotic systems to process sensor data locally, facilitating quicker understanding and reaction to their surroundings.

“Five years ago, our autonomy stack was more deterministic, and now it incorporates both deterministic and physical AI, which is quite exciting,” Cyrus commented. “We operate both in tandem, and it’s our responsibility to identify where physical AI can integrate into our stack and assist us in achieving unprecedented tasks.”

Employing GPUs in space presents challenges due to harsh conditions. Most space-capable GPUs orbit close to Earth, where they enjoy relative protection from radiation and significant temperature fluctuations. The moon, however, faces direct exposure to cosmic radiation and temperature extremes as it transitions through its phases.

“Your system must endure the lunar night while operating on very little power,” Cyrus stated.

Should they succeed in operating the chips in such conditions, Lunar Outpost’s engineers aspire for their vehicles to demonstrate enhanced capabilities — enabling swifter environmental processing and decision-making. NASA has extensive plans for a sustained human footprint on the moon, which will likely necessitate autonomous systems to precede and facilitate the groundwork.

“Our current mission at Lunar Outpost is to transition from exploration to establishing permanence — how we can concretely create that outpost on the moon?” Cyrus explained. “We believe that merging our deterministic models with the physical AI component will enable a sustainable human presence in space, effectively building that robotic workforce.”

In the coming years, Lunar Outpost plans to launch several smaller autonomous rovers to the moon along with a larger unit, Pegasus, intended to transport astronauts. Pegasus is awaiting launch on a rocket developed by Jeff Bezos’ Blue Origin, but the launch vehicle experienced an anomaly this summer, and the timeline for its return to service remains uncertain.

“They appear to be making good strides on the pad,” Cyrus said. “I can’t provide specifics on Blue Origin’s or NASA’s timelines regarding the pad repairs, but from what we’ve been informed, we are aligned for the 2028 timeline.”

This leaves advanced concepts of space data centers and robot fleets functioning on the moon both dependent on the same requirement: a larger rocket.

Dora Palfi hails from a lineage of educators. Thus, “it was ingrained in me that education can dramatically change the course of your life,” she stated to TechCrunch. 

In 2018, alongside Beatrice Ionascu, she established Imagi, a company dedicated to equipping K-12 students and educators with resources to teach and develop curricula centered around coding, foundational computer skills, and, since last year, AI literacy. On Thursday, the firm revealed a $4.5 million seed funding round, attracting investors such as Brighteye Ventures, Day One Capital, and the artist Will.i.am. 

Significantly, last November, the organization disclosed a collaboration with the vibe-coding platform Lovable that enables educators to design lessons and grant students supervised access to the platform, allowing them to learn vibe coding with safeguards in place. OpenAI also contributed $1 million in credits to enable schools to utilize the Imagi x Lovable tool at no cost. “We keep offering free trials and freemium opportunities due to their backing,” Palfi mentioned. 

She provided instances of outcomes stemming from the partnership thus far, such as the educator who designed an app that translated her curriculum into 15 languages relevant to her students.

“Another student created a website to promote his lawn-mowing service, which links to his calendar for direct bookings,” she noted. 

The product, in many respects, addresses the ongoing discussions about the deployment of AI in education and how youth should interact with this influential technology. In conversation with TechCrunch, Palfi asserted that the minds behind OpenAI and Lovable are “authorities in crafting cutting-edge AI tools,” while educational professionals like herself “possess the expertise to implement them safely in classrooms.” 

In this instance, safe implementation entails that every prompt and response generated by the platform is vetted, with any breaches omitted prior to reaching the students. Imagi also adheres to the Children’s Online Privacy Protection Act (COPPA), the Family Educational Rights and Privacy Act (FERPA), and the General Data Protection Regulation (GDPR) of the EU, ensuring no data retention and that Imagi’s partners do not train on student data or activities. The system also trains educators on effectively using AI, coding, and computational resources, so they can confidently relay this knowledge to students, Palfi explained. 

“Instead of being concerned about students cheating or regressing with AI, the educational landscape needs to adapt to the current situation,” Palfi remarked. “Most children are already engaging with AI, but we must guide them to create with AI instead of merely consuming it passively.”

This focus is crucial considering AI’s influence on the job markets into which these young learners will eventually transition. As not every student has access to AI tools at home, schools frequently serve as the most suitable environment to impart this new technology.

Since its inception, Imagi has collaborated with over 700,000 students in 140 nations, Palfi stated. This recent investment will facilitate expansion into additional K-12 institutions, bolster district sales, recruit talent, enhance new product features, and assist in launching a new platform next month. 

This article has been updated.

In 2022, Etched, an AI chip startup established by three Harvard dropouts, has successfully completed a $300 million Series C funding round with a valuation of $10.3 billion, according to co-founder and COO Robert Wachen in a conversation with TechCrunch.  

The funding round was spearheaded by Sequoia, joined by Andreessen Horowitz, SK Hynix, Jane Street, Diffusion Capital, and several earlier investors. Notable backers include figures such as Peter Thiel, Andrej Karpathy, Dylan Field, Amjad Masad, among others. 

Back in December, Etched had a valuation of $5 billion after raising a $500 million round, indicating it has doubled its worth in roughly seven months. The firm claims this marks the highest valuation achieved for a Sequoia-led Series C. Last month, Etched revealed it had efficiently produced its proprietary chips, with its initial full systems currently being tested by clients, alongside already securing $1 billion in orders. 

Etched emerged during a period when conceptualizing a chip tailored specifically for AI models utilizing transformer technology (the backbone of most contemporary AI systems, such as ChatGPT and Claude) was deemed extraordinary, if not absurd. The startup continues to challenge the notion that its offerings — marketed as complete systems rather than standalone chips — are limited to chips intended for specific LLMs.  

This is inaccurate, Wachen clarifies. The systems are capable of operating any AI model, including Mixture of Experts models like DeepSeek and Qwen — a structure that distributes tasks among specialized sub-models instead of depending on a singular, large model — together with non-transformer types like Mamba, which is built on a different fundamental architecture known as a state-space model. (Interestingly, the concept of embedding parts of a particular AI model directly into silicon to enhance performance is no longer regarded as far-fetched. Google is reportedly exploring a similar idea with its Frozen v2 chip for Gemini.)

Nonetheless, Etched’s current distinction lies in its development of two new components from the ground up to accelerate inference — the computing operation that occurs once a user inputs a prompt.  

“Inference consists of two stages,” Wachen articulates, “prefill and decode.” The “prefill phase” focuses on comprehending the prompt, including its context. It is mathematically intensive and requires considerable computational power. The “decode” stage produces the output tokens (the direct answer that the user observes). While it demands less computation, it requires vast amounts of memory. 

Etched has developed a prefill chip that operates “drastically” faster, he assures, “by functioning at significantly lower voltage than any other AI chip. We refer to this as low-voltage inference.” Reduced voltage generates less heat, permitting the chip to accommodate more transistors.  

In terms of the decode process, Etched has designed an innovative type of memory and “interconnect technology that we term cluster-scale memory. This enables numerous chips to connect collectively and utilize a shared memory pool at remarkably high speed and low latency,” he claims. The outcome, as Etched promises, is elevated speed along with reduced costs.

Having launched before most of the tech sector (aside from Nvidia) grasped the specialized computational requirements of AI, the founders, CEO Gavin Uberti, Wachen, and Chris Zhu, encountered numerous skeptics who remained doubtful even after the company disclosed the successful production of its first batch of silicon by TSMC.

Much of this skepticism stems from the limited number of individuals who have had access to the systems. To date, access has been restricted to investors and initial customers. Indeed, this is how Etched attracted its group of renowned investors initially — by offering them private demonstrations in their office.

“Andrej Karpathy from Anthropic, Noam Brown from OpenAI, Geoffrey Hinton, along with all the investors in this funding round — these individuals all actually tried the hardware and are very enthusiastic about it,” Wachen states.  

Nevertheless, the journey has been challenging, and more obstacles lie ahead before the rack systems can be mass-produced and distributed. The trio is renowned for dropping out of Harvard to start Etched, without a clear understanding of how to secure funds (let alone the large amounts required) or how to hire effectively. 

“We had no clue how challenging it would be,” Wachen remarks. “I believe we still need to remain humbled by what it will demand to actually scale.” 

Wachen recalls arriving in the Bay Area after informing his parents of his decision to leave school for a startup, with no office or housing arranged. He was forced to sleep on the floor of a friend’s unfurnished residence. 

“I recall staying at my friend’s house, which was about to be sold, using a towel as a blanket,” he chuckles.  The founders ultimately set up the necessary servers for running the chip-design tools in an early employee’s garage, and “every time they needed to be rebooted, he would call his wife, and she would go and hit the reboot button.” 

Now, there are 400 employees thriving in an office, and Etched manages a 2 megawatt data center there. Furthermore, it has just opened a brand-new 80,000 square-foot, 10MW facility in Milpitas, situated not far from its primary San Jose office.

“Today, we are processing tokens in our lab, collaborating with some of the largest AI companies in the world,” he shares. 

Wachen also has a blanket now, along with a mattress “and even a pillow. Multiple pillows,” he jokes.  

More significantly, he and his co-founders have never allowed the naysayers to deter them. “It has come a long distance. The world is markedly different. However, I believe that when you truly believe something is achievable, and you dedicate yourself to it over time, you can accomplish it.”

Note: This narrative was updated to add a reference to the new 10MW facility.

Google is on the verge of adding yet another name to its extensive roster of products boasting over a billion users, a roster that already features Search, Gmail, Drive, Android, YouTube, and Chrome. During its Q2 2026 earnings call, the company revealed that the AI assistant Gemini has surpassed 950 million monthly users.

The firm highlighted that the number of Gemini users has tripled compared to last year. Back in February, it was reported that the Gemini app had exceeded 750 million monthly active users. With this surge, Google’s assistant is positioned to rival OpenAI’s ChatGPT more closely, which achieved 1 billion monthly active users in June.

“Users appreciate new agentic features such as Daily Brief and our personalized agent, Gemini Spark, which is now accessible in the U.S. and globally. We’ve been introducing valuable new features like this at a remarkable pace,” stated Alphabet CEO Sundar Pichai during the call.

In addition to Android users, the Gemini app has established a robust user base on iOS, aided by launches like the Nano Banana image generation model. According to Appfigures, the app has been downloaded more than 137 million times on iOS over the past year.

In its most recent “State of AI” report, the analytics company Sensor Tower indicated that ChatGPT’s market share among AI assistants dipped below 50% for the first time. The report, which examined the first half of 2026, also noted that Gemini’s share increased to 27.7%.

Numerous individuals are already utilizing AI assistant applications as an alternative to search engines. Nevertheless, Google reported that its search segment remains robust, partly due to the AI-focused revamp. In this quarter, its Q&A-style AI mode surpassed 1 billion users. The company mentioned that it is contributing to “an incremental increase” in search queries. Google also stated that through hardware advancements, it has lowered the costs associated with AI mode for the company while still rolling out new models and features.