Techin' Geek

The apparel sector is aware of its waste issue. Approximately one garbage truck’s worth of textiles is discarded every second. In addition, this sector produces more carbon emissions than combined international flights and maritime shipping. 

Some businesses are trying out innovative methods to recycle textile waste, while others are creating new materials that do not rely on fossil fuels. One startup, Rubi, is “essentially extracting the machinery of biology from the cell” to create the foundational components of lyocell and viscose, co-founder and CEO Neeka Mashouf shared with TechCrunch. The technology developed by the startup will enable any firm using cellulose to manufacture products from captured carbon dioxide.

Rubi has recently secured $7.5 million to construct a demonstration-scale version of its cellulosic production system, aimed at generating tens of tons of material by using CO₂ as its primary ingredient. This funding round was spearheaded by AP Ventures and FH One Investments, with additional involvement from CMPC Ventures, H&M Group, Talis Capital, and Understorey Ventures, as exclusively reported to TechCrunch by Rubi.

The startup has secured over $60 million in non-binding off-take deals with several partners, Mashouf indicated to TechCrunch. The company has conducted material testing with 15 pilot partners, including H&M, Patagonia, and Walmart.

To create cellulose for lyocell or viscose, Rubi employs enzymes. This approach is distinct from other startups that may utilize engineered bacteria in a fermenter or chemical catalysts to convert carbon dioxide into the required compound. Currently, the majority of cellulose is sourced from trees, encompassing plantations and untapped rainforests.

“These textile and raw material supply chains are very lengthy,” Mashouf remarked. “In the U.S., we’ve seen interest in the ability to actually produce textile-grade cellulose pulp, which is not currently available.”

The inspiration to use enzymes arose when Mashouf, a scientist focused on researching new materials, collaborated with her twin sister, Leila, a medical student at Harvard Medical School. “We examined all the existing technology,” she noted, but always returned to enzymes.

The enzyme sector is substantial, she stated. It is utilized in the production of high-fructose corn syrup and in the treatment of wastewater. “The existing capacity is already available and can be quite cost-effective.”

Rubi employs a “cascade” of enzymes to process waste carbon dioxide. The company has integrated AI and machine learning techniques to enhance the enzymes’ efficiency and stability. 

At present, the enzymes are suspended in an aqueous solution; as carbon dioxide is introduced, white cellulose will form within minutes inside the reactor, Mashouf explained. The reactors are designed to fit within modules the size of shipping containers. Ultimately, Rubi intends to modify its process for continuous production.

While the startup aims to serve apparel companies as its initial clients, it aspires to provide cellulose to any sector that utilizes it in the future. “This truly is a foundational platform,” Mashouf asserted. “We view it as a means to produce all the crucial chemicals and materials across the economy at a reduced cost.”

Electricity serves as a crucial raw material for artificial intelligence, yet emerging processing methods surpass the capacity of data center operators to handle their power grid interactions, compelling them to reduce output by as much as 30%.

“There is an immense amount of energy wasted in these AI facilities,” stated Nvidia CEO Jensen Huang during a keynote address at the company’s annual GTC customer conference. “Every watt that goes unused equates to lost revenue,” the firm asserted during the yearly presentation.

Now, the startup Niv-AI has surfaced from stealth mode with $12 million in seed funding aimed at addressing this issue by accurately gauging GPU power consumption with innovative sensors and creating tools to manage it more effectively.

Founded in Tel Aviv last year by CEO Tomer Timor and CTO Edward Kizis, the startup counts Glilot Capital, Grove Ventures, Arc VC, Encoded VC, Leap Forward, and Aurora Capital Partners among its backers. The company opted not to disclose its valuation.

As advanced labs utilize thousands of GPUs simultaneously to train and operate complex models, intermittent, millisecond-level spikes in power demand occur when processors alternate between computational tasks and communication with other GPUs.

These spikes create challenges for data centers in managing their power intake from the grid. To prevent potential power shortages, data centers invest in temporary energy storage to handle surges or limit their GPU workloads. Both options diminish the return on investments in high-cost chips.

“We simply cannot continue constructing data centers the way we currently do,” remarked Lior Handelsman, a partner at Grove Ventures who serves on Niv’s board.

The initial phase of Niv’s strategy involves gaining insight into ongoing operations; the company is currently rolling out rack-level sensors that monitor power consumption at the millisecond level on GPUs that they possess and those of their design partners. The objective is to comprehend the distinct power profiles of various deep learning tasks and develop strategies that enable data centers to tap into more of their current capabilities.

Predictably, the engineers plan to develop an AI model based on the data they gather, aiming to train it to forecast and coordinate power loads across the data center — functioning as a “copilot” for data center engineers.

Niv-AI anticipates having an operational system in several U.S. data centers within the next six to eight months. This prospect is appealing, as hyperscalers looking to establish new data centers encounter challenging land-use and supply chain obstacles. The founders envision their final product as an essential “intelligence layer” bridging data centers and the electrical grid.

“The grid is genuinely concerned about the data center drawing excessive power at a particular moment,” Timor shared with TechCrunch. “The issue we are addressing is one with two facets: One aspect is to assist data centers in better utilizing their GPUs and, ideally, maximizing the power they are already paying for. Conversely, there’s a chance to create much more responsible power profiles between the data centers and the grid.”

Amazon is introducing one-hour and three-hour delivery services in various cities across the U.S. as the e-commerce leader aims to rival instant delivery services such as Instacart, DoorDash, and Uber Eats.

The retail giant is offering over 90,000 products through this new delivery method. If a user can receive an item within one or three hours, a label will indicate this next to that item in the Amazon app. Additionally, there is a filter for these new delivery choices available in the app and on the website.

Subscribers to Amazon Prime will be billed $9.99 for one-hour deliveries and $4.99 for three-hour deliveries. Non-Prime members will incur charges of $19.99 for one-hour deliveries and $14.99 for three-hour deliveries.

Amazon stated that it is rolling out the one-hour delivery service in hundreds of U.S. cities, including sectors of major urban areas like Los Angeles, Chicago, and Washington, D.C., along with Des Moines, Boise, and American Fork. The three-hour service is set to be available in more than 2,000 cities and towns across the U.S.

Additionally, the firm is launching a specific storefront to showcase items that qualify for these new delivery options.

“Our customers lead increasingly busy lives and are seeking innovative solutions to save time while managing their households. We recognized an opportunity to leverage our distinct operational know-how and delivery infrastructure to streamline our customers’ lives, offering enhanced value for Prime members,” said Udit Madan, senior vice president of Worldwide Operations at Amazon, in a remark.

The corporation mentioned that it is utilizing its current same-day fulfillment centers for these new delivery options.

This marks not the first attempt by Amazon at instant deliveries. The company previously initiated one-hour deliveries through the “Prime Now” service in 2014, but discontinued it in 2021. Later, in December 2025, it tested a 30-minute delivery option in Seattle and Philadelphia.

The firm has been striving to enter the quick-commerce sector on a global scale. In India, it introduced Amazon Now in 2024, providing a 10-minute delivery service for groceries and various products, which was expanded to multiple cities last year. Amazon also launched the service in the United Arab Emirates last October, pledging deliveries within 15 minutes.

Nvidia’s CEO Jensen Huang believes that every organization should adopt an OpenClaw strategy. Nvidia is ready to assist in that endeavor.

During his GTC keynote on Monday, Huang revealed Nvidia’s creation of NemoClaw, a platform designed for enterprises, rooted in the popular local AI autonomous agent.

This open-source platform is primarily OpenClaw, enhanced with robust enterprise security and privacy features. The objective is to transform OpenClaw into a secure space that businesses can access effortlessly, managing agent behavior and data handling, as stated by the company.

“For CEOs, the critical question is, what’s your OpenClaw strategy?” Huang remarked on stage. “We all possess a Linux strategy. Everyone required an HTTP HTML strategy, which initiated the internet. We all had to develop a Kubernetes strategy, enabling mobile cloud functionality. Every company globally needs an OpenClaw strategy, a strategy for agentic systems.”

According to Huang, Nvidia collaborated with Peter Steinberger, the original creator of OpenClaw, to devise NemoClaw.

Upon its launch, users of NemoClaw will have the ability to utilize any coding agent or open AI model, including Nvidia’s NemoTron open models, to create and implement AI agents. The platform permits access to cloud-based models from local devices. It’s hardware-agnostic and does not require Nvidia’s GPUs, integrating seamlessly with NeMo, Nvidia’s AI agent software suite.

Currently, Nvidia labels NemoClaw as an early-stage Alpha software. “Expect some rough edges. We are working towards a production-ready sandbox orchestration, but our initial focus is on establishing your personal environment,” the company mentioned on its website for developers.

In recent months, the development of enterprise AI agent platforms has become a major focus in the AI industry.

In February, OpenAI introduced OpenAI Frontier, an accessible platform for enterprises to construct and oversee AI agents. Last December, the global research firm Gartner published findings indicating that governance platforms for AI agents are essential infrastructure for enterprises looking to adopt AI technology. Nvidia has undoubtedly taken note.

“OpenClaw provided us, the industry, exactly what was needed at the right moment,” Huang stated. “Just like Linux met industry needs at the perfect time, like Kubernetes emerged precisely when required, and HTML arrived as well. This allowed the entire industry to embrace this open-source stack and utilize it effectively.”

During his keynote on Monday that launched the company’s annual GTC Conference in San Jose, California, Nvidia CEO Jensen Huang shared a multitude of figures — predominantly technical ones.

However, there was one financial statistic that surely caught the attention of investors: his forecast indicating there would be $1 trillion in orders for Nvidia’s Blackwell and Vera Rubin chips, a financial indicator of a flourishing AI market.

About an hour into his address, Huang pointed out that last year Nvidia experienced around $500 billion in demand for its Blackwell and forthcoming Rubin chips up to 2026.

“Now, I don’t know if you guys feel the same way, but $500 billion is an enormous amount of revenue,” he stated. “Well, I’m here to tell you that from where I stand — just a few months post-GTC DC, one year post the last GTC — right here where I am, I foresee through 2027, at least $1 trillion.”

The Rubin computing chip architecture, first unveiled in 2024, has been characterized by Huang as the pinnacle of AI hardware, surpassing its Blackwell predecessor. The company announced in January, when it formally commenced production of Rubin, that it would operate 3.5 times faster than the Blackwell architecture on model-training tasks and 5 times quicker on inference tasks, achieving up to 50 petaflops.

Nvidia has indicated that it anticipates increasing production in the latter part of the year.

Senator Elizabeth Warren (D-MA) addressed a letter to Defense Secretary Pete Hegseth on Monday voicing her concerns regarding the Pentagon’s choice to grant Elon Musk’s firm xAI access to classified networks.

“Grok, the contentious AI model created by xAI, has produced troubling results for users, including offering ‘advice on committing murders and terrorist acts,’ generating antisemitic material, and creating child sexual abuse content,” the correspondence states. 

Warren noted Grok’s “clear absence of sufficient safeguards” could present “serious threats to the safety of U.S. military personnel and the cybersecurity of classified systems.” She insisted that Hegseth provide details on how the Department of Defense intends to “address these possible national security dangers.”

Warren is not the first to raise concerns about Grok, xAI’s contentious chatbot, obtaining access to classified systems. Last month, a coalition of nonprofits called on the government to promptly halt Grok’s deployment in federal agencies, including the DoD, after X users persistently urged the chatbot to transform actual photos of women, and in some instances children, into sexualized images without their consent. On the same day Warren dispatched her letter, a class action lawsuit was initiated against xAI claiming Grok had produced sexual content from authentic images of the plaintiffs as minors. 

The letter follows the Pentagon’s ruling to classify Anthropic as a supply chain risk after the AI company declined to grant the military unrestricted access to its AI systems. Until recently, Anthropic was the sole AI firm with systems ready for classified use. Amid that dispute, the DoD secured an agreement with OpenAI and xAI to utilize their AI systems within classified networks, as reported by Axios. 

A senior official at the Pentagon verified that Grok was integrated for use in a classified environment but is not currently operational.

“It remains uncertain what guarantees or documentation xAI has presented to the Department of Defense regarding Grok’s security measures, data management practices, or safety protocols, and whether the DoD has assessed those assurances prior to reportedly permitting Grok access to classified systems,” Warren states.

Warren sought a copy of the agreement allegedly made between the DoD and xAI concerning the use of Grok in classified systems and an explanation of how the department plans to prevent Grok from being vulnerable to cyberattacks and ensure it will “not disclose sensitive or classified military information.”

(Last week, a former employee from Musk’s Department of Government Efficiency supposedly stole personal data from Americans at the Social Security Administration and saved it on a thumb drive — marking the latest allegation of DOGE-related data leakage.)

Chief Pentagon spokesperson Sean Parnell stated that the department “anticipates deploying Grok to its official AI platform GenAI.mil in the very near future.”

GenAI.mil is the military’s secure enterprise platform for generative AI, providing DoD personnel access to large language models (LLMs) and other AI resources within government-sanctioned cloud environments. It is primarily designed to assist with non-classified tasks such as research, document drafting, and data analysis. 

Shawn Shen asserts that for AI to thrive in the physical realm, it must have the capability to remember what it observes. Shen’s venture, Memories.ai, employs Nvidia AI technologies to establish the framework for wearables and robotics to retain and retrieve visual recollections.

On Monday, at its GTC conference, Memories.ai revealed a partnership with the semiconductor powerhouse Nvidia. This collaboration allows Memories.ai to leverage Nvidia’s Cosmos-Reason 2, a reasoning vision language model, along with Nvidia Metropolis, a tool designed for video search and summarization, to further enhance its visual memory capabilities.

Shen (shown above left) informed TechCrunch that he and his co-founder and CTO, Ben Zhou (depicted above right), conceived the idea for the company while developing the AI behind Meta’s Ray-Ban sunglasses. The creation of these AI glasses prompted them to consider how users would effectively engage with the technology in real-world scenarios if they could not remember the recorded video data.

They searched for existing solutions focused on that specific visual memory aspect for AI but, finding none, made the decision to depart from Meta and create the solution independently.

“AI is excelling in the digital arena. How about in the physical space?” Shen remarked. “AI wearables and robotics require memories too. Ultimately, visual memories for AI are essential. We envision that future.”

The capacity of AI systems to retain information is a relatively recent development. OpenAI enhanced ChatGPT to start remembering prior conversations in 2024 and refined that capability in 2025. Elon Musk’s xAI and Google Gemini have both introduced their own memory functionalities over the last two years.

However, Shen pointed out that these developments primarily concentrate on text-based memory. Text-based memory is more organized and simpler to index but falls short for physical AI applications that predominantly engage with their environment visually.

Founded in 2024, Memories.ai has secured $16 million to date, garnered from an $8 million seed round in July 2025 complemented by an $8 million extension. The funding round was spearheaded by Susa Ventures and included participants such as Seedcamp, Fusion Fund, and Crane Venture Partners.

Shen indicated that creating this visual memory layer successfully necessitated two elements: establishing the required infrastructure to assimilate and organize videos into a data-friendly format for storage and retrieval, along with gathering the necessary data to train the model to achieve that goal.

The organization unveiled its large visual memory model (LVMM) in July 2025. Shen mentioned it as a smaller counterpart to Gemini Embedding 2, a multimodal indexing and retrieval model released earlier this month.

For data collection, the company developed LUCI, a device worn by its “data collectors” that captures video to train the model. Shen stated they do not intend to evolve into a hardware company or market these devices, but rather created their own as they were dissatisfied with existing high-definition video recorders that consumed too much battery.

The firm has rolled out the second iteration of this LVMM and has partnered with Qualcomm to operate on Qualcomm’s processors starting later this year.

Memories.ai is collaborating with some major wearable companies already, according to Shen, though he refrained from naming them. Despite current demand, he anticipates even greater potential in wearables and robotics in the future.

“In terms of commercialization, we are concentrating more on the model and infrastructure, because we ultimately believe the wearables and robotics market will emerge, but it may not be immediate,” Shen explained.

In the past ten years, the electrical grid has undergone more transformation than in the previous fifty. Solar power, wind energy, and battery technology have shifted electricity generation from centralized producers. However, the grid continues to face the same core issues.

“The issue with the grid is primarily a peak issue. Typically, power levels are sufficient, but during peak periods, there may not be enough available,” stated Michael Phelan, co-founder and CEO of GridBeyond, in a conversation with TechCrunch.

Currently, these power shortages are especially affecting technology firms and data center operators, which require substantial electricity to train and run AI systems. 

“However, if you have adequate energy stored in a battery or can reduce an industrial load, which can reach hundreds of megawatts, you can initiate the establishment of those hyperscalers,” Phelan added.

GridBeyond is developing both hardware and software to integrate various segments of the grid into larger virtual power plants. The startup is already responsible for managing approximately 1 gigawatt of solar, batteries, wind, and hydropower, and has “several gigawatts” on the demand side across commercial and industrial sites, according to Phelan.

To broaden its offerings, GridBeyond recently secured a €12 million ($13.8 million) equity round led by Samsung Ventures, as exclusively reported by TechCrunch. Other investors include ABB, Act Venture Capital, Alantra’s Energy Transition Fund, Constellation Technology Ventures, EDP, Energy Impact Partners, Enterprise Ireland, Klima, Mirova, and the Japanese electronics and software company Yokogawa.

The startup has implemented its hardware controllers in batteries and renewable energy facilities, as well as substantial commercial and industrial operations across Australia, Ireland, Japan, the U.K., and the United States.

Similar to various virtual power plant companies, GridBeyond, based in Dublin, originated on an island. As Ireland began incorporating wind energy, Phelan noted, “they encountered an issue due to their island status, requiring them to balance the grid. Consequently, it was very applicable for them to have flexible loads they could introduce into the market.”

For an extended period, grid operators have requested large consumers to curtail their power consumption during extreme heat events, often providing financial incentives for reducing peak demand. This method is more cost-effective than constructing new transmission infrastructure or energy generation facilities. As renewable energy has proliferated, this strategy has been adopted more widely, enabling industrial and commercial clients to lessen their energy usage at night or during periods of low wind.

Recently, batteries have introduced a new element. GridBeyond oversees several significant energy storage projects, including a 200-megawatt battery in California. This flexible supply source helps address fluctuations in renewable energy output.

Batteries present another benefit: they can respond to demand much more swiftly than conventional peaking power plants, which may take minutes to activate. This capability allows the company to engage in rapid buying and selling of power through arbitrage. 

Additionally, it opens up new opportunities for data centers. Many facilities do not require a constant power supply, instead peaking during AI training sessions. These peaks can disrupt the grid—“akin to the issue that caused the collapse of the Spanish grid, which is not desirable,” Phelan explained. Batteries located at data centers can mitigate much of this load, stabilizing the site’s demand pattern on the grid to prevent unwanted fluctuations. 

By connecting to a nearby virtual power plant or utilizing batteries on-site, “it’s evidently simpler for them to establish a connection,” he mentioned.

Update 5:30 pm ET: The article was revised to specify that the investment originated from Constellation’s venture division, Constellation Technology Ventures.

Apple has purchased MotionVFX, a firm specializing in the creation of plug-ins, templates, and advanced features for Apple’s Final Cut Pro video editing application. The financial details of the transaction remain undisclosed.

“We are incredibly thrilled to announce that MotionVFX is becoming part of the Apple family to further enable creators and editors to excel in their work,” MotionVFX stated in a post on its website. “For more than 15 years, our goal has been to develop top-tier, visually impactful content and effects for video editors. From the outset, our focus has been on quality, user-friendliness, and exceptional design. These principles are also what we respect most in Apple’s offerings, and we are excited to unite our visions.”

Apple, which seldom reveals its acquisitions publicly, did not provide a response to TechCrunch’s inquiry for comment. TechCrunch will revise this article should Apple reply.

Founded in 2009 and based in Warsaw, MotionVFX provides subscription services starting at $29 monthly for access to its professional-level video editing solutions, graphics, and templates. Apple’s acquisition of the company is expected to lead to the integration of MotionVFX’s tools within the tech titan’s offerings.

Moreover, this strategy could enhance Apple’s competitiveness against Adobe Premiere Pro and the entire Adobe Creative Cloud ecosystem.

In January, Apple introduced Creator Studio, a subscription package that gives access to six creative applications along with premium content in iWork applications. The package is priced at $12.99 per month or $129 annually and features access to Final Cut Pro, Logic Pro, and Pixelmator Pro on both Mac and iPad, as well as Motion, Compressor, and MainStage on Mac. It also offers premium content for Keynote, Pages, and Numbers.

Through the acquisition of MotionVFX, Apple aims to draw more subscribers to its Creator Studio package.

In recent years, Apple’s services sector has emerged as one of its most significant growth catalysts. During the last fiscal year, this division represented over 26% of revenue, a remarkable rise compared to the 8.5% reported in 2015.