The project, which was funded by a grant from the Shell Foundation, aimed to introduce electric vehicles to Africa's massive market. The Shell Foundation, established by British oil and gas giant Shell plc, had initially highlighted the potential of the project on its website, stating that it would help de-risk the entry of global OEMs into East Africa's EV market.

The plan was ambitious: Also was set to develop modular battery designs and distributed EV charging systems, in addition to designing a purpose-built electric motorcycle tailored to African riders' needs. The company was expected to integrate these innovations into its platform, with the potential for scaling across the region.

Kenya's massive two-wheeler market has become an attractive opportunity for electric motorcycles, with some companies seeing significant growth in recent years. This trend has caught the attention of Chinese investors and mobility companies, who are now pouring resources into the continent to capitalize on this emerging market.

Also's early-stage e-moto project in Kenya was put on hold due to shifting priorities within the company.

According to an email sent by Also in September, the project was explored with a partner but ultimately abandoned after some initial work was completed. The grant funding received from the Shell Foundation is still available to support the project's ongoing development, although specifics are scarce.

The Shell Foundation initially stated that the Kenya pilot was intended to gather data on driver income and operational performance, aiming to better understand the market opportunity. However, when pressed for more information, the organization declined, citing a nondisclosure agreement with Also.

Also's co-founder and president Chris Yu explained during an interview at TechCrunch Disrupt that the Kenya project initially aligned with the company's mission of building cost-optimized vehicles tailored to specific markets.

The Africa project, which was initially aligned with Also's mission of building cost-optimized vehicles tailored to specific markets, ultimately fell by the wayside due to a shift in focus.

According to Chris Yu, Also's co-founder and president, the company decided to prioritize its efforts on autonomy, as it believed this technology would have a greater impact in smaller, purpose-built vehicles rather than passenger cars. This decision was driven by the urgency and pace of advancements in autonomy, which seemed to be accelerating rapidly.

The Africa project's demise coincided with Also's own rocky first year as an independent company. The startup faced significant supply chain issues that forced it to repeatedly delay deliveries of its flagship product, a premium e-bike called the TM-B. This led to frustration among customers who had reserved one, but were left in the dark about when they could expect their bikes.

Also's leadership has acknowledged that the company made a mistake by not communicating effectively with its reservation holders during this time. In fact, Chris Yu views the criticism as an opportunity for Also to improve its communication and engagement with customers, allowing it to earn their trust and feedback.

Also's focus on launching its first product, the TM-B e-bike, has been a crucial step in the company's growth ambitions. The bike's striking design has generated significant interest among consumers and will serve as a key showcase for the brand.

The company's plans to expand beyond e-bikes are well underway, with commercial cargo bikes set to be launched soon. These new products, including four-wheeled models, have the potential to bring in higher revenue streams for Also, particularly through partnerships with companies like Amazon and DoorDash.

According to Yu, no single issue was responsible for delaying the TM-B's launch. Instead, the company faced a series of complex challenges related to supply chain management. The bike itself is a highly intricate product, described as a "kind of a computer on wheels," making it vulnerable to disruptions in raw materials and certification processes.

Also encountered difficulties in securing the necessary components for production. At one point, the company found itself competing with other manufacturers for printed circuit board materials used in AI data centers. Additionally, navigating varying government regulations proved to be a significant challenge, requiring Also to adapt quickly to changing circumstances.

The company's communication strategy has undergone significant changes as it navigates the challenges of launching its first products to customers. Initially, Also struggled to provide timely updates on production and shipping timelines, leading to frustration among early adopters.

However, the team has made a concerted effort to improve transparency in recent times, acknowledging that clear communication is crucial during this critical phase. This shift in approach has earned them some goodwill from customers who appreciate the company's willingness to learn from its mistakes and adapt accordingly.

Some of these customers have taken to online forums to share their experiences with Also's products, highlighting issues such as delivery damage and noticeable battery drain. While these problems are not uncommon for a first-time product launch, they do underscore the importance of robust quality control measures in ensuring customer satisfaction.

As Also continues to work through these kinks, it will likely face increased scrutiny from customers who have already invested in its products. The company's ability to address these issues effectively will play a significant role in determining its long-term success and reputation in the market.

The challenges faced by Also are not unique to this startup alone, as many companies in the electric vehicle space have struggled with similar issues during their early stages of development.

The electric vehicle space has been fraught with challenges for several companies, including Also, a spinout from Rivian that attempted to develop an e-moto project in Kenya.

Also's efforts were ultimately unsuccessful, and it appears that the company abandoned its plans in the country. The exact reasons behind this decision are unclear, but it's likely that the startup faced significant obstacles in bringing its vision to life.

The setbacks experienced by Also serve as a reminder of the difficulties that many companies in the electric vehicle sector have encountered during their early stages of development, making it a challenging space for innovation and growth.

TechCrunch: https://techcrunch.com/2026/11/03/rivian-spinout-also-owns-up-to-mistakes-in-delayed-e-bike-launch/

The technology has been gaining traction in the automotive industry, with major players such as Ford Motor and Rivian Automotive investing heavily in 3D printing capabilities. This shift towards additive manufacturing is expected to have far-reaching implications for the sector.

Rivian's head of additive manufacturing, Jared Beck, notes that the company is scaling up its use of 3D printing across all areas of operations. According to Beck, this move aims to democratize access to 3D printing within the company.

The process itself involves creating three-dimensional objects from digital designs by layering materials such as plastics, composites, and metals. This allows for greater flexibility in production and can result in significant cost savings compared to traditional manufacturing methods.

Manufacturers are also drawn to the versatility of 3D printers, which can produce individual pieces or large batches of smaller parts depending on the specific requirements of a project.

Rivian's investment in 3D printing technology has been substantial, with the company having spent over $5 million on machines alone. The cost of materials for its operations has also increased to around $1.7 million annually.

Despite these costs, Beck believes that the machines typically pay for themselves within a year. One key advantage of 3D printing is that it can help reduce expenses in several areas, including supplier tooling costs and logistics expenses.

The technology also enables production times for parts to be significantly reduced, from weeks to just days or even hours. This rapid turnaround has been particularly beneficial for Rivian's operations, where speed is a major priority.

Rivian has expanded its 3D printing capabilities in recent times, with the addition of new machines capable of producing flexible silicone parts. The company has also set up a dedicated bay at its Illinois plant where employees can print parts on demand as needed.

Ford has taken a decentralized approach to additive manufacturing by establishing departments for this technology at multiple plants across its operations.

These departments are responsible for producing and distributing parts as needed, streamlining the process and reducing reliance on centralized facilities.

A prime example of this strategy is the vending machine set up near Ford's Dearborn, Michigan headquarters, which dispenses 3D-printed parts directly to production lines building F-150 pickup trucks.

The vending machine is stocked by Ford's 3D-printing teams, who also help develop new parts and tools designed by employees using in-house software.

Employees can request specific auto parts or tools through an app, which are then printed on demand, eliminating the need for inventory storage and reducing production time.

The benefits of 3D printing in the automotive industry are becoming increasingly apparent as companies like Ford continue to explore its potential. By creating tools with this technology, automakers can design them on demand, reducing production time and often lowering costs.

In some cases, 3D-printed parts have allowed production to carry on uninterrupted even when a permanent replacement was not readily available. For example, a large machining wheel that was urgently needed to maintain assembly line production was successfully printed until a supplier could provide a more durable alternative.

While the performance of these interim parts may not be comparable to their traditionally manufactured counterparts, they served as a vital stopgap solution in critical situations. This highlights the versatility and adaptability of 3D printing technology in responding to unexpected needs.

As Ford expands its use of this technology, it expects to deploy 3D labs at more than 23 plants by year's end, representing a significant escalation of its current program. The company's existing 3D-printing initiative has already grown to encompass over 200 machines, with additional printers operating outside the official program.

General Motors has been utilizing 3D printing for various components of its high-end vehicles, including the Cadillac Celestiq and performance-oriented Blackwing sedans. Specifically, the company uses this technology to produce over 135 custom parts for these models.

According to Fadi Abro, senior global director of automotive and mobility at Stratasys, GM's adoption of 3D printing is an exemplary case of how companies can standardize and scale up their use of this technology. This approach has led to significant improvements in material properties, expanding the potential applications for these components.

CNBC: https://www.cnbc.com/2026/10/31/automakers-3d-printing-ford-rivian-gm.html

The company's shares saw a significant boost in after-hours trading on Thursday, rising by around 7% following a day that began with the stock hitting a new 52-week low of $11.38. Despite this increase, the stock closed at $11.45 per share, down 1.9% from its opening.

Rivian has also revised its guidance for 2026, outlining expected improvements in vehicle deliveries, pre-tax adjusted earnings and capital expenditures. The new projections call for a narrower pre-tax adjusted loss of between $1.75 billion and $1.85 billion, representing an improvement of $100 million at the midpoint from previous estimates.

The company attributed the improved guidance to various factors, including higher-than-expected revenue generated by the sale of regulatory credits, a refund related to IEEPA tariffs received in the third quarter, and projected increases in vehicle deliveries.

Rivian's R2 model has emerged as the company's top seller, accounting for a significant portion of its quarterly gains. The first deliveries of the R2 to customers took place in June, and it appears that this vehicle has been a major contributor to Rivian's recent success.

The company's overall delivery numbers have also reached new heights, with 19,248 units shipped between July and September. However, Rivian does not break down its delivery figures by specific vehicle model, so the exact contribution of each model remains unclear.

Rivian's financial performance continues to be shaped by its ongoing transition from a loss-making entity to one that is narrowing its losses. The company reported a net loss attributable to common stockholders of $913 million for the third quarter, down from a loss of $1.17 billion in the same period last year.

The company's software and services segment has been driving growth, generating $605 million in revenue with a gross profit margin of 42%. This is in contrast to its automotive operations, which reported nearly $1.55 billion in revenue but incurred a gross loss of $80 million.

Rivian's R2 model is expected to achieve a positive gross margin by the end of this year, according to the company's latest projections. This milestone will be crucial in contributing to the overall profitability of Rivian's business.

The company's CEO, RJ Scaringe, emphasized that scaling up production beyond the current 160,000 units planned for the R2 model is essential to achieving positive gross margin on this vehicle and the entire business. He noted that unit economics will continue to improve throughout the fourth quarter and into next year's first quarter.

Rivian's cash reserves have also been boosted, with a balance of $5.5 billion in cash, cash equivalents, and short-term investments as of the end of the third quarter, up from $5.3 billion at the end of the second quarter.

CNBC: https://www.cnbc.com/2026/10/29/rivian-rivn-earnings-q3-2026.html

The release of Genie 4 comes at a time when the world model industry is rapidly evolving. Just recently, several key players have announced significant developments or acquisitions that are reshaping the landscape. Runway's GWM Worlds 2, for instance, was released as a playable model with dynamic response to user inputs and audio generation capabilities.

The consolidation of major players in the field has also become apparent. World Labs, founded by Fei-Fei Li, is being acquired by AMD, while Amazon is reportedly engaged in talks to acquire Decart. Rivian's acquisition of Third Dimension further underscores the trend towards bringing simulation capabilities in-house for specific use cases.

Google's decision to release Genie 4 as a research preview suggests that the company is committed to pushing the boundaries of this technology. The new model builds upon its predecessor, Genie 3, which was released around a year ago and featured improved photorealism but lacked audio capabilities.

Genie 4 offers several key improvements over its predecessor, including freeform edits, real-time weather and camera angle adjustments, and the ability to add or remove objects and people. The model can maintain a consistent scene for up to two minutes, doubling the previous limit, and boasts better physics and more human-like characters.

Google's Genie 4 world model has made significant strides in its capabilities, and it is now more closely integrated with Gemini, a large language AI model developed by Google.

Gemini acts as a director for Genie 4, planning steps and checking frames while the latter creates visuals. This integration has enabled researchers to conduct experiments that demonstrate the potential of hybrid world models. In one such experiment, a Gemini 4 Argon model broke down tasks into steps that were then simulated in real-time by Genie 4.

The results of this research suggest that it may be possible to test robot scenarios in simulation before they are implemented in the real world. This could have far-reaching implications for various industries, including robotics and manufacturing.

According to Google's research director, Tejas Kulkarni, hybrid world models will become increasingly common in the future. These models combine large language AI capabilities with simulated reality, allowing users to plan, visualize, and test complex scenarios in real-time.

In a briefing, Diego Rivas, a Google DeepMind engineer, noted that the real-time aspect of Genie 4 becomes particularly valuable during creative phases such as ideation and storyboarding. This suggests that the model may have applications in film prototyping and other fields where rapid idea generation is essential.

The Genie 4 world model is also being used to generate high-definition video clips with synchronized audio from text, image, or video prompts using Google's Veo AI video generation model. This tool has been gaining popularity among filmmakers who can use it to create professional-looking videos quickly and efficiently.

In the near future, users may be able to rely on another AI model, Gemini Omni, to turn those prototypes into creative assets such as video, audio, or images. However, this capability is still in development and not yet available for public use.

One of the key features of Genie 4 is its ability to generate more realistic worlds with accurate details and objects that remain consistent over time. However, the team behind the model acknowledges that there are still some gaps to be addressed, including issues with audio accuracy and text legibility within the simulated world.

The Genie 4 world model is currently available as a research preview for trusted testers, but it will soon be rolled out to Google AI Ultra subscribers in Project Genie. Additionally, early access partners of the Gemini API and Google AI Studio will also gain access to the model in the coming weeks.

Google's Genie 4 world model has been upgraded to include audio capabilities, allowing users to interact with virtual environments in a more immersive way.

This significant update also enables the creation of more realistic and complex worlds within the model, providing developers with greater flexibility when designing their applications.

Additionally, the model will now support real-time steering, enabling smoother and more responsive interactions between users and virtual objects or characters.

The upgrade is expected to benefit early access partners of the Gemini API and Google AI Studio, who will gain access to the updated model in the coming weeks.

TechCrunch: https://techcrunch.com/2026/10/27/googles-genie-4-world-model-adds-audio-more-realistic-worlds-and-real-time-steering/

The acquisition is expected to accelerate the development of advanced driver-assistance features and self-driving systems for Rivian's planned robotaxis, which will supply ride-hailing services through partnerships with companies like Uber. The technology has broader applications, but Rivian is primarily interested in leveraging it to enhance its autonomous driving capabilities.

Rivian's acquisition of Third Dimension comes after the startup secured $7 million in seed funding from venture capital firms such as Abstract Ventures and Soma Capital. Founded by Tolga Kart and Piotr Sokólski in 2024, Third Dimension initially developed its technology with an eye on speeding up video game development.

However, the company's founders saw potential for their AI to be used in other areas, including defense and autonomous vehicles. Under Rivian, they will now focus exclusively on developing automated driving capabilities, a problem that Kart believes has significant scale and impact.

The 15-person team at Third Dimension will join Rivian's autonomy and AI team led by James Philbin, with the acquisition also providing an opportunity for Rivian to expand its presence in London.

The acquisition of Third Dimension by Rivian marks a significant step towards bridging the gap between simulated and real-world driving environments for autonomous vehicles.

Historically, simulators have been built on rendering or video game engines, relying heavily on synthetic data to create virtual environments that mimic reality. However, these simulations often fall short in accurately replicating the complexities of the physical world, leaving a quality gap that can be challenging to overcome.

The workaround has typically involved feeding simulators with increasingly large amounts of data in an attempt to close this gap. However, this approach is not only resource-intensive but also limited in its ability to truly replicate real-world driving conditions.

Third Dimension's technology uses AI to match the physical world, and when combined with Rivian's vast collection of driving data, it has the potential to create a highly accurate simulator that can accurately model complex driving scenarios.

Rivian's existing fleet of vehicles, including pickup trucks, SUVs, and delivery vans, generates a significant amount of data through external camera sharing. This aggregated and anonymized data is then used to build training models for driving, with over 400,000 sequences uploaded per day from Rivian's customer fleets.

Rivian has acquired a world model startup to accelerate its self-driving ambitions. The acquisition will enable Rivian to leverage advanced machine learning capabilities and tap into vast amounts of real-world driving data.

The startup's technology is designed to process and analyze massive datasets from various sources, including Rivian's own customer fleets. This aggregated and anonymized data is then used to build training models for driving, with over 400,000 sequences uploaded per day. By integrating this technology into its operations, Rivian aims to improve the accuracy and reliability of its autonomous vehicles.

The acquisition marks a significant step forward in Rivian's mission to develop safe and efficient self-driving technologies. With this advanced capability, Rivian is poised to accelerate its progress in the autonomous vehicle space.

TechCrunch: https://techcrunch.com/2026/10/22/rivian-buys-world-model-startup-to-accelerate-self-driving-ambitions/

According to Scaringe, these third-party AI agents will enable users to access a wider range of capabilities, taking the car's functionality to new heights. He described this integration as "magical, suggesting that it will significantly enhance the user experience.

Rivian has been developing its own in-car software from scratch, unlike some other manufacturers that rely on Apple CarPlay or Android Auto. This approach has allowed the company to build a range of proprietary applications, including navigation systems and popular in-car apps like Apple Music.

The company's AI assistant already understands voice commands and can perform tasks such as adjusting temperature settings, activating seat warmers, or summarizing news updates. However, with external AI agents on board, users may be able to access additional features and services.

Rivian has not provided a specific timeline for the integration of third-party AI agents but is hosting an AI & Autonomy Day event in December, which will likely shed more light on its plans.

Rivian's AI system is designed to be flexible and adaptable, allowing it to choose from various models depending on the complexity of the task at hand. If a question requires a straightforward answer, the local model running on the vehicle can provide the response. However, if the query is more complex, the system can shift to a cloud-based model for a more accurate answer.

The AI agent has already been integrated with external apps like Google Calendar, and Rivian plans to take it a step further by incorporating products from leading AI companies into its vehicles. This integration will not be straightforward, however, requiring significant plumbing work behind the scenes to ensure seamless operation.

One of the key challenges that Rivian faces is integrating third-party software with its safety-critical systems. The company must exercise extreme caution when implementing new features, particularly those related to vehicle control. As Scaringe noted, it's essential to prevent the AI agent from taking control of critical functions like braking or steering.

To avoid this risk, Rivian is likely to implement a more nuanced approach that builds on existing user habits. For instance, users may be able to access their personal data and preferences stored in apps like Muse, which collect information about users' habits and routines. This would enable the AI agent to provide personalized recommendations and assistance without compromising vehicle safety.

The exact timeline for integrating third-party AI agents is still unclear, but Rivian's upcoming AI & Autonomy Day" event in December promises to shed more light on its plans. The company will likely provide further details about its integration strategy and how it intends to balance the benefits of AI with the need for safety and security.

Rivian's AI-powered assistant will be able to learn from drivers' habits and preferences over time, allowing it to provide more personalized recommendations and assistance.

This advanced functionality is made possible by the integration of natural language processing (NLP) technology into the car's software, enabling the assistant to understand complex voice commands and respond accordingly.

For instance, a driver could ask the Rivian assistant to recall a conversation they had on another device, such as their smartphone or tablet, and use that context to inform its response. This would allow drivers to pick up where they left off in previous conversations.

Rivian's AI-powered assistant will not be the first of its kind in an American car company, however - Tesla has already introduced a feature allowing users to interact with both SpaceX's Grok chatbot and its own Grok Bot assistant.

The integration of NLP technology into the car's software marks a significant step forward for Rivian's AI-powered assistant, and highlights the company's commitment to creating a more seamless and intuitive driving experience.

The integration of NLP technology into Rivian's car software is a significant step forward for its AI-powered assistant, highlighting the company's commitment to creating a seamless and intuitive driving experience.

Rivian has been working on enhancing its in-car AI assistant, which will now be able to understand voice commands more accurately. This improvement aims to make interactions with the vehicle more natural and user-friendly. The integration of NLP technology is expected to elevate the overall driving experience for Rivian's customers.

As part of this development, the company has also implemented a system that allows its AI agents to learn from users' behavior and adapt to their preferences. This adaptive learning capability will enable the AI assistant to provide more personalized recommendations and assistance over time.

The integration of NLP technology into Rivian's car software marks a major milestone in the development of its AI-powered driving experience, setting the stage for further innovation and improvement in this area.

TechCrunch: https://techcrunch.com/2026/10/15/ai-agents-are-coming-to-rivians-cars/

Field, who was also involved in Apple's secret car project and was employee number one at Segway, will take on the role of president at Mind Robotics, an industrial AI and robotics venture that separated from Rivian last year. This move suggests that Mind Robotics is ready to expand its operations just a year after its inception.

RJ Scaringe, Rivian's CEO, will still be involved with Mind Robotics but will leave day-to-day responsibilities to Field. These include product development, engineering, and operational management.

Mind Robotics has secured more than $1 billion in funding from prominent investors such as Accel, Andreessen Horowitz, Eclipse, Kleiner Perkins, and the venture arms of Volkswagen and Salesforce. The company is developing a comprehensive platform for industrial manufacturing that includes purpose-built robots running on foundation models designed to automate tasks at scale.

The startup's approach differs from others in the field by not attempting to replicate human biomechanics in its robot designs. Instead, it will focus on automating specific tasks within industrial and manufacturing environments.

RJ Scaringe's vision for Mind Robotics requires expertise in robotics deployment, and he sought someone with experience to help lead the company.

To find the right person, Scaringe called on Doug Field, who had recently left Ford after five years as a key figure in shaping the automaker's electric vehicle and technology strategies.

Rivian's spinoff companies continue to expand their teams and operations. Mind Robotics, a company spun out of Rivian, has made a significant hire in Doug Field, who joins as its new leader. Field brings his expertise from Ford, where he spent five years shaping the automaker's electric vehicle and technology strategies.

As chairman of Mind Robotics, Scaringe had been searching for the right person to lead the company. With Field on board, the focus will shift towards developing innovative technologies that can drive growth and success. The appointment is seen as a strategic move by Scaringe to strengthen the company's leadership and direction.

Mind Robotics operates independently but has ties to its parent company Rivian. The two companies share a common history, with Rivian having spun out Mind Robotics in addition to another startup called Also. Both spinoffs have received investments from Rivian, with the company owning minority stakes in each of them.

The partnership between Rivian and its spinoff companies is an interesting one. While they operate independently, they also benefit from shared resources and expertise. This model allows for innovation and risk-taking without being burdened by the responsibilities that come with being a standalone entity.

Rivian's involvement in Mind Robotics and Also demonstrates its commitment to supporting emerging technologies and entrepreneurs. The company is investing in various areas of mobility, including electric vehicles, micromobility, and more.

As part of its ongoing efforts to expand into various areas of mobility, Mind Robotics has announced significant investments in electric vehicles and micromobility.

The company is also exploring other innovative transportation solutions, although specific details about these initiatives have not been disclosed. With a growing focus on sustainable technologies, Mind Robotics appears to be positioning itself as a major player in the emerging mobility landscape.

Mind Robotics' investments are likely to drive innovation and growth in the industry, with far-reaching implications for consumers, businesses, and the environment.

TechCrunch: https://techcrunch.com/2026/10/13/rivian-spinoff-mind-robotics-hires-former-ford-ev-chief-doug-field/