Electric Cars

ALSO e-bikes: A delayed launch with mixed customer feedback

After extensive postponements and increasing impatience from those who placed reservations, ALSO, a subsidiary of Rivian, has finally commenced the distribution of its electric bicycles to initial customers. Early recipients of the $4,500 ALSO TM-B e-bikes have started sharing their initial thoughts and experiences on various social media platforms. The feedback, for the most part, appears encouraging, though initial range assessments offer a more realistic perspective on some of the vehicle's ambitious claims. This unique electric bicycle, stemming from Rivian's innovative approach, integrates a proprietary DreamRide system, which employs a pedal-by-wire mechanism rather than a traditional mechanical drivetrain, allowing for software-driven performance adjustments. The e-bike also features interchangeable top frames and a distinctive throttle mechanism that functions more as a temporary power boost rather than an independent accelerator. While early users express considerable satisfaction with the design and functionality, particularly the responsive acceleration, some real-world tests challenge the manufacturer's ambitious range estimates. One rider, under demanding conditions, achieved only 30 miles on a full charge, significantly less than the advertised 100 miles, highlighting a common industry trend of optimistic range projections.

Initial Customer Impressions and Innovative Features

After a prolonged period of anticipation and various postponements, ALSO, a company spun off from Rivian, has finally initiated the delivery of its electric bikes, the TM-B model, to its first wave of customers. These initial users have begun to share their experiences and evaluations of the e-bike's performance in real-world scenarios on social media platforms. The overarching sentiment from these early reviews appears to be largely favorable, indicating a positive reception for the long-awaited product. However, alongside this enthusiasm, the first evaluations of the bike's range capabilities have also provided a pragmatic assessment, offering a reality check against some of the more ambitious claims made by the manufacturer. This divergence between advertised figures and practical results is a common theme within the e-bike industry, where range estimations often represent ideal conditions rather than typical usage.

The TM-B electric bicycle stands out in the market due to its unconventional design and operational mechanisms, largely influenced by its origins within Rivian. A key innovation is the proprietary DreamRide drive system, which integrates a pedal-by-wire configuration with a robust motor. This setup means that unlike conventional bicycles, there is no direct mechanical linkage between the pedals and the rear wheel. Instead, the act of pedaling generates an electronic signal that governs the motor, allowing for fine-tuned performance adjustments primarily through software. This technological approach offers a distinct riding experience, differentiating the TM-B from many other e-bikes currently available. Furthermore, the bike features interchangeable top frames, adding a layer of customization, and an innovative interpretation of a throttle control. This "throttle" acts more as a temporary assist boost, activating only when pedaling and providing a surge of power, which users have described as highly responsive and exhilarating. This design choice sidesteps traditional independent throttle functionality, aligning with evolving regulatory landscapes and offering a unique user interface that has resonated positively with early adopters.

Real-World Range Challenges and Delivery Hurdles

One of the most compelling early reports comes from an owner who systematically evaluated the real-world operational distance of the TM-B. This rider managed to cover 30 miles (approximately 51 kilometers) before the battery capacity diminished to a mere 4%. This test was conducted under challenging circumstances, characterized by continuous high levels of pedal assistance, encounters with multiple steep inclines, and the presence of significant headwinds. These conditions collectively represent a rigorous test for any electric bicycle, likely pushing the limits of its battery efficiency. Furthermore, the bike's performance management system gradually curtails its maximum assistance as the battery level drops, beginning this power reduction once the charge falls below 40%. The owner noted a progressive decrease in assistance, starting from the highest 10x setting and gradually stepping down to only 2x assistance when the battery reached 6%, beyond which the bike felt akin to a standard pedal bicycle.

The reported range of 30 miles, derived from an almost fully charged battery, falls considerably short of the advertised 100-mile (160 km) claim. However, this discrepancy is not entirely unexpected within the e-bike sector, where range specifications are frequently optimistic. These figures typically reflect usage under minimal assistance and favorable environmental conditions, rather than scenarios where the motor is consistently operating at its maximum output. Despite the range not fully meeting the published expectations under strenuous conditions, the primary satisfaction for most customers lies in finally receiving their long-delayed e-bikes. ALSO had initially projected a much earlier delivery schedule, but these plans were repeatedly postponed due to various factors, including the need for hardware modifications related to component availability and complexities surrounding regulatory approvals for its battery and high-power USB-C charging system. Now, with the bikes reaching consumers, the focus shifts from logistical delays to how these innovative e-bikes perform in diverse, real-world applications, and whether ALSO's unique vision ultimately justifies the extensive wait for its clientele.

Figure F.02 Humanoid Robots Decommissioned in Molten Steel, 'Terminator 2' Style

In an unprecedented move, Figure, a prominent robotics firm, has chosen a dramatic and visually striking method to retire its advanced F.02 humanoid robots. Eschewing conventional disposal techniques, the company orchestrated a 'Terminator 2'-inspired decommissioning, where the robots marched autonomously into vats of molten steel. This audacious strategy was conceived to simultaneously reclaim precious raw materials and safeguard the company's sensitive proprietary technology from falling into unauthorized hands. The decision underscores a creative solution to the complex challenge of managing high-tech robotics at the end of their operational lifespan, ensuring both environmental responsibility through material recovery and intellectual property protection.

Executing this ambitious plan presented significant logistical hurdles. Initially, Figure encountered difficulties in securing a foundry willing to handle lithium-ion battery-equipped robots in their specialized equipment. After an extensive search, a facility in Imatra, Finland, ultimately agreed to undertake the task. The next phase involved sophisticated programming to enable the robots to perform the precise leap. Figure's engineers developed a new AI model, trained using motion capture data from stunt performers, to guide the robots in simulated jumps from a building at their San Jose campus. This rigorous preparation ensured that despite the extreme heat and electromagnetic interference of the foundry environment, the F.02 robots executed their final, fiery mission flawlessly, demonstrating remarkable resilience and precision.

Following the fiery decommission in Finland, the molten metal was repurposed. The reclaimed material is now being machined into a limited collection of artifacts, intended to commemorate the F.02 series and offer enthusiasts a tangible piece of Figure's history. This innovative approach not only addresses the practicalities of robot disposal but also taps into a unique merchandising opportunity, allowing the company to immortalize its pioneering robotic creations. The entire endeavor highlights Figure's blend of advanced engineering, creative problem-solving, and strategic branding, transforming an end-of-life process into a memorable event.

This remarkable act of robot decommissioning reflects a forward-thinking approach to technological evolution. By embracing such a bold and innovative method, companies can demonstrate a commitment to both advanced robotics and responsible lifecycle management. It's a powerful statement that technology, even at its conclusion, can inspire wonder and provide valuable lessons, paving the way for future advancements grounded in creativity and purpose.

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The Robotaxi's Nighttime Vision: Why Lidar is Crucial

This article explores the ongoing debate surrounding sensor technology in autonomous vehicles, specifically focusing on Tesla's camera-centric approach versus the multi-sensor strategies employed by competitors. It highlights the critical role of lidar and radar in overcoming the limitations of camera vision, particularly in challenging low-light conditions, and examines the implications for the future of self-driving technology.

Illuminating the Path: How Advanced Sensors Define the Future of Autonomous Driving

Nighttime Driving Challenges for Autonomous Vehicles

Elon Musk recently pointed out that a primary obstacle preventing Tesla's Robotaxi service from operating extensively at night is its difficulty in spotting small animals, such as "grey kittens on grey asphalt." This scenario epitomizes a common detection problem in low-light, low-contrast environments, an area where camera-based systems typically struggle. This limitation brings to the forefront the long-standing debate over the necessity of lidar and radar technologies, which Musk has previously referred to as redundant.

Extended Service Hours and Underlying Concerns

Tesla's Robotaxi service in Austin recently extended its operating hours by one hour, now closing at 11 PM instead of 10 PM. Musk's explanation for this limited extension underscored the aforementioned challenge of nocturnal pet detection. This modest expansion comes despite the service's initial launch in June 2025 with operating hours until midnight, indicating a regression in operational capability rather than advancement. The service's slow growth since its inception, even with the introduction of new vehicles, suggests fundamental challenges persist.

The Fundamental Differences in Sensor Technologies

Cameras are passive sensors that rely on ambient light reflecting off objects, making them less effective in dimly lit or low-contrast situations. In contrast, lidar systems are active sensors that emit laser pulses and measure the return time to create a detailed 3D map of the surroundings, performing consistently regardless of light conditions. Radar, another active sensor, uses radio waves to determine an object's speed and distance, offering resilience against environmental factors like fog or glare. While radar may be less precise for smaller objects, its ability to function in adverse conditions complements lidar. Companies like Waymo integrate all three sensor types, enabling their autonomous fleets to operate 24/7, a stark contrast to Tesla's vision-only approach.

Musk's Historical Stance on Lidar and Night Vision

For years, Elon Musk has been a vocal critic of lidar, labeling it a "fool's errand" and suggesting that a general solution to self-driving would primarily involve neural networks and cameras. He even claimed that integrating lidar and radar could compromise safety due to sensor conflicts. Despite his earlier assertions that Tesla's cameras provided superior night vision, recent statements contradict this, admitting that nighttime visibility is a significant unresolved issue. This shift comes amidst ongoing investigations by NHTSA into Tesla's FSD crashes in low-visibility conditions, which have highlighted the potential benefits of radar.

The Persistent Challenges of Camera-Only Systems

The issue of cameras struggling with dark, low-contrast objects at night is not new; it's a well-documented limitation that most autonomous vehicle developers address by incorporating lidar and radar. While no sensor suite is infallible, Tesla's reliance on a camera-only system appears to be a deliberate choice that introduces a heightened safety margin concern, especially when the detection of critical objects like pets or even larger obstacles on the road is compromised. The cost argument against lidar has also diminished, with reports indicating it now costs only a few hundred dollars per vehicle. This ongoing debate raises questions about Tesla's commitment to round-the-clock autonomous operation, especially as competitors like Waymo continue to expand their 24/7 services using a multi-sensor strategy.

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