Blogs

At the turn of the last century, the automobile industry was still new and evolving rapidly. In 1898, there were about 50 carmakers in the United States. A decade later, that number had increased fivefold. In 1901, the companies produced 7,000 vehicles. By 1910, production had reached 181,000.For several decades, electric cars vied with those powered by steam and internal combustion, and nobody was sure which technology would come out on top. Steam had the legacy of locomotive technology behind it but came with a risk of fire. Steam-powered vehicles could also become exceedingly hot, depending on the placement of the boiler and the steam piping. Both gasoline and electric cars faced logistical challenges: How far could you travel without refueling or charging? You could always throw an extra can of gasoline in the back of the car, but charging a battery involved more planning. The infrastructure for long-distance travel was not yet in place.Before the invention of the electric starter in 1911, gasoline-powered engines had to be started with a hand crank; once running, they were loud and emitted noxious fumes. Fully electric vehicles, by contrast, were easy to start; you just turned on the main battery switch, often with a key, and there was no foul exhaust to deal with. Electric carmakers looking for a way to differentiate their products decided that these attributes made their vehicles perfect for women. (Electric cars were also marketed to doctors so that they could make house calls in the middle of the night without waking the neighbors.) General Electric, which made car chargers based on mercury-arc rectifiers, was so captivated by the idea of women driving electric cars that the company created a series of advertisements featuring stylishly dressed women plugging in their cars and posing with their charging stations. In ads for its electric car chargers, General Electric featured women using the equipment.miSci—Museum of Innovation and ScienceA young woman named Fannie Goodnow was an early EV adopter. She owned a 1908 Bailey Victoria Phaeton, an open two-seater that really did look like a horseless carriage, and she used a GE mercury-arc rectifier to […]

This article is brought to you by Qualcomm Technologies.For many consumers, much of the promise and appeal of AI is personal. Consumers are looking past generic tools and want to know how these technologies will help them in their daily lives. These trends coincide with the advent of new classes of wearable devices that, in addition to being able to leverage powerful frontier models, feature built-in intelligence that understand the context of a user. Where are they? What are they seeing and hearing? What are their habits, their preferences, their schedules?It’s an astonishing pivot, from passive accessories that served mostly to send users smartphone notifications to proactive, intelligent companions. The smartphone is no longer the center of that universe; though it’s still incredibly important, in this personal AI paradigm, the AI is the UI. And it shifts the focus toward you, the user.These new technologies are exciting. But what do consumers really want?A Personal AI report, commissioned by Qualcomm Technologies, built on a survey of more than 12,000 people across key geographies worldwide (the U.S., U.K., Germany, India, Brazil, and China) focused on the rise of personal AI in intelligent wearables looks deeply at these developments.The smartphone is no longer the center of that universe; though it’s still incredibly important, in this personal AI paradigm, the AI is the UI.Survey respondents are less interested in single devices and are responding more to the idea of connected ecosystems. As people expand their roster of devices, it only makes sense. Instead of relying entirely on a smartphone and a laptop, respondents also have connected technology in their cars, as well as intelligent wearables like smartwatches, smart glasses, hearables, and other wearables like rings, pins, and pendants. They want those devices to work in concert, and the way to do that is to decentralize any single one of them. Instead, the AI agent that knows the user and works across all of those devices becomes the unifying factor.Consider a typical workday: A user’s watch detects it is time to leave for a meeting and, with permission, their AI agent factors in calendar […]

Modern engineering projects increasingly combine human judgment with machine capability. An engineer can define a problem, then ask an artificial intelligence tool to search relevant research and technical standards, generate design options, test them in simulation, and compare the results. The engineer can then bring the results to specialists who understand the parts AI cannot judge on its own, such as whether a design can be built safely, whether it makes sense in a particular setting, or how it might affect its users. The final decision about whether and how to move forward remains a human responsibility.AI can help engineers do early project steps that once required several people with different technical skills. The engineer’s role is therefore expanding from performing each technical step to deciding how people, machines, and specialists’ knowledge should work together on the project.The problem, not the titleEngineering has always been divided into disciplines, and for good reasons. Electrical, mechanical, civil, software, and other engineering fields require deep knowledge that takes years to develop. AI does not replace that need. It simply changes how easily engineers can explore the parts of a problem that sit outside their own specialty.Consider a software engineer working on a medical device. AI can help the engineer review relevant biomedical research, understand unfamiliar terms, analyze data, and build an early model.That does not make the engineer a physician or biomedical expert. It allows the engineer to ask better questions before working with the experts.The same is true in energy, transportation, manufacturing, and many other fields. A problem might begin as a software issue and then quickly involve hardware, safety measures, economics, human behavior, and regulations.Engineers do not need to master every field; they need to recognize which expertise the problem requires and bring the right people and tools together.The importance of systems thinkingSystems thinking thus becomes especially important. It requires looking at the whole problem: understanding how its parts affect one another, identifying constraints and failure points, […]

In the cockpit of Beta Technologies’ Alia CX300, pilot Chris Caputo steers onto Runway 33 at Patrick Leahy Burlington International Airport in Vermont. Cleared for takeoff, he releases the brakes and nudges the throttle forward.At the back of the aircraft, the five-blade pusher propeller snaps awake, and the Alia bolts forward. There’s no shriek of a turbofan spooling up, no shudder of a piston engine, and no wait for thrust. Just the low hum of an electric motor and a shove of instant acceleration.Within a few seconds, we’re at 85 knots (almost 160 kilometers per hour), and Caputo rotates the nose upward. The runway drops abruptly away as we climb. Gaining speed and altitude, we head northwest over Lake Champlain. Through the wraparound canopy, I watch the hunched shoulders of Vermont’s Green Mountains shrink under the right wing, with New York’s taller Adirondacks to the left.Caputo, a former Air Force fighter pilot, flicks the control stick hard left, then right. Despite its 15-meter wingspan, the Alia feels snappy, its fly-by-wire system automatically coordinating aileron and rudder inputs. The machine, he says, is much simpler to manage than the Cessna 182 I flew around Australia in my student-pilot days.What’s more, our half-hour flight in the Alia will consume only about US $9 worth of electricity. The same flight in a comparable Cessna 208 Caravan would burn roughly 25 to 30 gallons of Jet A fuel, costing about $210 to $255 at press time. “Even at full throttle, we’re not burning any fuel up here,” says Caputo, as he takes the Alia into a sweeping left turn and heads south over the lake. “We’re not polluting the environment. [There’s] no noise pollution.” At Beta’s South Burlington, Vt., facility, workers assemble the body of an Alia A250. The company says it has an order and option-to-buy backlog of nearly 1,000 aircraft.Beta TechnologiesThis ride is happening during an unusually lively time for electric aviation. The promise of lower operating costs and cleaner flight has pushed electric aircraft from a fringe experiment to one of the aviation industry’s most closely watched frontiers. After years of renderings, […]

This article is brought to you by VicOne.A mobile robot slows for someone in a hallway. A collaborative arm eases its movement as a worker approaches. A humanoid pauses to let a person pass. Each response depends on information about the robot or its surroundings: a distance reading, a position estimate, or a stop signal.But what happens when one of those inputs is wrong, and the robot still responds exactly as designed? The mobile robot reads the hallway as clear while someone is still there. The arm estimates that the worker is farther away. The humanoid does not receive a stop signal as a person crosses its path.In each case, a fault could cause that mismatch. So could deliberate manipulation.At VicOne LAB R7, we examine how manipulated inputs can change robot behavior — and what that means for the systems meant to keep people safe.How an untrusted input can change a robot’s behaviorA robot does more than measure its surroundings. It may interpret what it sees and hears to decide what to do next. Information placed in its environment can therefore influence its actions.Published research shows how this can happen. In a study of vision-language-action (VLA) models, a patch in a camera’s view reduced task success in simulated robot tests. FreezeVLA found that an adversarial image could cause tested models to ignore later instructions. Although the studies used different methods, both demonstrate how visual input can interfere with a robot’s intended task.In a robot-dog test using Gemma 4 E4B, text on a poster was treated as an instruction and changed the robot’s movement.VicOne LAB R7 also tested how untrusted inputs could change robot behavior. In a robot-dog test using Gemma 4 E4B, text on a poster was treated as an instruction and changed the robot’s movement. In a separate hospital-service-robot simulation using Nemotron on NVIDIA Jetson AGX Orin, crafted audio that is inaudible to people changed the robot’s simulated behavior. The assigned tasks did not change; the inputs did. In a VicOne LAB R7 test, text on a poster changed a robot dog’s movement, illustrating how a crafted input can turn an unlikely outcome into a repeatable […]