Goto

Collaborating Authors

Transportation


Harnessing Noise In Optical Computing For AI - AI Summary

#artificialintelligence

In the near future, it's predicted that these technologies will have an even larger impact on society through activities such as driving fully autonomous vehicles, enabling complex scientific research and facilitating medical discoveries. And cloud computing data centers used by AI and machine learning applications worldwide are already devouring more electrical power per year than some small countries. A research team led by the University of Washington has developed new optical computing hardware for AI and machine learning that is faster and much more energy efficient than conventional electronics. Optical computing noise essentially comes from stray light particles, or photons, that originate from the operation of lasers within the device and background thermal radiation. Of course the optical computer didn't have a human hand for writing, so its form of "handwriting" was to generate digital images that had a style similar to the samples it had studied, but were not identical to them.


Senior Machine Learning Engineer (Matching)

#artificialintelligence

Beat is the fastest growing ride hailing app in Latin America and a part of the international FreeNow Group, the multi-service mobility joint venture backed by BMW Group and Daimler AG. One city at a time, we are on a mission to develop seamless mobility for a safe and sustainable urban life. We are proud to say we have launched Beat Tesla / Loonshot, the first and largest private all-electric vehicle service in Latin America. As an organization, we are committed to our drivers with ethical practices and a safe working environment. To our customers, we differentiate ourselves from other ride-hailing apps with our super user-friendly app and excellent customer service.


In Texas, driverless trucks are set to take over roads

#artificialintelligence

A giant 18-wheel transport truck is barreling down a multi-lane Texas highway, and there is no one behind the wheel. The futuristic idea may seem surreal, but it is being tested in this vast southern US state, which has become the epicenter of a rapidly developing self-driving vehicle industry. Before driverless trucks are allowed onto roads and highways, however, multiple tests must still be conducted to ensure they are safe. Self-driving lorries are operated using radars, laser scanners, cameras and GPS antennas that communicate with piloting software. "Each time we drive a mile or a kilometer in real life, we re-simulate a thousand more times on the computer by changing hundreds of parameters," explains Pierre-François Le Faou, trucking partner development manager at Waymo, the self-driving unit at Google's parent company Alphabet.


Computing for Ocean Environments: Bio-Inspired Underwater Devices & Swarming Algorithms for Robotic Vehicles

#artificialintelligence

Assistant Professor Wim van Rees and his team have developed simulations of self-propelled undulatory swimmers to better understand how fish-like deformable fins could improve propulsion in underwater devices, seen here in a top-down view. MIT ocean and mechanical engineers are using advances in scientific computing to address the ocean's many challenges, and seize its opportunities. There are few environments as unforgiving as the ocean. Its unpredictable weather patterns and limitations in terms of communications have left large swaths of the ocean unexplored and shrouded in mystery. "The ocean is a fascinating environment with a number of current challenges like microplastics, algae blooms, coral bleaching, and rising temperatures," says Wim van Rees, the ABS Career Development Professor at MIT. "At the same time, the ocean holds countless opportunities -- from aquaculture to energy harvesting and exploring the many ocean creatures we haven't discovered yet."


Hitting the Books: What autonomous vehicles mean for tomorrow's workforce

Engadget

In the face of daily pandemic-induced upheavals, the notion of "business as usual" can often seem a quaint and distant notion to today's workforce. But even before we all got stuck in never-ending Zoom meetings, the logistics and transportation sectors (like much of America's economy) were already subtly shifting in the face of continuing advances in robotics, machine learning and autonomous navigation technologies. In their new book, The Work of the Future: Building Better Jobs in an Age of Intelligent Machines, an interdisciplinary team of MIT researchers (leveraging insights gleaned from MIT's multi-year Task Force on the Work of the Future) exam the disconnect between improvements in technology and the benefits derived by workers from those advancements. It's not that America is rife with "low-skill workers" as New York's new mayor seems to believe, but rather that the nation is saturated with low-wage, low-quality positions -- positions which are excluded from the ever-increasing perks and paychecks enjoyed by knowledge workers. The excerpt below examines the impact vehicular automation will have on rank and file employees, rather than the Musks of the world.


Harnessing noise in optical computing for AI

#artificialintelligence

Artificial intelligence and machine learning are currently affecting our lives in many small but impactful ways. For example, AI and machine learning applications recommend entertainment we might enjoy through streaming services such as Netflix and Spotify. In the near future, it's predicted that these technologies will have an even larger impact on society through activities such as driving fully autonomous vehicles, enabling complex scientific research and facilitating medical discoveries. But the computers used for AI and machine learning demand a lot of energy. Currently, the need for computing power related to these technologies is doubling roughly every three to four months.


StackPath

#artificialintelligence

The service requires full cookie support in order to view this website. Please enable cookies on your browser and try again.


Worldwide AI software market to reach $62 billion in 2022 -- Gartner

#artificialintelligence

The AI software forecast from Gartner is based on use cases, measuring the amount of potential business value, timing of business value and risk to project how use cases will grow. According to the global research firm and consultancy, the top five use case categories for AI software spending in 2022 will be knowledge management; virtual assistants; autonomous vehicles; digital workplace; and crowdsourced data. The AI software market encompasses applications with AI embedded in them, such as computer vision software, as well as software that is used to build AI systems. "The AI software market is picking up speed, but its long-term trajectory will depend on enterprises advancing their AI maturity," said Alys Woodward, senior research director at Gartner. "Successful AI business outcomes will depend on the careful selection of use cases. Use cases that deliver significant business value, yet can be scaled to reduce risk, are critical to demonstrate the impact of AI investment to business stakeholders."


More Chinese Automakers Collaborating On EVs, AVs

#artificialintelligence

More Chinese automakers collaborating on EVs -- The automotive industry has entered into an intense era of collaboration among carmakers, technology giants, and even software start-ups, among others. This trend comes as countries, including China, accelerate into increased usage of EVs and AVs. Numerous partnerships have sprouted up in the past year, adding density and life to this ecosystem. Among Chinese automakers themselves, a handful of significant partnerships were made to accelerate the developments of EVs and AVs within the country. In fact, China is shaping up to be the first real test of Big Tech's ambitions in the world of car making.


Computing for ocean environments

#artificialintelligence

There are few environments as unforgiving as the ocean. Its unpredictable weather patterns and limitations in terms of communications have left large swaths of the ocean unexplored and shrouded in mystery. "The ocean is a fascinating environment with a number of current challenges like microplastics, algae blooms, coral bleaching, and rising temperatures," says Wim van Rees, the ABS Career Development Professor at MIT. "At the same time, the ocean holds countless opportunities -- from aquaculture to energy harvesting and exploring the many ocean creatures we haven't discovered yet." Ocean engineers and mechanical engineers, like van Rees, are using advances in scientific computing to address the ocean's many challenges, and seize its opportunities. These researchers are developing technologies to better understand our oceans, and how both organisms and human-made vehicles can move within them, from the micro scale to the macro scale.