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Test Drive: Can the 2021 Polestar 2 electric sedan outshine Tesla?

FOX News

The Polestar 2 is the first all-electric car from Polestar, a new brand owned by Volvo. Fox News Autos Gary Gastelu takes it for a spin. Well, let's go ahead and add one more, anyway. It's called Polestar and it's a little different than the rest because it's a standalone subsidiary of Volvo, so comes to the table with some experience. The name originally belonged to a Swedish outfit called Polestar Racing that built competition Volvos and modified the company's sedate street cars into high performance machines.


Tesla CEO Elon Musk's next big bet rides on better batteries

The Japan Times

SAN RAMON, California – Tesla is working on new battery technology that CEO Elon Musk says will enable the company within the next three years to make sleeker, more affordable cars that can travel dramatically longer distances on a single charge. But the battery breakthroughs that Musk unveiled Tuesday at a highly anticipated event didn't impress investors. They were hoping Tesla's technology would mark an even bigger leap forward and propel the company's soaring stock to even greater heights. Tesla's shares shed more than 6 percent in extended trading after Musk's presentation. That deepened a downturn that began during Tuesday's regular trading session as investors began to brace for a potential letdown.


Discrete Word Embedding for Logical Natural Language Understanding

arXiv.org Artificial Intelligence

In this paper, we propose an unsupervised neural model for learning a discrete embedding of words. While being discrete, our embedding supports vector arithmetic operations similar to continuous embeddings by interpreting each word as a set of propositional statements describing a rule. The formulation of our vector arithmetic closely reflects the logical structure originating from the symbolic sequential decision making formalism (classical/STRIPS planning). Contrary to the conventional wisdom that discrete representation cannot perform well due to the lack of ability to capture the uncertainty, our representation is competitive against the continuous representations in several downstream tasks. We demonstrate that our embedding is directly compatible with the symbolic, classical planning solvers by performing a "paraphrasing" task. Due to the discrete/logical decision making in classical algorithms with deterministic (non-probabilistic) completeness, and also because it does not require additional training on the paraphrasing dataset, our system can negatively answer a paraphrasing query (inexistence of solutions), and can answer that only some approximate solutions exist -- A feature that is missing in the recent, huge, purely neural language models such as GPT-3.


Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach

arXiv.org Artificial Intelligence

The broader ambition of this article is to popularize an approach for the fair distribution of the quantity of a system's output to its subsystems, while allowing for underlying complex subsystem level interactions. Particularly, we present a data-driven approach to vehicle price modeling and its component price estimation by leveraging a combination of concepts from machine learning and game theory. We show an alternative to common teardown methodologies and surveying approaches for component and vehicle price estimation at the manufacturer's suggested retail price (MSRP) level that has the advantage of bypassing the uncertainties involved in 1) the gathering of teardown data, 2) the need to perform expensive and biased surveying, and 3) the need to perform retail price equivalent (RPE) or indirect cost multiplier (ICM) adjustments to mark up direct manufacturing costs to MSRP. This novel exercise not only provides accurate pricing of the technologies at the customer level, but also shows the, a priori known, large gaps in pricing strategies between manufacturers, vehicle sizes, classes, market segments, and other factors. There is also clear synergism or interaction between the price of certain technologies and other specifications present in the same vehicle. Those (unsurprising) results are indication that old methods of manufacturer-level component costing, aggregation, and the application of a flat and rigid RPE or ICM adjustment factor should be carefully examined. The findings are based on an extensive database, developed by Argonne National Laboratory, that includes more than 64,000 vehicles covering MY1990 to MY2020 over hundreds of vehicle specs.


Alphabet's Next Billion-Dollar Business: 10 Industries To Watch - CB Insights Research

#artificialintelligence

Alphabet is using its dominance in the search and advertising spaces -- and its massive size -- to find its next billion-dollar business. From healthcare to smart cities to banking, here are 10 industries the tech giant is targeting. With growing threats from its big tech peers Microsoft, Apple, and Amazon, Alphabet's drive to disrupt has become more urgent than ever before. The conglomerate is leveraging the power of its first moats -- search and advertising -- and its massive scale to find its next billion-dollar businesses. To protect its current profits and grow more broadly, Alphabet is edging its way into industries adjacent to the ones where it has already found success and entering new spaces entirely to find opportunities for disruption. Evidence of Alphabet's efforts is showing up in several major industries. For example, the company is using artificial intelligence to understand the causes of diseases like diabetes and cancer and how to treat them. Those learnings feed into community health projects that serve the public, and also help Alphabet's effort to build smart cities. Elsewhere, Alphabet is using its scale to build a better virtual assistant and own the consumer electronics software layer. It's also leveraging that scale to build a new kind of Google Pay-operated checking account. In this report, we examine how Alphabet and its subsidiaries are currently working to disrupt 10 major industries -- from electronics to healthcare to transportation to banking -- and what else might be on the horizon. Within the world of consumer electronics, Alphabet has already found dominance with one product: Android. Mobile operating system market share globally is controlled by the Linux-based OS that Google acquired in 2005 to fend off Microsoft and Windows Mobile. Today, however, Alphabet's consumer electronics strategy is being driven by its work in artificial intelligence. Google is building some of its own hardware under the Made by Google line -- including the Pixel smartphone, the Chromebook, and the Google Home -- but the company is doing more important work on hardware-agnostic software products like Google Assistant (which is even available on iOS).


The 84 biggest flops, fails, and dead dreams of the decade in tech

#artificialintelligence

The world never changes quite the way you expect. But at The Verge, we've had a front-row seat while technology has permeated every aspect of our lives over the past decade. Some of the resulting moments -- and gadgets -- arguably defined the decade and the world we live in now. But others we ate up with popcorn in hand, marveling at just how incredibly hard they flopped. This is the decade we learned that crowdfunded gadgets can be utter disasters, even if they don't outright steal your hard-earned cash. It's the decade of wearables, tablets, drones and burning batteries, and of ridiculous valuations for companies that were really good at hiding how little they actually had to offer. Here are 84 things that died hard, often hilariously, to bring us where we are today. Everyone was confused by Google's Nexus Q when it debuted in 2012, including The Verge -- which is probably why the bowling ball of a media streamer crashed and burned before it even came to market.


Toyota is building an actual city

#artificialintelligence

Car manufacturers are always building new prototype, y'know, cars, but this is the first time we've heard of one building its own prototype city. Toyota (obviously) is planning to build a 175-acre city at the base of Japan's Mount Fuji. Construction of'Woven City', which is being designed by the same company behind 2 World Trade Center in New York, Lego House in Denmark, and Google's Mountain View and London headquarters among others, will begin in 2021. But what exactly, we hear you cry, is the point? Toyota says Woven City will be a "living laboratory" populated by more than 2,000 people, many of whom will be scientists, engineers and researchers who will use it to "test and develop technologies such as autonomy, robotics, personal mobility, smart homes and artificial intelligence in a real-world environment".


Toyota to build 'city of the future' at the base of Mount Fuji

The Japan Times

LAS VEGAS – Toyota Motor Corp. said Monday it plans to build a prototype "city of the future" at the base of Mount Fuji, powered by hydrogen fuel cells and functioning as a laboratory for autonomous cars, smart homes, artificial intelligence and other technologies. Toyota unveiled the plan at CES, the big technology industry show. The development, to be built at the site of a factory that is planned to be closed in Shizuoka Prefecture, will be called "Woven City" -- a reference to Toyota's start as a loom manufacturing company -- and will serve as a home to full-time residents and researchers. Toyota did not disclose costs for the project. Executives at many major automakers have talked about how cities of the future could be designed to cut climate-changing emissions from vehicles and buildings, reduce congestion and apply internet technology to everyday life.


Driving toward a healthier planet

#artificialintelligence

With 100 million Toyota vehicles on the planet emitting greenhouse gases at a rate roughly comparable to those of France, the Toyota Motor Corporation has set a goal of reducing all tailpipe emissions by 90 percent by 2050, according to Brian Storey, who directs the Toyota Research Institute (TRI) Accelerated Materials Design and Discovery program from its Kendall Square office in Cambridge, Massachusetts. He gave the keynote address at the MIT Materials Research Laboratory's Materials Day Symposium on Oct. 9. "A rapid shift from the traditional vehicle to electric vehicles has started," Storey says. "And we want to enable that to happen at a faster pace." "Our role at TRI is to develop tools for accelerating the development of emissions-free vehicles," Storey said. He added that machine learning is helping to speed up those innovations, but the challenges are very great, so his team has to be a little humble about what it can actually accomplish.


The End of an Era: Will Tesla and Google Kill the German Car?

Der Spiegel International

History will be written on Nov. 4 at the VW plant in Zwickau, Germany. Anyone lucky enough to recently visit the factory, which is sealed behind blue rolling doors, entered into a secret world, a hidden industrial laboratory to which only a few Volkswagen employees have access. In its "ghost run," or test operation, orange-colored robots run by highly complex programs and aided by humans and machines assembled eight electric model-ID.3 Serial production is now set to begin on Nov. 4. Depending on how you see it, this marks either the beginning or the end of an era. In the future, 1,500 electric Volkswagen cars are to roll off the assembly line at the plant in the eastern state of Saxony every day, a total of 330,000 vehicles every year, in what the company describes as the "largest and most efficient electric car factory in Europe." The designers of the new compact, C-class ID.3 want to make it a 21st century icon, just as the VW Beetle and VW Golf were in their heydays. That's advertising language, of course, but even from a neutral perspective, it is difficult to overestimate the significance of what is happening: In Zwickau, Volkswagen is ringing the death knell for the combustion engine.