Harley-Davidson’s LiveWire Del Mar is its most affordable electric motorcycle yet

After months of teasing, Harley-Davidson’s LiveWire brand has unveiled its second all-electric motorcycle, the new middleweight Del Mar. Built on the brand’s new Arrow platform, it features a 60 kW motor capable of accelerating the EV from zero to 60 miles per hour in under four seconds, Electrek reported on Tuesday.

The Del Mar’s 21700-format battery is housed in a structural case that doubles as part of the motorcycle’s frame, reducing the overall weight of the vehicle. To make the Del Mar even lighter, LiveWire integrated a handful of components, including the onboard charger, into a single unit mounted to the outside of the structural battery case. All told, it’s about 25 percent lighter than the LiveWire One.

LiveWire expects the Del Mar will be able to travel approximately 100 miles on a single charge. Additionally, the EV will feature built-in GPS and cellular connectivity, which will allow the company to roll out new software features to the motorcycle and tune its performance through OTA updates. One feature you won’t find on the Del Mar is DC fast charging. It’s limited to Level 1 and 2 charging.

Following Tuesday’s reveal, LiveWire made 100 $17,699 “Launch Edition” Del Mar motorcycles available for pre-order. Those sold out almost instantly. As for the production model, which should go on sale sometime in the spring of 2023, LiveWire said it’s targeting a price of $15,000. For context, the LiveWire One, currently the brand’s most affordable electric motorcycle, starts at $22,799 before federal subsidies. LiveWire also teased that it’s already developing a third model based on the Arrow platform.

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ICE 'now operates as a domestic surveillance agency,' think tank says

Although it’s supposed to be restricted by surveillance rules at local, state and federal levels, Immigration and Customs Enforcement (ICE) has built up a mass surveillance system that includes details on almost all US residents, according to a report from a major think tank. Researchers from Georgetown Law’s Center on Privacy and Technology said ICE “now operates as a domestic surveillance agency” and that it was able to bypass regulations in part by purchasing databases from private companies. 

“Since its founding in 2003, ICE has not only been building its own capacity to use surveillance to carry out deportations but has also played a key role in the federal government’s larger push to amass as much information as possible about all of our lives,” the report’s authors state. “By reaching into the digital records of state and local governments and buying databases with billions of data points from private companies, ICE has created a surveillance infrastructure that enables it to pull detailed dossiers on nearly anyone, seemingly at any time.”

The researchers spent two years looking into ICE to put together the extensive report, which is called “American Dragnet: Data-Driven Deportation in the 21st Century.” They obtained information by filing hundreds of freedom of information requests and scouring more than 100,000 contracts and procurement records.

The agency is said to be using data from the Department of Motor Vehicles and utility companies, along with the likes of call records, child welfare records, phone location data, healthcare records and social media posts. ICE is now said to hold driver’s license data for 74 percent of adults and can track the movement of cars in cities that are home to 70 percent of the adult population in the US.

The study shows that ICE, which falls under the Department of Homeland Security, has already used facial recognition technology to search through driver’s license photos of a third of adults in the US. In 2020, the agency signed a deal with Clearview AI to use that company’s controversial technology. In addition, the report states that when 74 percent of adults hook up gas, electricity, phone or internet utilities in a new residence, ICE was able to automatically find out their updated address.

The authors wrote that ICE is able to carry out these actions in secret and without warrants. Along with the data it acquired from other government departments, utilities, private companies and third-party data brokers, “the power of algorithmic tools for sorting, matching, searching and analysis has dramatically expanded the scope and regularity of ICE surveillance,” the report states.

Spending transactions reviewed by the researchers showed that, between 2008 and last year, ICE spent around $2.8 billion on “new surveillance, data collection and data-sharing initiatives.” It spent approximately $569 million on data analysis, including $186.6 million in contracts with Palantir Technologies to help it make sense of its vast troves of data. Records showed that ICE also spent more than $1.3 billion on geolocation tech during that timeframe and $389 million on telecom interception, which includes tech that helps the agency track someone’s phone calls, emails, social media activity and real-time internet use.

In addition, the findings suggest the agency started engaging in certain surveillance activities much earlier than previously believed. The researchers found a contract from 2008 that granted ICE access to the Rhode Island motor vehicle department’s facial recognition database. Prior to that, it was understood that ICE started conducting facial recognition searches on state and local data sets in 2013.

The authors claim that ICE has been able to sidestep congressional oversight and bypass attempts at state level to curtain its surveillance capabilities. They included a list of recommendations that may help rein in the agency’s surveillance dragnet, such as Congress reforming immigration laws to “undercut ICE surveillance authority” and blocking ICE’s use of DMV data. The recommended measures also include protecting people who trust federal, state and local authorities with their data and blocking the use of utility records for immigration enforcement.

Engadget has contacted ICE and the Department of Homeland Security for comment.

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Qualcomm Modem’s Embedded AI Boosts Performance

At the Qualcomm 5G Summit, Qualcomm has revealed the extensive impact of artificial intelligence (AI) on the performance of its latest Snapdragon X70 modem.

The modem was announced earlier this year, and the built-in AI computing unit wasn’t a secret, but its effectiveness was unknown until now.

Qualcomm claims its built-in AI extends the effective range of mmWave by 20% and boosts the throughput by 28% to 73% at the edge of the cell coverage (depending on conditions).

These numbers are a rather extraordinary example of how AI can increase outcomes for all kinds of “signal” problems. We’ve already seen AI-based technology applied to ray-tracing denoising or other forms of image processing with great success.

The same can be done with radio signal processing, where the modem can learn how to interpret real-world radio signals in various challenging conditions. For example, a tree might interfere, or perhaps the radio wave bounced on a wall or passed through a material. AI helps the modem figure out what was the original signal.

Qualcomm also says that its modem is smart enough to infer what the signal should look like in the near future. That could enable better connectivity for moving vehicles, for example.

Although both 4G and 5G will benefit from these improvements, it looks like 5G mmWave (the fastest 5G) is the one that should help the most as it’s the trickiest form of 5G in terms of coverage. mmWave ideally requires a line of sight to the base station, and its signal can quickly degrade if it collides with anything along the way.

AI’s added performance is even more relevant for “standalone mmWave” (without 4G or 5G Sub-6 support). Standalone mmWave could be crucial to connect homes to a nearby Fiber network at a very high speed without deploying cables or digging trenches.

In conclusion, this is very exciting, and we can expect Qualcomm to fine-tune its AI neural networks as more data becomes available and modems can fit ever-larger networks.

Qualcomm Modem’s Embedded AI Boosts Performance

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