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Lucid Motors strikes SPAC deal to go public with $24 billion valuation

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Lucid Motors reached an agreement to become a publicly traded company through a merger with special-purpose acquisition company Churchill Capital IV Corp, in the largest deal yet between a blank-check company and electric vehicle startup. 

The combined company, in which Saudi Arabia’s sovereign fund will continue to be the largest shareholder, will have a transaction equity value of $11.75 billion. Private investment in the public equity deal is priced at $15 a share, putting the implied the pro-forma equity value at $24 billion. The announcement comes more than a week after Bloomberg, citing unnamed sources, reported a deal was close to being finalized.

Lucid follows a string of other, albeit smaller valued, SPAC mergers with electric vehicle startups that have been announced this year, including Arrival, Canoo, Fisker and Lordstown Motors. Several EV infrastructure companies including EVgo and ChargePoint have also become public companies via SPAC mergers.

Lucid might have been the most anticipated. The hype and speculation that has been rampant for weeks drove up the stock price of Churchill Capital IV Corp from its opening price of $10 a share more than 470% since January 2021. The skyrocketing share price, plummeted more than 30% after the details of the deal were announced.

The private investment and cash from Churchill will provide roughly $4.4 billion in total funding to Lucid. That capital will be put to work to speed up and expand Lucid’s plans. The company plans to begin production and deliveries of the Lucid Air in North America in the second half of this year. The Air will come to Europe in 2022, followed by China in 2023. The Gravity performance luxury SUV is expected to come to market in North America in 2023. The vehicles will be produced at its new factory in Casa Grande, Arizona. 

The funding will be used to bring those two vehicles to market as well as to expand its factory in Arizona, Lucid CEO and CTO Peter Rawlinson said Monday. The company plans to expand the factory over another three phases in the coming years to have the capacity to produce 365,000 units per year at scale. The initial phase of the $700 million factory was completed late last year and will have the capacity to produce 30,000 vehicles a year.

Lucid Motors air EV

Image Credits: Lucid Motors

The deal will also help Lucid realize its vision to supply electric vehicle technologies to third parties such as other automotive manufacturers as well as offer energy storage solutions in the residential, commercial and utility segments, Rawlinson said.

Scaling an electric vehicle company is not cheap or easy. Lucid narrowly missed imploding several years ago as it struggled to find an investor that would provide the capital it needed to bring its ultra-luxe electric Air sedan into production. That investor ended up being Saudi Arabia’s sovereign wealth fund, which agreed in September 2018 to invest $1 billion into Lucid Motors.

Lucid began in 2007 as Atieva, a company founded by former Tesla VP and board member Bernard Tse and entrepreneur Sam Weng that focused on developing electric car battery technology. The early research, development and eventual progress in the components and overall electric architecture would lay the critical ground work for the future Lucid, which emerged at the end of 2016 with new publicly stated purpose to make electric vehicles (although the company had already been working quietly at this for a couple of years). Rawlinson, who left Tesla to join Lucid in 2013 as CTO, was one of the driving forces behind this new mission. He later took on the CEO title and responsibility as well.

While Lucid is often couched as a competitor to Tesla, Rawlinson has told TechCrunch the Air is meant to be a rival of the Mercedes S Class, the internal combustion engine flagship of the German automaker. The investor presentation released Monday echoes Rawlinson’s earlier comments, noting that “Tesla is innovative but not luxury.” Lucid describes itself as “post luxury” and in competition with “established luxury” brands Audi, BMW and Mercedes-Benz.

Lucid is taking a page out of Tesla’s playbook and outlined plans to eventually offer more affordable EVs once it scales production.

Rawlinson will remain as CEO and CTO. The deal is expected to close in the second quarter.

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Teach AIs forgetfulness could make them better at their jobs

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While modern machine learning systems act with a semblance of artificial intelligence, the truth is they don’t “understand” any of the data they work with — which in turn means they tend to store even trivial items forever. Facebook researchers have proposed structured forgetfulness as a way for AI to clear the decks a bit, improving their performance and inching that much closer to how a human mind works.

The researchers describe the problem by explaining how humans and AI agents might approach a similar problem.

Say there are ten doors of various colors. You’re asked to go through the yellow one, you do so and then a few minutes later have forgotten the colors of the other doors — because it was never important that two were red, one plaid, two walnut, etc, only that they weren’t yellow and that the one you chose was. Your brain discarded that information almost immediately.

But an AI might very well have kept the colors and locations of the other nine doors in its memory. That’s because it doesn’t understand the problem or the data intuitively — so it keeps all the information it used to make its decision.

This isn’t an issue when you’re talking about relatively small amounts of data, but machine learning algorithms, especially during training, now routinely handle millions of data points and ingest terabytes of imagery or language. And because they’re built to constantly compare new data with their accrued knowledge, failing to forget unimportant things means they’re bogged down by constant references to pointless or outdated data points.

The solution hit upon by Facebook researchers is essentially — and wouldn’t we all like to have this ability — to tell itself how long it needs to remember a piece of data when it evaluates it to begin with.

Animation showing 'memories' of an AI disappearing.

Image Credits: Facebook

“Each individual memory is associated with a predicted expiration date, and the scale of the memory depends on the task,” explained Angela Fan, a Facebook AI researcher who worked on the Expire-Span paper. “The amount of time memories are held depends on the needs of the task—it can be for a few steps or until the task is complete.”

So in the case of the doors, the colors of the non-yellow doors are plenty important until you find the yellow one. At that point it’s safe to forget the rest, though of course depending on how many other doors need to be checked, the memory could be held for various amounts of time. (A more realistic example might be forgetting faces that aren’t the one the system is looking for, once it finds it.)

Analyzing a long piece of text, the memory of certain words or phrases might matter until the end of a sentence, a paragraph, or longer — it depends on whether the agent is trying to determine who’s speaking, what chapter the sentence belongs to, or what genre the story is.

This improves performance because at the end, there’s simply less information for the model to sort through. Because the system doesn’t know whether the other doors might be important, that information is kept ready at hand, increasing the size and decreasing the speed of the model.

Fan said the models trained using Expire-Span performed better and were more efficient, taking up less memory and compute time. That’s important during training and testing, which can take up thousands of hours of processing, meaning even a small improvement is considerable, but also at the end user level, where the same task takes less power and happens faster. Suddenly performing an operation on a photo makes sense to do live rather than after the fact.

Though being able to forget does in some ways bring AI processes closer to human cognition, it’s still nowhere near the intuitive and subtle ways our minds operate. Of course, being able to pick what to remember and how long is a major advantage over those of us for whom those parameters are chosen seemingly randomly.

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What The Conflict With Israel Looks Like To 2 Palestinians

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NPR’s Steve Inskeep talks to Omar Shaban, founder of a Gaza-based think tank, and Palestinian lawyer Diana Buttu, about how this cycle of Palestinian-Israeli violence plays out in their neighborhoods.

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Echelon exposed riders’ account data, thanks to a leaky API

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Image Credits: Echelon (stock image)

Peloton wasn’t the only at-home workout giant exposing private account data. Rival exercise giant Echelon also had a leaky API that let virtually anyone access riders’ account information.

Fitness technology company Echelon, like Peloton, offers a range of workout hardware — bikes, rowers, and a treadmill — as a cheaper alternative for members to exercise at home. Its app also lets members join virtual classes without the need for workout equipment.

But Jan Masters, a security researcher at Pen Test Partners, found that Echelon’s API allowed him to access the account data — including name, city, age, sex, phone number, weight, birthday, and workout statistics and history — of any other member in a live or pre-recorded class. The API also disclosed some information about members’ workout equipment, such as its serial number.

Masters, if you recall, found a similar bug with Peloton’s API, which let him make unauthenticated requests and pull private user account data directly from Peloton’s servers without the server ever checking to make sure he (or anyone else) was allowed to request it.

Echelon’s API allows its members’ devices and apps to talk with Echelon’s servers over the internet. The API was supposed to check if the member’s device was authorized to pull user data by checking for an authorization token. But Masters said the token wasn’t needed to request data.

Masters also found another bug that allowed members to pull data on any other member because of weak access controls on the API. Masters said this bug made it easy to enumerate user account IDs and scrape account data from Echelon’s servers. Facebook, LinkedIn, Peloton and Clubhouse have all fallen victim to scraping attacks that abuse access to APIs to pull in data about users on their platforms.

Ken Munro, founder of Pen Test Partners, disclosed the vulnerabilities to Echelon on January 20 in a Twitter direct message, since the company doesn’t have a public-facing vulnerability disclosure process (which it says is now “under review”). But the researchers did not hear back during the 90 days after the report was submitted, the standard amount of time security researchers give companies to fix flaws before their details are made public.

TechCrunch asked Echelon for comment, and was told that the security flaws identified by Masters — which he wrote up in a blog post — were fixed in January.

“We hired an outside service to perform a penetration test of systems and identify vulnerabilities. We have taken appropriate actions to correct these, most of which were implemented by January 21, 2021. However, Echelon’s position is that the User ID is not PII [personally identifiable information,” said Chris Martin, Echelon’s chief information security officer, in an email.

Echelon did not name the outside security company but said while the company said it keeps detailed logs, it did not say if it had found any evidence of malicious exploitation.

But Munro disputed the company’s claim of when it fixed the vulnerabilities, and provided TechCrunch with evidence that one of the vulnerabilities was not fixed until at least mid-April, and another vulnerability could still be exploited as recently as this week.

When asked for clarity, Echelon did not address the discrepancies. “[The security flaws] have been remediated,” Martin reiterated.

Echelon also confirmed it fixed a bug that allowed users under the age of 13 to sign up. Many companies block access to children under the age of 13 to avoid complying with the Children’s Online Privacy Protection Act, or COPPA, a U.S. law that puts strict rules on what data companies can collect on children. TechCrunch was able to create an Echelon account this week with an age less than 13, despite the page saying: “Minimum age of use is 13 years old.”

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