
Hadrian Raises $90 Million to Build Second Factory in Torrance
Samson Amore is a reporter for dot.LA. He holds a degree in journalism from Emerson College and previously covered technology and entertainment for TheWrap and reported on the SoCal startup scene for the Los Angeles Business Journal. Send tips or pitches to samsonamore@dot.la and find him on Twitter @Samsonamore.
Manufacturing startup Hadrian Automation has raised $90 million to build a second autonomous factory in Torrance, with the goal of getting the new facility up and running by this summer.
Hadrian told CNBC that its planned 100,000-square-foot factory in Torrance—not far from its first factory location in Hawthorne—will be operational by this August. The startup, which aims to automate manufacturing processes for aerospace and defense companies, also plans to grow from 40 employees currently to around 120 by the end of this year.
The $90 million round—which appears to round out the $36 million that Hadrian reported raising in January, as dot.LA reported at the time—was co-led by Silicon Valley venture firms Andreessen Horowitz and previous backer Lux Capital. Investors Lachy Groom, Caffeinated Capital, Founders Fund, Construct Capital and 137 Ventures also participated in the funding.
As part of the deal, Andreessen Horowitz partner Katherine Boyle and Lux Capital partner Brandon Reeves will join Hadrian’s board.
“Chris’s realization after talking with hundreds of machine shops and even more machinists is the hard truth we can’t ignore: financial engineering doesn’t solve the core problem of making aerospace and defense parts faster and cheaper,” Boyle said in a statement provided to dot.LA. “You need to build automation and solve a complex engineering problem in the physical world to truly shore up the aerospace and defense supply chain.”
Hadrian CEO Christopher Power did not immediately return a request for comment. He told CNBC that the company now has three aerospace customers that build rockets and satellites for which Hadrian is manufacturing aluminum components, but did not disclose the companies’ names.
Hadrian wants to create factories that can automatically manufacture parts for rockets, satellites, jets and drones at a rapid pace with limited human interference. Power told CNBC that the startup’s existing factory in Hawthorne “can produce space and defense parts 10 times faster and more efficient than anyone else.”
“We’re not setting up factories that are like manufacturing lines—we’re building an abstract factory that you can drop any part into and it comes out the other side,” Power said. “As long as it fits within a certain size or certain material that we support, we can make anything within that.” The CEO added that Hadrian soon plans to expand its manufacturing offerings into hard metals like steel.
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Samson Amore is a reporter for dot.LA. He holds a degree in journalism from Emerson College and previously covered technology and entertainment for TheWrap and reported on the SoCal startup scene for the Los Angeles Business Journal. Send tips or pitches to samsonamore@dot.la and find him on Twitter @Samsonamore.
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The Learning Perv: How I Learned to Stop Worrying and Love Lensa’s NSFW AI
It took me 48 hours to realize Lensa might have a problem.
“Is that my left arm or my boob?” I asked my boyfriend, which is not what I’d consider a GREAT question to have to ask when using photo editing software.
“Huh,” my boyfriend said. “Well, it has a nipple.”
Well then.
I had already spent an embarrassing amount of money downloading nearly 1,000 high-definition images of myself generated by AI through an app called Lensa as part of its new “Magical Avatar” feature. There are many reasons to cock an eyebrow at the results, some of which have been covered extensively in the last few days in a mounting moral panic as Lensa has shot itself to the #1 slot in the app store.
The way it works is users upload 10-20 photos of themselves from their camera roll. There are a few suggestions for best results: the pictures should show different angles, different outfits, different expressions. They shouldn’t all be from the same day. (“No photoshoots.”) Only one person in the frame, so the system doesn’t confuse you for someone else.
Lensa runs on Stable Diffusion, a deep-learning mathematical method that can generate images based on text or picture prompts, in this case taking your selfies and ‘smoothing’ them into composites that use elements from every photo. That composite can then be used to make the second generation of images, so you get hundreds of variations with no identical pictures that hit somewhere between the Uncanny Valley and one of those magic mirrors Snow White’s stepmother had. The tech has been around since 2019 and can be found on other AI image generators, of which Dall-E is the most famous example. Using its latent diffusion model and a 400 million image dataset called CLIP, Lensa can spit back 200 photos across 10 different art styles.
Though the tech has been around a few years, the rise in its use over the last several days may have you feeling caught off guard for a singularity that suddenly appears to have been bumped up to sometime before Christmas. ChatGPT made headlines this week for its ability to maybe write your term papers, but that’s the least it can do. It can program code, break down complex concepts and equations to explain to a second grader, generate fake news and prevent its dissemination.
It seems insane that when confronted with the Asminovian reality we’ve been waiting for with either excitement, dread or a mixture of both, the first thing we do is use it for selfies and homework. Yet here I was, filling up almost an entire phone’s worth of pictures of me as fairy princesses, anime characters, metallic cyborgs, Lara Croftian figures, and cosmic goddesses.
And in the span of Friday night to Sunday morning, I watched new sets reveal more and more of me. Suddenly the addition of a nipple went from a Cronenbergian anomaly to the standard, with almost every photo showing me with revealing cleavage or completely topless, even though I’d never submitted a topless photo. This was as true for the male-identified photos as the ones where I listed myself as a woman (Lensa also offers an “other” option, which I haven’t tried.)
Drew Grant
When I changed my selected gender from female to male: boom, suddenly, I got to go to space and look like Elon Musk’s Twitter profile, where he’s sort of dressed like Tony Stark. But no matter which photos I entered or how I self-identified, one thing was becoming more evident as the weekend went on: Lensa imagined me without my clothes on. And it was getting better at it.
Was it disconcerting? A little. The arm-boob fusion was more hilarious than anything else, but as someone with a larger chest, it would be weirder if the AI had missed that detail completely. But some of the images had cropped my head off entirely to focus just on my chest, which…why?
According to AI expert Sabri Sansoy, the problem isn’t with Lensa’s tech but most likely with human fallibility.
“I guarantee you a lot of that stuff is mislabeled,” said Sansoy, a robotics and machine learning consultant based out of Albuquerque, New Mexico. Sansoy has worked in AI since 2015 and claims that human error can lead to some wonky results. “Pretty much 80% of any data science project or AI project is all about labeling the data. When you’re talking in the billions (of photos), people get tired, they get bored, they mislabel things and then the machine doesn’t work correctly.”
Sansoy gave the example of a liquor client who wanted software that could automatically identify their brand in a photo; to train the program to do the task, the consultant had first to hire human production assistants to comb through images of bars and draw boxes around all the bottles of whiskey. But eventually, the mind-numbing work led to mistakes as the assistants got tired or distracted, resulting in the AI learning from bad data and mislabeled images. When the program confuses a cat for a bottle of whiskey, it’s not because it was broken. It’s because someone accidentally circled a cat.
So maybe someone forgot to circle the nudes when programming Stable Diffusion’s neural net used by Lensa. That’s a very generous interpretation that would explain a baseline amount of cleavage shots. But it doesn’t explain what I and many others were witnessing, which was an evolution from cute profile pics to Brassier thumbnails.
When I reached out for comment via email, a Lensa spokesperson responded not by directing us to a PR statement but actually took the time to address each point I’d raised. “It would not be entirely accurate to state that this matter is exclusive to female users,” said the Lensa spokesperson, “or that it is on the rise. Sporadic sexualization is observed across all gender categories, although in different ways. Please see attached examples.” Unfortunately, they were not for external use, but I can tell you they were of shirtless men who all had rippling six packs, hubba hubba.
“The stable Diffusion Model was trained on unfiltered Internet content, so it reflects the biases humans incorporate into the images they produce,” continued the response. Creators acknowledge the possibility of societal biases. So do we.” It reiterated the company was working on updating its NSFW filters.
As for my insight about any gender-specific styles, the spokesperson added: “The end results across all gender categories are generated in line with the same artistic principles. The following styles can be applied to all groups, regardless of their identity: Anime and Stylish.”
I found myself wondering if Lensa was also relying on AI to handle their PR, before surprising myself by not caring all that much. If I couldn’t tell, did it even matter? This is either a testament to how quickly our brains adapt and become numb to even the most incredible of circumstances; or the sorry state of hack-flack relationships, where the gold standard of communication is a streamlined transfer of information without things getting too personal.
As for the case of the strange AI-generated girlfriend? “Occasionally, users may encounter blurry silhouettes of figures in their generated images. These are just distorted versions of themselves that were ‘misread’ by the AI and included in the imagery in an awkward way.”
So: gender is a social construct that exists on the Internet; if you don’t like what you see, you can blame society. It’s Frankenstein’s monster, and we’ve created it after our own image.
Or, as the language processing AI model ChatGPT might put it: “Why do AI-generated images always seem so grotesque and unsettling? It's because we humans are monsters and our data reflects that. It's no wonder the AI produces such ghastly images - it's just a reflection of our own monstrous selves.”
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Drew Grant is dot.LA's Senior Editor. She's a media veteran with over 15-plus years covering entertainment and local journalism. During her tenure at The New York Observer, she founded one of their most popular verticals, tvDownload, and transitioned from generalist to Senior Editor of Entertainment and Culture, overseeing a freelance contributor network and ushering in the paper's redesign. More recently, she was Senior Editor of Special Projects at Collider, a writer for RottenTomatoes streaming series on Peacock and a consulting editor at RealClearLife, Ranker and GritDaily. You can find her across all social media platforms as @Videodrew and send tips to drew@dot.la.
PG&E Is Seeking EV Owners for Its New Program to Sell Energy Back to the Grid
Pacific Gas and Electric is in the midst of enrolling customers into an ambitious new pilot program that seeks to use electric car vehicles as a means of powering daily life and stabilizing the grid.
The “Vehicle to Everything” pilot envisions a future in which automobiles not only draw their power from the electrical grid but can also strategically add electricity back in when demand is high — and generate some money for their owners along the way.
The concept of bidirectional energy flow using EV batteries isn’t new, and dot.LA has covered various vehicle-to-grid endeavors in the past. But having a utility company as large as PG&E onboard could begin to transform the idea into a reality.
Though the program’s website has been live for a few weeks, PG&E officially began to invite customers to pre-enroll starting on December 6th. The pilot has space for 1,000 residential customers and 200 commercial customers. PG&E isn’t releasing the numbers for how many people have signed up so far, but Paul Doherty, a communications architect at the company, says he expects the enrollment period to take several months, stretching into Q1 2023.
On the residential side, customers can receive financial incentives up to $2,500 just for enrolling in the pilot. That money, says Doherty, goes towards the cost of installing a bidirectional charger at the customer’s residence. The cost of installation varies according to the specifications of the residence, but Doherty says it’s unlikely that $2,500 will cover the full cost for most users, though it may come close, with most installations ranging in the low thousands.
But there’s more money to be had as well. Once the bidirectional charger is installed, customers can not only use the electricity to power their homes but also begin selling electricity back to the grid during flex alerts. Southern California residents may remember back in September when the electric grid was pushed to its breaking point thanks to an historic heatwave. During such events–or any other disaster that strains the system–customers can plug their vehicle in, discharge the battery and get paid.
Doherty says that users can expect to make between $10 and $50 per flex alert depending on how severe the event is and how much of their battery they’re willing to discharge. That might not seem like a huge sum, but the pilot program is slated to last two years. Meaning that if California averages 10 flex alerts per year like in 2022, customers could make $1,000. That could be enough to offset the rest of the bidirectional charger installation or provide another income stream. Not to mention, help stabilize our beleaguered grid.
There is one gigantic catch, however. PG&E has to test and validate any bi-directional charger before it can be added into the program. So far, the only approved hardware is Ford’s Charge Station Pro, meaning only one vehicle–the F-150 Lightning–can participate in the program. That should change soon as the utility company tests additional hardware from other brands. Doherty says they’re expecting to add the Nissan LEAF, Hyundai’s IONIQ 5, the KIA EV6 and others soon since it’s just a matter of testing and integrating those chargers into the program.
One name notably absent from that list is Tesla. So far, the country’s largest EV presence hasn’t announced concrete plans for bidirectional charging, meaning there’s no way for Tesla owners to participate in the pilot.
“We hope they come to the table as soon as possible,” says Doherty. “That would be a game changer.”
The commercial side of the pilot looks similar to the residential. Businesses receive cash incentives upfront to help offset the cost of installing bidirectional charger and then get paid for their contribution to stabilizing the grid in times of duress. PG&E says electric school bus fleets, especially, represent attractive targets for this technology due to their large battery capacity, high peak power needs, and predictable schedule–a strategy that mirrors what V2G pioneer Nuvve described to dot.LA back in October.
If California’s plan to transition all new car sales to electric by 2035 actually succeeds — which would require it to add nearly two million new EVs to state roads every year — that’s two million rolling, high power batteries with the potential to power our homes, our jobs and the grid at large. Getting there will be a colossal undertaking, but PG&E’s pilot should be a litmus test of sorts, assuming they can figure out how to get more vehicles than the Ford Lightning into the program.
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David Shultz reports on clean technology and electric vehicles, among other industries, for dot.LA. His writing has appeared in The Atlantic, Outside, Nautilus and many other publications.