OpenAI releases Point-E, an AI that generates 3D models
The next breakthrough to take the AI world by storm might be 3D model generators. This week, OpenAI open-sourced Point-E, a machine learning system that creates a 3D object given a text prompt. According to a paper published alongside the code base, Point-E can produce 3D models in 1 to 2 minutes on a single Nvidia V100 GPU.
Point-E doesn’t create 3D objects in the traditional sense. Rather, it generates point clouds, or discrete sets of data points in space that represent a 3D shape — hency the cheeky abbreviation. (The “E” in Point-E is short for “efficiency,” because it’s ostensibly faster than previous 3D object generation approaches.) Point clouds are easier to synthesize from a computational standpoint, but they don’t capture an object’s fine-grained shape or texture — a key limitation of Point-E currently.
To get around this limitation, the Point-E team trained an additional AI system to convert Point-E’s point clouds to meshes. (Meshes — the collections of vertices, edges and faces that define an object — are commonly used in 3D modeling and design.) But they note in the paper that the model can sometimes miss certain parts of objects, resulting in blocky or distorted shapes.
Outside of the mesh-generating model, which stands alone, Point-E consists of two models: a text-to-image model and an image-to-3D model. The text-to-image model, similar to generative art systems like DALL-E 2 and Stable Diffusion, was trained on labeled images to understand the associations between words and visual concepts. The image-to-3D model, on the other hand, was fed a set of images paired with 3D objects so that it learned to effectively translate between the two.
When given a text prompt — for example, “a 3D printable gear, a single gear 3 inches in diameter and half inch thick” — Point-E’s text-to-image model generates an synthetic rendered object that’s fed to the image-to-3D model, which then generates a point cloud.
After training the models on a data set of “several million” 3D objects and associated metadata, Point-E could produce colored point clouds that frequently matched text prompts, the OpenAI researchers say. It’s not perfect — Point-E’s image-to-3D model sometimes fails to understand the image from the text-to-image model, resulting in a shape that doesn’t match the text prompt. Still, it’s orders of magnitude faster than the previous state-of-the-art — at least according to the OpenAI team.
“While our method performs worse on this evaluation than state-of-the-art techniques, it produces samples in a small fraction of the time,” they wrote in the paper. “This could make it more practical for certain applications, or could allow for the discovery of higher-quality 3D object.”
What are the applications, exactly? Well, the OpenAI researchers point out that Point-E’s point clouds could be used to fabricate real-world objects, for example through 3D printing. With the additional mesh-converting model, the system could — once it’s a little more polished — also find its way into game and animation development workflows.
OpenAI might be the latest company to jump into the 3D object generator fray, but — as alluded to earlier — it certainly isn’t the first. Earlier this year, Google released DreamFusion, an expanded version of Dream Fields, a generative 3D system that the company unveiled back in 2021. Unlike Dream Fields, DreamFusion requires no prior training, meaning that it can generate 3D representations of objects without 3D data.
While all eyes are on 2D art generators at the present, model-synthesizing AI could be the next big industry disruptor. 3D models are widely used in film and TV, interior design, architecture and various science fields. Architectural firms use them to demo proposed buildings and landscapes, for example, while engineers leverage models as designs of new devices, vehicles and structures.
3D models usually take a while to craft, though — anywhere between several hours to several days. AI like Point-E could change that if the kinks are someday worked out, and make OpenAI a respectable profit doing so.
The question is what sort of intellectual property disputes might arise in time. There’s a large market for 3D models, with several online marketplaces including CGStudio and CreativeMarket allowing artists to sell content they’ve created. If Point-E catches on and its models make their way onto the marketplaces, model artists might protest, pointing to evidence that modern generative AI borrow heavily from its training data — existing 3D models, in Point-E’s case. Like DALL-E 2, Point-E doesn’t credit or cite any of the artists that might’ve influenced its generations.
But OpenAI’s leaving that issue for another day. Neither the Point-E paper nor GitHub page make any mention of copyright.
The market has changed, but super-voting shares are here to stay, says Mr. IPO
Yesterday, the ride-sharing company Lyft said its two co-founders, John Zimmer and Logan Green, are stepping down from managing the company’s day-to-day operations, though they are retaining their board seats. According to a related regulatory filing, they actually need to hang around as “service providers” to receive their original equity award agreements. (If Lyft is sold or they’re fired from the board, they’ll see “100% acceleration” of these “time-based” vesting conditions.)
As with so many founders who’ve used multi-class voting structures in recent years to cement their control, their original awards were fairly generous. When Lyft went public in 2019, its dual-class share structure provided Green and Zimmer with super-voting shares that entitled them to 20 votes per share in perpetuity, meaning not just for life but also for a period of nine to 18 months after the passing of the last living co-founder, during which time a trustee would retain control.
It all seemed a little extreme, even as such arrangements became more common in tech. Now, Jay Ritter, the University of Florida professor whose work tracking and analyzing IPOs has earned him the moniker Mr. IPO, suggests that if anything, Lyft’s trajectory might make shareholders even less nervous about dual-stock structures.
For one thing, with the possible exception of Google’s founders — who came up with an entirely new share class in 2012 to preserve their power — founders lose their stranglehold on power as they sell their shares, which then convert to a one-vote-per-one-share structure. Green, for example, still controls 20% of the shareholder voting rights at Lyft, while Zimmer now controls 12% of the company’s voting rights, he told the WSJ yesterday.
Further, says Ritter, even tech companies with dual-class shares are policed by shareholders who make it clear what they will or will not tolerate. Again, just look at Lyft, whose shares were trading at 86% below their offering price earlier today in a clear sign that investors have — at least for now — lost confidence in the outfit.
We talked with Ritter last night about why stakeholders aren’t likely to push too hard against super-voting shares, despite that now would seem the time to do it. Excerpts from that conversation, below, have been lightly edited for length and clarity.
TC: Majority voting power for founders became widespread over the last dozen years or so, as VCs and even exchanges did what they could to appear founder-friendly. According to your own research, between 2012 and last year, the percentage of tech companies going public with dual-class shares shot from 15% to 46%. Should we expect this to reverse course now that the market has tightened and money isn’t flowing so freely to founders?
JR: The bargaining power of founders versus VCs has changed in the last year, that’s true, and public market investors have never been enthusiastic about founders having super voting stock. But as long as things go well, there isn’t pressure on managers to give up super voting stock. One reason U.S. investors haven’t been overly concerned about dual-class structures is that, on average, companies with dual-class structures have delivered for shareholders. It’s only when stock prices decline that people start questioning: Should we have this?
Isn’t that what we are seeing currently?
With a general downturn, even if a company is executing according to plan, shares have fallen in many cases.
So you expect that investors and public shareholders will remain complacent about this issue despite the market.
In recent years, there haven’t been a lot of examples where entrenched management is doing things wrong. There have been cases where an activist hedge fund is saying, “We don’t think you’re pursuing the right strategy.” But one of the reasons for complacency is that there are checks and balances. It’s not the case where, as in Russia, a manager can loot the company and public shareholders can’t do anything about it. They can vote with their feet. There are also shareholder lawsuits. These can be abused, but the threat of them [keeps companies in check]. What’s also true, especially of tech companies where employees have so much equity-based compensation, is that CEOs are going to be happier when their stock goes up in price but they also know their employees will be happier when the stock is doing well.
Before WeWork’s original IPO plans famously imploded in the fall of 2019, Adam Neumann expected to have so much voting control over the company that he could pass it along to future generations of Neumanns.
But when the attempt to go public backfired — [with the market saying] just because SoftBank thinks it’s worth $47 billion doesn’t mean we think it’s worth that much — he faced a trade-off. It was, “I can keep control or take a bunch of money and walk away” and “Would I rather be poorer and in control or richer and move on?” and he decided, “I’ll take the money.”
I think Lyft’s founders have the same trade-off.
Meta is perhaps a better example of a company whose CEO’s super-voting power has worried many, most recently as the company leaned into the metaverse.
A number of years ago, when Facebook was still Facebook, Mark Zuckerberg proposed doing what Larry Page and Sergey Brin had done at Google but he got a lot of pushback and backed down instead of pushing it through. Now if he wants to sell off stock to diversify his portfolio, he gives up some votes. The way most of these companies with super voting stock are structured is that if they sell it, it automatically converts into one-share-one-stock sales, so someone who buys it doesn’t get extra votes.
A story in Bloomberg earlier today asked why there are so many family dynasties in media — the Murdochs, the Sulzbergers — but not in tech. What do you think?
The media industry is different from the tech industry. Forty years ago, there was analysis of dual-class companies and, at the time, a lot of the dual-class companies were media: the [Bancroft family, which previously owned the Wall Street Journal], the Sulzbergers with the New York Times. There were also a lot of dual-class structures associated with gambling and alcohol companies before tech firms began [taking companies public with this structure in place]. But family firms are nonexistent in tech because the motivations are different; dual-class structures are [solely] meant to keep founders in control. Also, tech companies come and go pretty rapidly. With tech, you can be successful for years and then a new competitor comes along and suddenly . . .
So the bottom line, in your view, is that dual-class shares aren’t going away, no matter that shareholders don’t like them. They don’t dislike them enough to do anything about them. Is that right?
If there was concern about entrenched management pursuing stupid policies for years, investors would be demanding bigger discounts. That might have been the case with Adam Neumann; his control wasn’t something that made investors enthusiastic about the company. But for most tech companies — of which I would not consider WeWork — because you have not only the founder but employees with equity-linked compensation, there is a lot of implicit, if not explicit, pressure on shareholder value maximization rather than kowtowing to the founder’s whims. I’d be surprised if they disappeared.
Tesla brings back European referral program as end of Q1 nears
Tesla is bringing back its referral program to Europe, a strategy that taps into the brand loyalty of customers as it seeks to preserve market share and boost sales before the first quarter of 2023 closes.
The referral program follows Tesla’s move to reduce prices in a variety of markets, including Europe, China and North America.
Starting Tuesday in Europe, new Tesla buyers can receive 100 so-called “Loot Box Credits” when referred by a current Tesla owner, who will get 2,000 credits for the referral. If the referred customer takes delivery before March 31, 2023, they’ll get a bonus of 5,000 free Supercharging kilometres, and the referrer will get 10,000 credits. Those credits can be redeemed for software upgrades, up to 10,000 kilometers of free Supercharging “and more.”
Tesla has never used traditional advertising, so the company has historically used its referral program to get its loyal customer base to promote vehicles. Those rewards have changed over the last few years. At certain points, owners could win rewards like having a photo of their choosing launched into deep space orbit, an invite to an upcoming Tesla event, or even free new Roadsters to owners who accumulated enough referrals.
Tesla realized such extravagant rewards were starting to eat into profits, so in 2019 the automaker paused the program and came back with a more reasonable one that gives the referral giver and receiver 1,000 miles of free Supercharging each.
Last November, Tesla launched a revamped referral program in the U.S., which gives out credits that can be put towards the purchase of Tesla solar products, like the Solar Roof and Solar Panels. Tesla also launched a program in China called Treasure Box, where owners get credits that can be used towards the purchase of accessories like vehicle chargers, t-shirts or shot glasses.
The move in Europe suggests that Tesla is trying to hold onto, or even grow, its market share dominance. Tesla was the most popular EV brand in Europe last year, with the Model Y and Model 3 topping the ranks at 138,373 and 91,257 sales, respectively. Following behind were the Volkswagen ID.4 with 68,409 unit sales, the Fiat 500 electric with 66,732, and the Ford Kuga plug-in hybrid EV with 55,018 sales, according to Inside EVs.
While Tesla was the most popular EV brand in Europe last year, it actually falls behind the large multi-brand OEMs. Volkswagen Group, which includes brands like Audi and VW, actually has the largest market share of plug-in EVs with 20.6%. Stellantis, BMW Group and Hyundai follow with 14.6%, 10.5% and 10.1%, respectively. Mercedes and Tesla are tied at around 9% share.
As of this week, Tesla has finally hit production capacity of 5,000 vehicles per week at its Berlin gigafactory — a milestone CEO Elon Musk had originally promised for the end of 2022. While production numbers don’t equal sales, it’s possible that the increased production in Europe could help the automaker maintain its position and gain even more market share in the future.
The referral program isn’t the only move Tesla has made to boost sales, particularly before it reports quarterly earnings. In January, Tesla cut prices for Model 3 and Model Y vehicles in the U.S. and Europe by 20%. Earlier this month, the automaker slashed Model S and Model X prices in the U.S. as well.
In December 2022, Tesla also provided up to $7,500 discounts for vehicles purchased and delivered before the end of the year in the hopes of attracting buyers who might otherwise wait for the new year when Inflation Reduction Act incentives would kick in.
Pinterest brings shopping capabilities to Shuffles, its collage-making app
Pinterest announced today that it’s testing ways to integrate Shuffles collage content into Pinterest, starting with shopping. Shuffles, which is Pinterest’s collage-making app, launched to general public last November. To use Shuffles, users build collages using Pinterest’s own photo library or by snapping photos of objects they want to include with their iPhone’s camera. The iOS-only app is available in the U.S., Canada, Great Britain, Ireland, Australia and New Zealand.
Shuffles will now have all of the shopping capabilities as regular pins. Users will be able to tap individual cutouts used in collages, see the brand, price, and other product metadata along with similar products to shop.
“Unlike typical product exploration, Shuffles bring an interactivity that makes the experience inspirational and fun,” the company said in a blog post. “Gen-Z is curating fresh, relevant content alongside their peers, which is quickly making for a marketplace of trendy, shoppable ideas. The high density nature of Shuffles, which can include layers of product cutouts from multiple Pins, allows consumers to dig deeper and also connect to other Shuffles that include the same Pins. As we look ahead to how consumer behavior is evolving, we’re testing ways of integrating Shuffles collage content into Pinterest, starting with shopping.”
Although Shuffles surged to become the No. 1 Lifestyle app on the U.S. App Store in August when it was invite-only, the app’s popularity has since declined. By bringing shopping capabilities to Shuffles, Pinterest is likely looking for ways to retain users on the standalone app.
Pinterest also announced that it’s exploring a new takeover feature for advertisers called “Pinterest Premiere Spotlight” that prominently showcases a brand on search. The company says the feature is designed give advertisers a new way to reach users on Pinterest.
The company says 97% of top searches on Pinterest are unbranded, which means users typically don’t type a brand name into their searches on the platform. This gives brands the opportunity to be discovered as they help consumers go from discovery to decision to purchase, Pinterest says. In the coming months, the company planes to offer additional ways to help brands connect with shoppers.
Pinterest also shared some new stats about its Catalogs offering, which lets brands upload their full catalog to the platform and turn their products into dynamic Product Pins. The company says it has seen a 66% increase in retailers setting up shop by uploading or integrating their digital catalogs on its platform, along with 70% growth in active shopping feeds year over year globally.
As part of its most recent earnings release, Pinterest revealed that its platform now has 450 million monthly active users globally, a 4% jump year-on-year. Pinterest has been focused on enhancing the shopping experience on its platform over the past few years, and said during its earnings call that it wants to make every pin shoppable, including videos.
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