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Stonks, flying burritos and my boss’s boss’s boss’s boss

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Welcome back to The TechCrunch Exchange, a weekly startups-and-markets newsletter. It’s broadly based on the daily column that appears on Extra Crunch, but free, and made for your weekend reading. Want it in your inbox every Saturday morning? Sign up here.

What a week. What a month. Are you doing all right? It’s okay if you are tired. We all are. That’s why we have weekends.

Let’s reflect on what happened this week: Individual traders outraged more professional investors by doing something hilarious, namely taking a trade that made some sense — betting that an atrophying physical retailer was going to continue obsolesce — and inverting it.

By going long on GameStop, investors flipped the script on the smart money. Then all heck snapped free, some stocks got blocked on trading services, Congress got mad, billionaires started to front on Twitter like they were the Common Man, some cryptos surged, including Dogecoin of all things, and as we headed into the weekend nothing was truly resolved. It was weird.

Let’s talk over the lessons we’ve learned. First, don’t short a stock so heavily that you are at risk of having the trade exposed and inverted to your detriment. Second, the fintech startups that TechCrunch has covered for years were more brittle than anticipated, either thanks to reserve requirements or simple platform risk. And third, things can always get dumber.

Evidence of that final lesson came during the week’s news cycle in which it became known that WeWork might pursue a public listing via a SPAC. So much for this year being more serious and normal than 2020.

But let’s stop recapping and get into our main topic today, namely a chat that I had with the person I actually work for, Guru Gowrappan, the CEO of Verizon Media Group (VMG). For those who don’t know, Verizon owns VMG, which in turn owns TechCrunch. VMG is a collection of assets, ranging from Yahoo to media brands to technology products. It does billions in yearly revenue, which should help frame how far above my seat — an excellent perch inside of TechCrunch, but not one that comes with org-chart stature — Guru sits.

Very far away.

But we follow each other on Twitter and after Verizon reported earnings this week, inclusive of some honestly pretty good numbers from VMG that I tweeted about, I got about half an hour of Guru’s time. This meant that I had my boss’s boss’s [etc] boss on the record with zero agenda. How could I say no?

For context, VMG generated $2.3 billion in Q4 revenue, up 11% from the year-ago quarter. Verizon described that as “the first quarter of year-over-year growth since the Yahoo! acquisition.” What drove the result? Per the Verizon earnings call, “strong advertising trends with demand-side platform revenue growing 41% compared to the prior year.”

If you are Guru or, frankly, your humble servant, the growth was welcome after VMG’s revenue had dipped to $1.4 billion in Q2 2020, off 24.5% from its year-ago result.

I had a few questions: Would the recent advertising momentum persist in 2021, something that could impact a host of businesses far beyond the VMG org; how important was it to Verizon that VMG had managed to post year-over-year growth; how he expects to balance commerce revenue and journalism; and what Guru thinks about new media products like the recent rebirth of newsletter tech, something that Substack and Twitter and even Facebook are tinkering with.

Here’s what I learned:

  • Regarding strong advertising performance in the final months of the year during COVID, Guru said that “the core fundamentals [of] the market dynamics have changed so that they’re more permanent,” adding that consumer behavior is now “more digital, more online” than before.
  • The VMG CEO declined to share Q1 2021 expectations in detail, but did note that VMG is aiming to “continue [its] momentum.”
  • Part of that momentum comes from subscription products, which Guru cited as a win: “If you look at one of the trends that happened due to COVID, consumers [are] moving to more trusted content and want to spend more time and money on consuming subscription-based products […] TechCrunch/Extra Crunch grew almost 196% year-on-year.”
  • My read of his answer to where we are today is that it’s not a bad time to be in the online media game, which isn’t something that has been true much in the past few years, looking around the remains of the journalism industry.
  • Regarding VMG’s home inside of Verizon — something that I’ve thought about after the Buzzfeed-HuffPost deal — I asked Guru if VMG’s recent financial performance made our company more attractive to Verizon, and if we have proven the bet that we were trying to make. This, by the way, is the sort of question that is pretty easy to write down, but slightly harder to ask when you are talking to someone who could terminate you at will. Anyway, Guru said “completely” in response. The VMG CEO summarized the Verizon CEO as saying that the media business is “core” to Verizon, and that our parent company “will continue to invest in the media business while we continue to deliver on our promise.” So sign up for Extra Crunch.
  • Guru said VMG won’t exchange revenue for credibility when it comes to promoting e-commerce across its platform: “At no point will we trade dollar value in a transaction for trust; there’s no way. […] The editorial team keeps me honest,” he said, adding that he stays out of changes that might upset journalistic balance. That was good to hear.
  • And finally, are there new media products that VMG may want to emulate, or buy? Guru was generally bullish on personalization, but declined to dish that VMG is about to buy Substack or anything like that.

Oh and I asked if VMG is going to sell, or otherwise divest, any other media properties in the wake of the HuffPost-BuzzFeed decision. Guru said that the Verizon CEO said that the broader company is “fully committed” to the media business, and that that won’t be “built upon divestment.” Instead, he said, it will be built “upon investing and growing,” adding that there are “no plans to sell any additional properties.” As I like my health insurance, that was nice to hear.

I understand that the above is not a standard sort of Exchange entry, but one thing that I will always try to do is take the conversations that come my way thanks to my job, and bring them to you.

Now, back to venture capital.

Market Notes

GameStop was your entire Twitter feed this week but there is other stuff you need to know. Alfred, a US-based fintech raised $100 million on Tuesday, to pick an example. The company fuses digital intelligence and humans to help users manage their financial lives. Neat.

And adding to our recent data-focused coverage of 2020 venture data — including a dive into the African VC market — investing group Work-Bench put together a look at how NYC’s enterprise tech scene performed in the second half of last year. This is the exact sort of data I would parse for you during a more regular week. But since we had this week, you have to do it yourself.

Sticking to data, Hallo, a startup that helps companies recruit more diverse candidates, dropped a sheaf of data in its “Black Founder Funding Q4 2020” report. Read it. If you don’t have time, I’ll give you the headline stat that both caught my eye and depressed my heart: “Hallo’s research found that out of the 1,537 companies analyzed [in Q4 2020], 40 were led by Black founders.” 

And this week I got to yammer with Microsoft after it reported earnings. Saving most of that for a later date, two things were clear: The cloud world still has oodles of growth ahead of it, which is good news for a large chunk of the startup software market. And if you wanted more data on Teams’ growth to better understand why Salesforce bought Slack, wait another quarter.

Various and Sundry

Closing out, in August of 2014 I came up with the idea for a burrito cannon food delivery service. You would push a button in an app, and it would deliver a burrito to your office sans the need for you to make choices. Then Postmates actually built a burrito cannon into its app, which was both hilarious and fun.

Fast forward to 2021, and Postmates is now part of Uber. And it is back with the return of the burrito cannon:

I did not anticipate that my lazy, stupid idea would help get an NFL star, over a half decade later, to sprint down a field as an industrial-scale potato cannon shot a Mexican delight in his direction. But it’s 2021 and this is where we are.

Evidence, I think, that all my startup ideas are brilliant,

Alex

Lyron Foster is a Hawaii based African American Musician, Author, Actor, Blogger, Filmmaker, Philanthropist and Multinational Serial Tech Entrepreneur.

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Personal skin problems leads founder to launch skincare startup Nøie, raises $12M Series A

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Inspired by his own problems with skin ailments, tech founder Daniel Jensen decided there had to be a better way. So, using an in-house tech platform, his Copenhagen-based startup Nøie developed its own database of skin profiles, to better care for sensitive skin.

Nøie has now raised $12m in a Series A funding round led by Talis Capital, with participation from Inventure, as well as existing investors including Thomas Ryge Mikkelsen, former CMO of Pandora, and Kristian Schrøder Hart-Hansen, former CEO of LEO Pharma’s Innovation Lab.

Nøie’s customized skincare products target sensitive skin conditions including acne, psoriasis and eczema. Using its own R&D, Nøie says it screens thousands of skincare products on the market, selects what it thinks are the best, and uses an algorithm to assign customers to their ‘skin family’. Customers then get recommendations for customized products to suit their skin.

Skin+Me is probably the best-known perceived competitor, but this is a prescription provider. Noie is non-prescription.

Jensen said: “We firmly believe that the biggest competition is the broader skincare industry and the consumer behavior that comes with it. I truly believe that in 2030 we’ll be surprised that we ever went into a store and picked up a one-size-fits-all product to combat our skincare issues, based on what has the nicest packaging or the best marketing. In a sense, any new company that emerges in this space are peers to us: we’re all working together to intrinsically change how people choose skincare products. We’re all demonstrating to people that they can now receive highly-personalized products based on their own skin’s specific needs.”

Of his own problems to find the right skincare provider, he said: “It’s just extremely difficult to find something that works. When you look at technology, online, and all our apps and everything, we got so smart in so many areas, but not when it comes to consumer skin products. I believe that in five or 10 years down the line, you’ll be laughing that we really used to just go in and pick up products just off the shelf, without knowing what we’re supposed to be using. I think everything we will be using in the bathroom will be customized.”

Beatrice Aliprandi, principal at Talis Capital, said: “For too long have both the dermatology sector and the skincare industry relied on the outdated ‘one-size-fits-all’ approach to addressing chronic skin conditions. By instead taking a data-driven and community feedback approach, Nøie is building the next generation of skincare by providing complete personalization for its customers at a massive scale, pioneering the next revolution in skincare.”

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Comms expert and VC Caryn Marooney will detail how to get attention at TC Early Stage

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We’re thrilled to announce Caryn Marooney is speaking at our upcoming TechCrunch Early Stage virtual event in July. She spoke with us last year and we had to have her back.

Just look at her resume. She was the co-founder and CEO of The Outcast Agency, one of Silicon Valley’s best-regarded public relations firms. She left her company to serve as VP of Global Communication at Facebook, which she did for eight years, overseeing communication for Facebook, Instagram, WhatsApp and Oculus. In 2019 she joined Coatue Management as a general partner, where she went on to invest in Startburst, Supabase, Defined Networks and others.

Needless to say, Marooney is one of the Valley’s experts on getting people’s attention — a skill that’s critical when running a startup, nonprofit or school bake sale.

She said it best last year: “People just fundamentally aren’t walking around caring about this new startup — actually, nobody does.” So how do you get people to care? That’s the trick and why we’re having her back to speak on this evergreen topic.

Watch her presentation from 2020 here. It’s fantastic.

One of the great things about TC Early Stage is that the show is designed around breakout sessions, with each speaker leading a chat around a specific startup core competency (like fundraising, designing a brand, mastering the art of PR and more). Moreover, there is plenty of time for audience Q&A in each session.

Pick up your ticket for the event, which goes down July 8 and 9, right here. And if you do it today, you’ll save a cool $100 off of your registration.


 

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Lightmatter’s photonic AI ambitions light up an $80M B round

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AI is fundamental to many products and services today, but its hunger for data and computing cycles is bottomless. Lightmatter plans to leapfrog Moore’s law with its ultra-fast photonic chips specialized for AI work, and with a new $80M round the company is poised to take its light-powered computing to market.

We first covered Lightmatter in 2018, when the founders were fresh out of MIT and had raised $11M to prove that their idea of photonic computing was as valuable as they claimed. They spent the next three years and change building and refining the tech — and running into all the hurdles that hardware startups and technical founders tend to find.

For a full breakdown of what the company’s tech does, read that feature — the essentials haven’t changed.

In a nutshell, Lightmatter’s chips perform certain complex calculations fundamental to machine learning in a flash — literally. Instead of using charge, logic gates, and transistors to record and manipulate data, the chips use photonic circuits that perform the calculations by manipulating the path of light. It’s been possible for years, but until recently getting it to work at scale, and for a practical, indeed a highly valuable purpose has not.

Prototype to product

It wasn’t entirely clear in 2018 when Lightmatter was getting off the ground whether this tech would be something they could sell to replace more traditional compute clusters like the thousands of custom units companies like Google and Amazon use to train their AIs.

“We knew in principle the tech should be great, but there were a lot of details we needed to figure out,” CEO and co-founder Nick Harris told TechCrunch in an interview. “Lots of hard theoretical computer science and chip design challenges we needed to overcome… and COVID was a beast.”

With suppliers out of commission and many in the industry pausing partnerships, delaying projects, and other things, the pandemic put Lightmatter months behind schedule, but they came out the other side stronger. Harris said that the challenges of building a chip company from the ground up were substantial, if not unexpected.

A rack of Lightmatter servers.

Image Credits: Lightmatter

“In general what we’re doing is pretty crazy,” he admitted. “We’re building computers from nothing. We design the chip, the chip package, the card the chip package sits on, the system the cards go in, and the software that runs on it…. we’ve had to build a company that straddles all this expertise.”

That company has grown from its handful of founders to more than 70 employees in Mountain View and Boston, and the growth will continue as it brings its new product to market.

Where a few years ago Lightmatter’s product was more of a well-informed twinkle in the eye, now it has taken a more solid form in the Envise, which they call a ‘general purpose photonic AI accelerator.” It’s a server unit designed to fit into normal datacenter racks but equipped with multiple photonic computing units, which can perform neural network inference processes at mind-boggling speeds. (It’s limited to certain types of calculations, namely linear algebra for now, and not complex logic, but this type of math happens to be a major component of machine learning processes.)

Harris was reticent to provide exact numbers on performance improvements, but more because those improvements are increasing than that they’re not impressive enough. The website suggests it’s 5x faster than an NVIDIA A100 unit on a large transformer model like BERT, while using about 15 percent of the energy. That makes the platform doubly attractive to deep-pocketed AI giants like Google and Amazon, which constantly require both more computing power and who pay through the nose for the energy required to use it. Either better performance or lower energy cost would be great — both together is irresistible.

It’s Lightmatter’s initial plan to test these units with its most likely customers by the end of 2021, refining it and bringing it up to production levels so it can be sold widely. But Harris emphasized this was essentially the Model T of their new approach.

“If we’re right, we just invented the next transistor,” he said, and for the purposes of large-scale computing, the claim is not without merit. You’re not going to have a miniature photonic computer in your hand any time soon, but in datacenters, where as much as 10 percent of the world’s power is predicted to go by 2030, “they really have unlimited appetite.”

The color of math

A Lightmatter chip with its logo on the side.

Image Credits: Lightmatter

There are two main ways by which Lightmatter plans to improve the capabilities of its photonic computers. The first, and most insane sounding, is processing in different colors.

It’s not so wild when you think about how these computers actually work. Transistors, which have been at the heart of computing for decades, use electricity to perform logic operations, opening and closing gates and so on. At a macro scale you can have different frequencies of electricity that can be manipulated like waveforms, but at this smaller scale it doesn’t work like that. You just have one form of currency, electrons, and gates are either open or closed.

In Lightmatter’s devices, however, light passes through waveguides that perform the calculations as it goes, simplifying (in some ways) and speeding up the process. And light, as we all learned in science class, comes in a variety of wavelengths — all of which can be used independently and simultaneously on the same hardware.

The same optical magic that lets a signal sent from a blue laser be processed at the speed of light works for a red or a green laser with minimal modification. And if the light waves don’t interfere with one another, they can travel through the same optical components at the same time without losing any coherence.

That means that if a Lightmatter chip can do, say, a million calculations a second using a red laser source, adding another color doubles that to two million, adding another makes three — with very little in the way of modification needed. The chief obstacle is getting lasers that are up to the task, Harris said. Being able to take roughly the same hardware and near-instantly double, triple, or 20x the performance makes for a nice roadmap.

It also leads to the second challenge the company is working on clearing away, namely interconnect. Any supercomputer is composed of many small individual computers, thousands and thousands of them, working in perfect synchrony. In order for them to do so, they need to communicate constantly to make sure each core knows what other cores are doing, and otherwise coordinate the immensely complex computing problems supercomputing is designed to take on. (Intel talks about this “concurrency” problem building an exa-scale supercomputer here.)

“One of the things we’ve learned along the way is, how do you get these chips to talk to each other when they get to the point where they’re so fast that they’re just sitting there waiting most of the time?” said Harris. The Lightmatter chips are doing work so quickly that they can’t rely on traditional computing cores to coordinate between them.

A photonic problem, it seems, requires a photonic solution: a wafer-scale interconnect board that uses waveguides instead of fiber optics to transfer data between the different cores. Fiber connections aren’t exactly slow, of course, but they aren’t infinitely fast, and the fibers themselves are actually fairly bulky at the scales chips are designed, limiting the number of channels you can have between cores.

“We built the optics, the waveguides, into the chip itself; we can fit 40 waveguides into the space of a single optical fiber,” said Harris. “That means you have way more lanes operating in parallel — it gets you to absurdly high interconnect speeds.” (Chip and server fiends can find that specs here.)

The optical interconnect board is called Passage, and will be part of a future generation of its Envise products — but as with the color calculation, it’s for a future generation. 5-10x performance at a fraction of the power will have to satisfy their potential customers for the present.

Putting that $80M to work

Those customers, initially the “hyper-scale” data handlers that already own datacenters and supercomputers that they’re maxing out, will be getting the first test chips later this year. That’s where the B round is primarily going, Harris said: “We’re funding our early access program.”

That means both building hardware to ship (very expensive per unit before economies of scale kick in, not to mention the present difficulties with suppliers) and building the go-to-market team. Servicing, support, and the immense amount of software that goes along with something like this — there’s a lot of hiring going on.

The round itself was led by Viking Global Investors, with participation from HP Enterprise, Lockheed Martin, SIP Global Partners, and previous investors GV, Matrix Partners and Spark Capital. It brings their total raised to about $113 million; There was the initial $11M A round, then GV hopping on with a $22M A-1, then this $80M.

Although there are other companies pursuing photonic computing and its potential applications in neural networks especially, Harris didn’t seem to feel that they were nipping at Lightmatter’s heels. Few if any seem close to shipping a product, and at any rate this is a market that is in the middle of its hockey stick moment. He pointed to an OpenAI study indicating that the demand for AI-related computing is increasing far faster than existing technology can provide it, except with ever larger datacenters.

The next decade will bring economic and political pressure to rein in that power consumption, just as we’ve seen with the cryptocurrency world, and Lightmatter is poised and ready to provide an efficient, powerful alternative to the usual GPU-based fare.

As Harris suggested hopefully earlier, what his company has made is potentially transformative in the industry and if so there’s no hurry — if there’s a gold rush, they’ve already staked their claim.

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