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UK’s WhiteHat rebrands as Multiverse, raises $44M to build tech apprenticeships in the US

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University education is getting more expensive, and at the moment it feels a bit like a petrie dish for infections, but the long-term trends continue to show a dramatic growth in the number of people worldwide getting degrees beyond high school, with one big reason for this being that a college degree generally provides better economic security.

But today, a startup that is exploring a different route for those interested in technology and knowledge worker positions — specifically by way of apprenticeships to bring in and train younger people on the job — is announcing a significant round of growth funding to see if it can provide a credible, scalable alternative to that model.

Multiverse, a UK startup that works with organizations to develop these apprenticeships, and then helps source promising, diverse candidates to fill those roles, has raised $44 million, funding that it will be using to spearhead a move into the US market after picking up some 300 clients in the UK and thousands of apprentices.

The Series B is being led by General Catalyst (which has been especially active this week with UK startups: it also led a large round yesterday for Bloom & Wild), with GV (formerly known as Google Ventures), Audacious Ventures, Latitude and SemperVirens also participating. Index Ventures and Lightspeed Venture Partners, who first invested in the company in its $16 million Series A in 2020, also participated.

Valuation is not being disclosed but for what it’s worth, the round was one that generated a lot of interest. In between getting pitched this story and publishing it, the size of the Series B grew by $8 million (it was originally closed at $36 million). The FT notes that the valuation was around $200 million with this round.

The company was originally co-founded as WhiteHat and is officially rebranding today. Co-founder Euan Blair (who happens to be the son of the former UK prime minister Tony Blair and his accomplished barrister wife Cherie Booth Blair) said the name change was because the original name was a reference to how the startup sought to “hack the system for good.”

However, he added, “The scale has become bigger and more evolved.” The new name is to convey that — as in gaming, which is probably the arena where you might have heard this term before — “anything is possible.”

There are “multiple universes” one can inhabit as a post-18 young adult, Blair continued. While it’s been assumed that to get into tech, the obvious route was a two-to-four year (and often more) tour through college or university to pick up a higher education degree, the bet is that Multiverse is making here is that apprenticeships can easily, and widely, become another. “We want to build an outstanding alternative to university and college,” he said. These typically last 1.5 years. 

The idea of an “outstanding alternative” is especially important when thinking of how to target more marginalized groups and how this ties up with how tech companies are looking to be more diverse in the future, without cutting down on the quality of what people are getting out of the experience, or the resulting talent that is getting recruited.

There’s long been a stigma attached less prestigious institutions, and putting money or effort into another channel to perpetuate that doesn’t really make sense or point to progress.

Blair said that currently over half of the people making their way through Multiverse are people of color, and 57% are women, and the plan is to build tools to make that an even firmer part of its mission. 

The startup sees itself as part-tech company and part-education enterprise.

It works with tech companies and others to open up opportunities for people who have not had any higher education or any training, where fresh high school graduates can come in, learn the ropes of a job while getting paid, and then continue on working their way up the ladder with that knowledge base in place.

Apprenticeships on the platform right now range from data analysts through to exhibition designers, and the idea is that by opening up and targeting the US market, the breadth, number and location of roles will grow.

This is not just a social enterprise: there is actual money in this area. Blair prices that it charges the companies it works with range by qualification “but are broadly around the $15,000 mark.” (The individuals applying don’t pay anything, and they will also be paid by the companies providing the apprenticeships.)

On the educational front, Multiverse doesn’t just connect people as a recruiter might: it has a team in place to build out what the “curriculum” might be for a particular apprenticeship, and how to deliver and train people with the requisite skills alongside the practice experience of working, and more.

That latter role, of course, has taken on a more poignant dimension in the last year: concepts like remote training and virtual mentorship have very much come into their own at a time when offices are largely standing empty to help reduce the spread of Covid-19.

Regardless of what happens in the year ahead — fingers crossed that vaccinations and other efforts will help us collectively move past where we are right now — many believe that the infrastructure that has been put into place to keep working virtually will continue to be used, which bodes well for a company like Multiverse that is building a business around that, both with technology it creates itself and will bring in from third parties and partners.

Indeed, the ecosystem of companies building tools to deliver educational content, provide training and work collaboratively has really boomed in the pandemic, giving companies like Multiverse a large library of options for how to bring people into new work situations. (Google, which is now an investor in Multiverse, is very much one of the makers of such education tools.)

Apprenticeships are an interesting area for a startup to tackle. Traditionally, it’s a term that would have been associated mainly with skilled labor positions, rather than “knowledge workers.”

But you can argue that with the bigger swing that the globe has seen away from industrial and towards knowledge economies, there is an argument to be made for building more enterprises and opportunities for an ever wider pool of users, rather than expecting everyone to be shoehorned into the models of the last 50 years. (The latter would essentially imply that college is possibly the only way up.)

You might also be fair to claim that Blair’s connections helped him secure funding and open doors with would-be customers, and that might well be the case, but ultimately the startup will live or die by how well it executes on its premise, whether it finds a good way to connect more people, engage them in opportunities, and keep them on board.

This is what really attracted the investors, said Joel Cutler, managing director and co-founder of General Catalyst.

“Euan has a genuine belief that this is important, and when you talk to him, you get a  feeling of manifest destiny,” Cutler said in an interview. In response to the question of family connections, he said that this was precisely the kind of issue that the technology industry should be tackling to fight.

“Of all the industries to break the mold of where you went to school, it should be the tech world that will do that, since it is far more of a meritocracy than others. This is the perfect place to start to break that mold,” he said. “Education will be super valuable but apprenticeships will also be important.” He noted that another company that General Catalyst invests in, Guild Education, is addressing similar opportunities, or rather the gaps in current opportunities, for older people.

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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