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Tile secures $40 million to take on Apple AirTag with new products

Tile, the maker of Bluetooth-powered lost item finder beacons and, more recently, a staunch Apple critic, announced today it has raised $40 million in non-dilutive debt financing from Capital IP. The funding will be put toward investment in Tile’s finding technologies, ahead of the company’s plan to unveil a new slate of products and features that the company believes will help it to better compete with Apple’s AirTags and further expand its market.

The company has been a longtime leader in the lost item finder space, offering consumers small devices they can attach to items — like handbags, luggage, bikes, wallets, keys and more — which can then be tracked using the Tile smartphone app for iOS or Android. When items go missing, the Tile app leverages Bluetooth to find the items and can make them play a sound. If the items are further afield, Tile taps into its broader finding network consisting of everyone who has the app installed on their phone and other access points. Through this network, Tile is able to automatically and anonymously communicate the lost item’s location back to its owner through their own Tile app.

Image Credits: Tile

Tile has also formed partnerships focused on integrating its finding network into over 40 different third-party devices, including those across audio, travel, wearables and PC categories. Notable brand partners include HP, Dell, Fitbit, Skullcandy, Away, Xfinity, Plantronics, Sennheiser, Bose, Intel and others. Tile says it’s seen 200% year-over-year growth on activations of these devices with its service embedded.

To date, Tile has sold more than 40 million devices and has over 425,000 paying customers — a metric it’s revealing for the first time. It doesn’t disclose its total number of users, both free and paid combined, however. During the first half of 2021, Tile says revenues increased by over 50%, but didn’t provide hard numbers.

While Tile admits that the COVID-19 pandemic had some impacts on international expansions, as some markets have been slower to rebound, it has still seen strong performance outside the U.S., and considers that a continued focus.

The pandemic, however, hasn’t been Tile’s only speed bump.

When Apple announced its plans to compete with the launch of AirTags, Tile went on record to call it unfair competition. Unlike Tile devices, Apple’s products could tap into the iPhone’s U1 chip to allow for more accurate finding through the use of ultra-wideband technologies available on newer iPhone models. Tile, meanwhile, has plans for its own ultra-wideband-powered device, but hadn’t been provided the same access. In other words, Apple gave its own lost item finder early, exclusive access to a feature that would allow it to differentiate itself from the competition. (Apple has since announced it’s making ultra-wideband APIs available to third-party developers, but this access wasn’t available from day one of AirTag’s arrival.)

Image Credits: Tile internal concept art

Tile has been vocal on the matter of Apple’s anti-competitive behavior, having testified in multiple congressional hearings alongside other Apple critics, like Spotify and Match. As a result of increased regulatory pressure, Apple later opened up its Find My network to third-party devices, in an effort to placate Tile and the other rivals its AirTags would disadvantage.

But Tile doesn’t want to route its customers to Apple’s first-party app — it intends to use its own app in order to compete based on its proprietary features and services. Among other things, this includes Tile’s subscriptions. A base plan is $29.99 per year, offering features like free battery replacement, smart alerts and location history. A $99.99 per year plan also adds insurance of sorts — it pays up to $1,000 per year for items it can’t find. (AirTag doesn’t do that.)

Despite its many differentiators, Tile faces steep competition from the ultra-wideband-capable AirTags, which have the advantage of tapping into Apple’s own finding network of potentially hundreds of millions of iPhone owners.

However, Tile CEO CJ Prober — who joined the company in 2018 — claims AirTag hasn’t impacted the company’s revenue or device sales.

“But that doesn’t take away from the fact that they’re making things harder for us,” he says of Apple. “We’re a growing business. We’re winning the hearts and minds of consumers… and they’re competing unfairly.”

“When you own the platform, you shouldn’t be able to identify a category that you want to enter, disadvantage the incumbents in that category, and then advantage yourself — like they did in our case,” he adds.

Tile is preparing to announce an upcoming product refresh that may allow it to better take on the AirTag. Presumably, this will include the pre-announced ultra-wideband version of Tile, but the company says full details will be shared next week. Tile may also expand its lineup in other ways that will allow it to better compete based on look and feel, size and shape, and functionality.

Tile’s last round of funding was $45 million in growth equity in 2019. Now it’s shifted to debt. In addition to new debt financing, Tile is also refinancing some of its existing debt with this fundraise, it says.

“My philosophy is it’s always good to have a mix of debt and equity. So some amount of debt on the balance sheet is good. And it doesn’t incur dilution to our shareholders,” Prober says. “We felt this was the right mix of capital choice for us.”

The company chose to work with Capital IP, a group it’s had a relationship with over the last three years, and who Tile had considered bringing on as an investor. The group has remained interested in Tile and excited about its trajectory, Prober notes.

“We are excited to partner with the Tile team as they continue to define and lead the finding category through hardware and software-based innovations,” said Capital IP’s Managing Partner Riyad Shahjahan, in a statement. “The impressive revenue growth and fast-climbing subscriber trends underline the value proposition that Tile delivers in a platform-agnostic manner, and were a critical driver in our decision to invest. The Tile team has an ambitious roadmap ahead and we look forward to supporting their entry into new markets and applications to further cement their market leadership,” he added.

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Intel rumored to be in talks to buy chip manufacturer GlobalFoundries for $30B

When it comes to M&A in the chip world, the numbers are never small. In 2020, four deals involving chip companies totaled $106 billion, led by Nvidia snagging ARM for $40 billion. One surprise from last year’s chip-laced M&A frenzy was Intel remaining on the sidelines. That would change if a rumored $30 billion deal to buy chip manufacturing concern GlobalFoundries comes to fruition.

The rumor was first reported by The Wall Street Journal yesterday.

Patrick Moorhead, founder and principal analyst at Moor Insight & Strategies, who watches the chip industry closely, says that snagging GlobalFoundries would certainly make sense for Intel. The company is currently pursuing a new strategy to manufacture and sell chips for both Intel and to others under CEO Pat Gelsinger, who came on board in January to turn around the flagging chip maker.

“GlobalFoundries has technologies and processes that are specialized for 5G RF, IoT and automotive. Intel with GlobalFoundries would become what I call a ‘full-stack provider’ that could offer a customer everything. This is in full alignment with IDM 2.0 (Intel’s chip manufacturing strategy) and would get Intel there years before it could without GlobalFoundries,” Moorhead told TechCrunch.

It would also give Intel a chip manufacturing facility at a time when there are global chip shortages and huge demand for product from every corner, due in part to the pandemic and the impact it has had on the global supply chain. Intel has already indicated it has plans to spend more than $20 billion to build two fabs (chip manufacturing plants) in Arizona. Adding GlobalFoundries to these plans would give them a broad set of manufacturing capabilities in the coming years if it came to pass, but would also involve a significant investment of tens of billions of dollars to get there.

GlobalFoundries is a worldwide chip manufacturing concern based in the U.S. The company was spun off from Intel’s rival chip maker AMD in 2012, and is currently owned by Mubadala Investment Company, the investment arm of the government of Abu Dhabi.

Investors seem to like the idea of combining these two companies, with Intel stock up 1.59% as of publication. It’s important to note that this deal is still in the rumor stage and nothing is definitive or final yet. We will let you know if that changes.

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SambaNova raises $676M at a $5.1B valuation to double down on cloud-based AI software for enterprises

Artificial intelligence technology holds a huge amount of promise for enterprises — as a tool to process and understand their data more efficiently; as a way to leapfrog into new kinds of services and products; and as a critical stepping stone into whatever the future might hold for their businesses. But the problem for many enterprises is that they are not tech businesses at their core, so bringing on and using AI will typically involve a lot of heavy lifting. Today, one of the startups building AI services is announcing a big round of funding to help bridge that gap.

SambaNova — a startup building AI hardware and integrated systems that run on it that only officially came out of three years in stealth last December — is announcing a huge round of funding today to take its business out into the world. The company has closed on $676 million in financing, a Series D that co-founder and CEO Rodrigo Liang has confirmed values the company at $5.1 billion.

The round is being led by SoftBank, which is making the investment via Vision Fund 2. Temasek and the government of Singapore Investment Corp. (GIC), both new investors, are also participating, along with previous backers BlackRock, Intel Capital, GV (formerly Google Ventures), Walden International and WRVI, among other unnamed investors. (Sidenote: BlackRock and Temasek separately kicked off an investment partnership yesterday, although it’s not clear if this falls into that remit.)

Co-founded by two Stanford professors, Kunle Olukotun and Chris Ré, and Liang, who had been an engineering executive at Oracle, SambaNova has been around since 2017 and has raised more than $1 billion to date — both to build out its AI-focused hardware, which it calls DataScale, and to build out the system that runs on it. (The “Samba” in the name is a reference to Liang’s Brazilian heritage, he said, but also the Latino music and dance that speaks of constant movement and shifting, not unlike the journey AI data regularly needs to take that makes it too complicated and too intensive to run on more traditional systems.)

SambaNova on one level competes for enterprise business against companies like Nvidia, Cerebras Systems and Graphcore — another startup in the space which earlier this year also raised a significant round. However, SambaNova has also taken a slightly different approach to the AI challenge.

In December, the startup launched Dataflow-as-a-Service as an on-demand, subscription-based way for enterprises to tap into SambaNova’s AI system, with the focus just on the applications that run on it, without needing to focus on maintaining those systems themselves. It’s the latter that SambaNova will be focusing on selling and delivering with this latest tranche of funding, Liang said.

SambaNova’s opportunity, Liang believes, lies in selling software-based AI systems to enterprises that are keen to adopt more AI into their business, but might lack the talent and other resources to do so if it requires running and maintaining large systems.

“The market right now has a lot of interest in AI. They are finding they have to transition to this way of competing, and it’s no longer acceptable not to be considering it,” said Liang in an interview.

The problem, he said, is that most AI companies “want to talk chips,” yet many would-be customers will lack the teams and appetite to essentially become technology companies to run those services. “Rather than you coming in and thinking about how to hire scientists and hire and then deploy an AI service, you can now subscribe, and bring in that technology overnight. We’re very proud that our technology is pushing the envelope on cases in the industry.”

To be clear, a company will still need data scientists, just not the same number, and specifically not the same number dedicating their time to maintaining systems, updating code and other more incremental work that comes managing an end-to-end process.

SambaNova has not disclosed many customers so far in the work that it has done — the two reference names it provided to me are both research labs, the Argonne National Laboratory and the Lawrence Livermore National Laboratory — but Liang noted some typical use cases.

One was in imaging, such as in the healthcare industry, where the company’s technology is being used to help train systems based on high-resolution imagery, along with other healthcare-related work. The coincidentally-named Corona supercomputer at the Livermore Lab (it was named after the 2014 lunar eclipse, not the dark cloud of a pandemic that we’re currently living through) is using SambaNova’s technology to help run calculations related to some COVID-19 therapeutic and antiviral compound research, Marshall Choy, the company’s VP of product, told me.

Another set of applications involves building systems around custom language models, for example in specific industries like finance, to process data quicker. And a third is in recommendation algorithms, something that appears in most digital services and frankly could always do to work a little better than it does today. I’m guessing that in the coming months it will release more information about where and who is using its technology.

Liang also would not comment on whether Google and Intel were specifically tapping SambaNova as a partner in their own AI services, but he didn’t rule out the prospect of partnering to go to market. Indeed, both have strong enterprise businesses that span well beyond technology companies, and so working with a third party that is helping to make even their own AI cores more accessible could be an interesting prospect, and SambaNova’s DataScale (and the Dataflow-as-a-Service system) both work using input from frameworks like PyTorch and TensorFlow, so there is a level of integration already there.

“We’re quite comfortable in collaborating with others in this space,” Liang said. “We think the market will be large and will start segmenting. The opportunity for us is in being able to take hold of some of the hardest problems in a much simpler way on their behalf. That is a very valuable proposition.”

The promise of creating a more accessible AI for businesses is one that has eluded quite a few companies to date, so the prospect of finally cracking that nut is one that appeals to investors.

“SambaNova has created a leading systems architecture that is flexible, efficient and scalable. This provides a holistic software and hardware solution for customers and alleviates the additional complexity driven by single technology component solutions,” said Deep Nishar, senior managing partner at SoftBank Investment Advisers, in a statement. “We are excited to partner with Rodrigo and the SambaNova team to support their mission of bringing advanced AI solutions to organizations globally.”

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Google Cloud hires Intel veteran to head its custom chip efforts

There has been a growing industry trend in recent years for large-scale companies to build their own chips. As part of that, Google announced today that it has hired long-time Intel executive Uri Frank as vice president to run its custom chip division.

“The future of cloud infrastructure is bright, and it’s changing fast. As we continue to work to meet computing demands from around the world, today we are thrilled to welcome Uri Frank as our VP of Engineering for server chip design,” Amin Vahdat, Google Fellow and VP of systems infrastructure wrote in a blog post announcing the hire.

With Frank, Google gets an experienced chip industry executive, who spent more than two decades at Intel rising from engineering roles to corporate vice president at the Design Engineering Group, his final role before leaving the company earlier this month.

Frank will lead the custom chip division in Israel as part of Google. As he said in his announcement on LinkedIn, this was a big step to join a company with a long history of building custom silicon.

“Google has designed and built some of the world’s largest and most efficient computing systems. For a long time, custom chips have been an important part of this strategy. I look forward to growing a team here in Israel while accelerating Google Cloud’s innovations in compute infrastructure,” Frank wrote.

Google’s history of building its own chips dates back to 2015 when it launched the first TensorFlow chips. It moved into video processing chips in 2018 and added OpenTitan , an open-source chip with a security angle in 2019.

Frank’s job will be to continue to build on this previous experience to work with customers and partners to build new custom chip architectures. The company wants to move away from buying motherboard components from different vendors to building its own “system on a chip” or SoC, which it says will be drastically more efficient.

“Instead of integrating components on a motherboard where they are separated by inches of wires, we are turning to “Systems on Chip” (SoC) designs where multiple functions sit on the same chip, or on multiple chips inside one package. In other words, the SoC is the new motherboard,” Vahdat wrote.

While Google was early to the “Build Your Own Chip” movement, we’ve seen other large scale companies like Amazon, Facebook, Apple and Microsoft begin building their own custom chips in recent years to meet each company’s unique needs and give more precise control over the relationship between the hardware and software.

It will be Frank’s job to lead Google’s custom chip unit and help bring it to the next level.

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Anthony Lin named permanent managing director and head of Intel Capital

When Wendell Brooks stepped down as managing partner and head of Intel Capital last August, Anthony Lin was named to replace him on an interim basis. At the time, it wasn’t clear if he would be given the role permanently, but today, six months later, the answer is known.

In a letter to the firm’s portfolio CEOs published on the company website, Lin mentioned, almost casually, that he had taken on the two roles on a permanent basis. “Personally, I want to share that I have been appointed to managing partner and head of Intel Capital. I have been a member of the investment committee for the past several years and am humbly awed by the talent of our entrepreneurs and our team,” he wrote.

Lin takes over in a time of turmoil for Intel as the company struggles to regain its place in the semiconductor business that it dominated for decades. Meanwhile, Intel itself has a new CEO with Pat Gelsinger returning in January from VMware to lead the organization.

As the corporate investment arm of Intel, it looks for companies that can help the parent company understand where to invest resources in the future. If that is its goal, perhaps it hasn’t done a great job, as Intel has lost some of its edge when it comes to innovation.

Lin, who was formerly head of mergers and acquisitions and international investing at the firm, can use the power of the firm’s investment dollars to try to help point the parent company in the right direction and help find new ways to build innovative solutions on the Intel platform.

Lin acknowledged how challenging 2020 was for everyone, and his company was no exception, but the firm invested in 75 startups, including 35 new deals and 40 deals involving companies in which it had previously invested. It has also made a commitment to invest in companies with more diverse founders. To that end, 30% of new venture-stage dollars went to startups led by diverse leaders, according to Lin.

What’s more, the company made a five-year commitment that 15% of all its deals would go to companies with Black founders. It made some progress toward that goal, but there is still a ways to go. “At the end of 2020, 9% of our new venture deals and 15% of our venture dollars committed were in companies led by Black founders. We know there is more progress to be made and we will continue to encourage, foster and invest in diverse and inclusive teams,” he wrote.

Lin faces a big challenge ahead as he takes over a role that had the same leader for the first 28 years in Arvind Sodhani. His predecessor, Brooks, was there for five years. Now it passes to Lin, and he needs to use the firm’s investment might to help Gelsinger advance the goals of the broader firm, while making sound investments.

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Metalenz reimagines the camera in 2D and raises $10M to ship it

As impressive as the cameras in our smartphones are, they’re fundamentally limited by the physical necessities of lenses and sensors. Metalenz skips over that part with a camera made of a single “metasurface” that could save precious space and battery life in phones and other devices… and they’re about to ship it.

The concept is similar to, but not descended from, the “metamaterials” that gave rise to flat beam-forming radar and lidar of Lumotive and Echodyne. The idea is to take a complex 3D structure and accomplish what it does using a precisely engineered “2D” surface — not actually two-dimensional, of course, but usually a plane with features measured in microns.

In the case of a camera, the main components are of course a lens (these days it’s usually several stacked), which corrals the light, and an image sensor, which senses and measures that light. The problem faced by cameras now, particularly in smartphones, is that the lenses can’t be made much smaller without seriously affecting the clarity of the image. Likewise sensors are nearly at the limit of how much light they can work with. Consequently, most of the photography advancements of the last few years have been done on the computational side.

Using an engineered surface that does away with the need for complex optics and other camera systems has been a goal for years. Back in 2016 I wrote about a NASA project that took inspiration from moth eyes to create a 2D camera of sorts. It’s harder than it sounds, though — usable imagery has been generated in labs, but it’s not the kind of thing that you take to Apple or Samsung.

Metalenz aims to change that. The company’s tech is built on the work of Harvard’s Federico Capasso, who has been publishing on the science behind metasurfaces for years. He and Rob Devlin, who did his doctorate work in Capasso’s lab, co-founded the company to commercialize their efforts.

“Early demos were extremely inefficient,” said Devlin of the field’s first entrants. “You had light scattering all over the place, the materials and processes were non-standard, the designs weren’t able to handle the demands that a real world throws at you. Making one that works and publishing a paper on it is one thing, making 10 million and making sure they all do the same thing is another.”

Their breakthrough — if years of hard work and research can be called that — is the ability not just to make a metasurface camera that produces decent images, but to do it without exotic components or manufacturing processes.

“We’re really using all standard semiconductor processes and materials here, the exact same equipment — but with lenses instead of electronics,” said Devlin. “We can already make a million lenses a day with our foundry partners.”

Diagram comparing the multi-lens barrel of a conventional phone camera, and their simpler "meta-optic"

The thing at the bottom is the chip where the image processor and logic would be, but the meta-optic could also integrate with that. The top is a pinhole. Image Credits: Metalenz

The first challenge is more or less contained in the fact that incoming light, without lenses to bend and direct it, hits the metasurface in a much more chaotic way. Devlin’s own PhD work was concerned with taming this chaos.

“Light on a macro [i.e. conventional scale, not close-focusing] lens is controlled on the macro scale, you’re relying on the curvature to bend the light. There’s only so much you can do with it,” he explained. “But here you have features a thousand times smaller than a human hair, which gives us very fine control over the light that hits the lens.”

Those features, as you can see in this extreme close-up of the metasurface, are precisely tuned cylinders, “almost like little nano-scale Coke cans,” Devlin suggested. Like other metamaterials, these structures, far smaller than a visible or near-infrared light ray’s wavelength, manipulate the radiation by means that take a few years of study to understand.

Diagram showing chips being manufactured, then an extreme close up showing nano-scale features.

Image Credits: Metalenz

The result is a camera with extremely small proportions and vastly less complexity than the compact camera stacks found in consumer and industrial devices. To be clear, Metalenz isn’t looking to replace the main camera on your iPhone — for conventional photography purposes the conventional lens and sensor are still the way to go. But there are other applications that play to the chip-style lens’s strengths.

Something like the FaceID assembly, for instance, presents an opportunity. “That module is a very complex one for the cell phone world — it’s almost like a Rube Goldberg machine,” said Devlin. Likewise the miniature lidar sensor.

At this scale, the priorities are different, and by subtracting the lens from the equation the amount of light that reaches the sensor is significantly increased. That means it can potentially be smaller in every dimension while performing better and drawing less power.

Image (of a very small test board) from a traditional camera, left, and metasurface camera, right. Beyond the vignetting it’s not really easy to tell what’s different, which is kind of the point. Image Credits: Metalenz

Lest you think this is still a lab-bound “wouldn’t it be nice if” type device, Metalenz is well on its way to commercial availability. The $10 million Series A they just raised was led by 3M Ventures, Applied Ventures LLC, Intel Capital, M Ventures and TDK Ventures, along with Tsingyuan Ventures and Braemar Energy Ventures — a lot of suppliers in there.

Unlike many other hardware startups, Metalenz isn’t starting with a short run of boutique demo devices but going big out of the gate.

“Because we’re using traditional fabrication techniques, it allows us to scale really quickly. We’re not building factories or foundries, we don’t have to raise hundreds of mils; we can use what’s already there,” said Devlin. “But it means we have to look at applications that are high volume. We need the units to be in that tens of millions range for our foundry partners to see it making sense.”

Although Devlin declined to get specific, he did say that their first partner is “active in 3D sensing” and that a consumer device, though not a phone, would be shipping with Metalenz cameras in early 2022 — and later in 2022 will see a phone-based solution shipping as well.

In other words, while Metalenz is indeed a startup just coming out of stealth and raising its A round… it already has shipments planned on the order of tens of millions. The $10 million isn’t a bridge to commercial viability but short-term cash to hire and cover upfront costs associated with such a serious endeavor. It’s doubtful anyone on that list of investors harbors any serious doubts on ROI.

The 3D sensing thing is Metalenz’s first major application, but the company is already working on others. The potential to reduce complex lab equipment to handheld electronics that can be fielded easily is one, and improving the benchtop versions of tools with more light-gathering ability or quicker operation is another.

Though a device you use may in a few years have a Metalenz component in it, it’s likely you won’t know — the phone manufacturer will probably take all the credit for the improved performance or slimmer form factor. Nevertheless, it may show up in teardowns and bills of material, at which point you’ll know this particular university spin-out has made it to the big leagues.

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Pat Gelsinger stepping down as VMware CEO to replace Bob Swan at Intel

In a move that could have wide ramifications across the tech landscape, Intel announced that VMware CEO Pat Gelsinger would be replacing interim CEO Bob Swan at Intel on February 15th. The question is why would he leave his job to run a struggling chip giant.

The bottom line is he has a long history with Intel, working with some of the biggest names in chip industry lore before he joined VMware in 2009. It has to be a thrill for him to go back to his roots and try to jump start the company.

“I was 18 years old when I joined Intel, fresh out of the Lincoln Technical Institute. Over the next 30 years of my tenure at Intel, I had the honor to be mentored at the feet of Grove, Noyce and Moore,” Gelsinger wrote in a blog post announcing his new position.

Certainly Intel recognized that the history and that Gelsinger’s deep executive experience should help as the company attempts to compete in an increasingly aggressive chip industry landscape. “Pat is a proven technology leader with a distinguished track record of innovation, talent development, and a deep knowledge of Intel. He will continue a values-based cultural leadership approach with a hyper focus on operational execution,” Omar Ishrak, independent chairman of the Intel board, said in a statement.

But Gelsinger is walking into a bit of a mess. As my colleague Danny Crichton wrote in his year-end review of the chip industry last month, Intel is far behind its competitors, and it’s going to be tough to play catch-up:

Intel has made numerous strategic blunders in the past two decades, most notably completely missing out on the smartphone revolution and also the custom silicon market that has come to prominence in recent years. It’s also just generally fallen behind in chip fabrication, an area it once dominated and is now behind Taiwan-based TSMC, Crichton wrote.

Patrick Moorhead, founder and principal analyst at Moor Insights & Strategy, agrees with this assertion, saying that Swan was dealt a bad hand, walking in to clean up a mess that has years long timelines. While Gelsinger faces similar issues, Moorhead thinks he can refocus the company. “I am not foreseeing any major strategic changes with Gelsinger, but I do expect him to focus on the company’s engineering culture and get it back to an execution culture,” Moorhead told me.

The announcement comes against the backdrop of massive chip industry consolidation last year with over $100 billion changing hands in four deals, with Nvidia nabbing ARM for $40 billion, the $35 billion AMD-Xilink deal, Analog snagging Maxim for $21 billion and Marvell grabbing Inphi for a mere $10 billion, not to mention Intel dumping its memory unit to SK Hynix for $9 billion.

As for VMware, it has to find a new CEO now. As Moorhead says, the obvious choice would be current COO Sanjay Poonen, but for the time being, it will be CFO Zane Rowe serving as interim CEO, rather than Poonen. In fact, it appears that the company will be casting a wider net than internal options. The official announcement states, “VMware’s Board of Directors is initiating a global executive search process to name a permanent CEO…”

Holger Mueller, an analyst at Constellation Research, says it will be up to Michael Dell to decide who to hand the reins to, but he believes Gelsinger was stuck at Dell and would not get a broader role, so he left.

“VMware has a deep bench, but it will be up to Michael Dell to get a CEO who can innovate on the software side and keep the unique DNA of VMware inside the Dell portfolio going strong, Dell needs the deeper profits of this business for its turnaround,” he said.

The stock market seems to like the move for Intel, with the company stock up 7.26%, but not so much for VMware, whose stock was down close to the same amount at 7.72% as we went to publication.

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The big question on every startup’s mind for 2021

My big question for 2021, and the one that is on every startup’s mind, is how will a cataclysmic event such as a global pandemic show up in post-pandemic innovation? I think we’re in the early innings of seeing what “aha moments” have materialized into companies. And we won’t know the pandemic’s true impact on our psyches until the dust settles and we have an opportunity to reflect.

We do know it will be fascinating to watch. In 2020, innovators and investors were forced to stand still, and witness cracks, fractures and rubble in society in a way like never before. It was a humbling year that, for much of the tech community, was mostly spent inside, away and alone.

One reaction I’ve noticed so far — that isn’t necessarily new but comes with new weight — is a rush of innovation that focuses on reducing friction. Take trends like the rise of building in public or the unbundling of venture capital. Or remote work’s shift from enabling communication to now needing to enable passive and active collaboration. Apply the same idea to mental health, education and fitness. Heck, we’re even seeing people take the Y Combinator format and apply it to anything that makes sense, from helping operators turn into investors to helping employees try to turn their side gig into a full-time company.

While these movements didn’t begin because of the coronavirus, they all seem to have a huge, pandemic-sized asterisk next to it.

It would be easy to dismiss these movements as small and inconsequential. But, as my colleague and fellow Equity co-host Danny Crichton pointed out this week, “sometimes the most important changes in venture and startups more generally have come from lowering that last bit of friction to action.”

Lowering friction feels like the mantra with which we all need to enter 2021.

I already have hope that innovation will come from a more diverse set of people, whether it’s in a hacker house for undergraduate women or a student-founded service that matches undergraduate students to nonprofits. So, as we enter the new year — and bear with me here — I urge you to be optimistic.

The last year in tech hasn’t left people exhausted and hopeless, it’s left them energized and ready.

Maze, computer artwork. (Image Credits: Pasieka / Getty Images)

Will the second time be the charm for Qualtrics?

When SAP announced that Qualtrics was getting spun out in July, the full-circle moment made the Equity podcast crew jump to our mics with guesses around why. Now, months later, there’s a new S-1 filing, and more to color in. Alex Wilhelm broke down the Utah-based unicorn’s numbers, noting that it’s the second time Qualtrics has filed.

Will the second time be the charm that Qualtrics needs to actually go public this time around? I’ll let you make the call yourself once you sift through Alex’s analysis of the valuation and financials.

Blackboard Business Strategy Concept. (Image Credits: hanibaram / Getty Images)

Miami, Substack and Clubhouse

If those three words in a single subhed elicit a certain reaction from you, Danny Crichton has a bone to pick with you. He wrote a piece this week about tech’s cynicism around anything new, underscoring how Miami’s future as a tech hub, Substack’s future as a replacement for traditional journalism and Clubhouse’s future as a social media disruptor have come under fire as expected:

The cynicism of immediate perfection is one of the strange dynamics of startups in 2020. There is this expectation that a startup, with one or a few founders and a couple of employees, is somehow going to build a perfect product on day one that mitigates any potential problem even before it becomes one. Maybe these startups are just getting popularized too early, and the people who understand early product are getting subsumed by the wider masses who don’t understand the evolution of products?

Danny’s argument is to give these companies a little more grace to execute on a vision they themselves are not even close to scratching the surface of. When it comes to holding specific decision-makers and businesses to a certain standard, I prefer a more fluid conversation. But I do agree that writing off a business because it hasn’t done everything correctly from the start can hurt progress. It’s easy to be grumpy, but why not choose to be an optimist? Tell me your optimistic bets by responding to this newsletter or tweeting me @nmasc_.

Skyline of downtown Miami, Florida looking toward the Brickell neighborhood on Biscayne Bay. Brickell is one of the largest financial districts in the United States and also has many high-rise residential condominium and apartment towers. (Image Credits: John Coletti / Getty Images)

And some good news

Speaking of humbling moments and optimism, our own Sarah Perez wrote a piece this week about EarlyBird, an app that lets families and friends gift investments to children. While Acorns and Stash have similar offerings, EarlyBird is bringing a fresh UX play to financial literacy, freedom and education. There’s a ton of work left to be done, hurdles to deal with, and giant unicorns to compete with. EarlyBird, however, is only weeks old, so there’s much to watch out for.

VP Caleb Frankel, now EarlyBird COO, explained the early inspiration:

“This all started with a problem I experienced years ago when my beautiful baby niece was born. I found myself head over heels and spending hundreds and hundreds of dollars on just the most ridiculous stuff — pretty much just junk gifts,” he says. “I wanted to have a larger impact in her life and something that she could really use when she grew up.”

Crowdfunding Concept Investment into Idea or Business Startup

Image Credits: oxygen (opens in a new window) / Getty Images

Around TechCrunch

Attending CES 2021? TechCrunch wants to meet your startup

Gift Guide: Last-minute subscriptions to keep the gifts going all year

Across the week

Seen on Extra Crunch

How artificial intelligence will be used in 2021

On the diversity front, 2020 may prove a tipping point

The 2020 boom in climate tech SPACs

2021 will be a calmer year for semiconductors and chips (except for Intel)

Understanding Europe’s big push to rewrite the digital rulebook

Seen on TechCrunch

China lays out ‘rectification’ plan for Jack Ma’s fintech empire Ant

NSO used real people’s location data to pitch its contact-tracing tech, researchers say

India’s slow 2020 told through dollars and cents

An earnest review of a robotic cat pillow

@EquityPod

The Equity pod put together a 2021 predictions episode (with Chris Gates, our producer, making a guest appearance on the mic as well!). We talk about IPO candidates, San Francisco and the future of drugs.

2020 brought several million downloads to the podcast, and we’re super thankful to all of y’ all for tuning in. This year will be even bigger, better and, hey, maybe we’ll even get to make fun of each other in person too.

Till next week,

Natasha Mascarenhas

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Intel has acquired Cnvrg.io, a platform to manage, build and automate machine learning

Intel continues to snap up startups to build out its machine learning and AI operations. In the latest move, TechCrunch has learned that the chip giant has acquired Cnvrg.io, an Israeli company that has built and operates a platform for data scientists to build and run machine learning models, which can be used to train and track multiple models and run comparisons on them, build recommendations and more.

Intel confirmed the acquisition to us with a short note. “We can confirm that we have acquired Cnvrg,” a spokesperson said. “Cnvrg will be an independent Intel company and will continue to serve its existing and future customers.” Those customers include Lightricks, ST Unitas and Playtika.

Intel is not disclosing any financial terms of the deal, nor who from the startup will join Intel. Cnvrg, co-founded by Yochay Ettun (CEO) and Leah Forkosh Kolben, had raised $8 million from investors that include Hanaco Venture Capital and Jerusalem Venture Partners and PitchBook estimates that it was valued at around $17 million in its last round. 

It was only a week ago that Intel made another acquisition to boost its AI business, also in the area of machine learning modeling: it picked up SigOpt, which had developed an optimization platform to run machine learning modeling and simulations.

While SigOpt is based out of the Bay Area, Cnvrg is in Israel and joins an extensive footprint that Intel has built in the country specifically in the area of artificial intelligence research and development, banked around its Mobileye autonomous vehicle business (which it acquired for more than $15 billion in 2017) and its acquisition of AI chipmaker Habana (which it acquired for $2 billion at the end of 2019).

Cnvrg.io’s platform works across on-premise, cloud and hybrid environments and it comes in paid and free tiers (we covered the launch of the free service, branded Core, last year). It competes with the likes of Databricks, Sagemaker and Dataiku as well as smaller operations like H2O.ai that are built on open source frameworks.

While Intel is not saying much about the deal, it seems that some of the same logic behind last week’s SigOpt acquisition applies here as well: Intel has been refocusing its business around next-generation chips to better compete against the likes of Nvidia and smaller players like GraphCore. So it makes sense to also provide/invest in AI tools for customers, specifically services to help with the compute loads that they will be running on those chips.

It’s notable that in our article about the Core free tier last year, Frederic noted that those using the platform in the cloud can do so with Nvidia-optimized containers that run on a Kubernetes cluster. It’s not clear if that will continue to be the case, or if containers will be optimized instead for Intel architecture, or both. Cnvrg’s other partners include Red Hat and NetApp.

Intel’s focus on the next generation of computing aims to offset declines in its legacy operations. In the last quarter, Intel reported a 3% decline in its revenues, led by a drop in its data center business. It said that it’s projecting the AI silicon market to be bigger than $25 billion by 2024, with AI silicon in the data center to be greater than $10 billion in that period.

In 2019, Intel reported some $3.8 billion in AI-driven revenue, but it hopes that tools like SigOpt’s will help drive more activity in that business, dovetailing with the push for more AI applications in a wider range of businesses.

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AWS launches its next-gen GPU instances

AWS today announced the launch of its newest GPU-equipped instances. Dubbed P4, these new instances are launching a decade after AWS launched its first set of Cluster GPU instances. This new generation is powered by Intel Cascade Lake processors and eight of Nvidia’s A100 Tensor Core GPUs. These instances, AWS promises, offer up to 2.5x the deep learning performance of the previous generation — and training a comparable model should be about 60% cheaper with these new instances.

Image Credits: AWS

For now, there is only one size available, the p4d.12xlarge instance, in AWS slang, and the eight A100 GPUs are connected over Nvidia’s NVLink communication interface and offer support for the company’s GPUDirect interface as well.

With 320 GB of high-bandwidth GPU memory and 400 Gbps networking, this is obviously a very powerful machine. Add to that the 96 CPU cores, 1.1 TB of system memory and 8 TB of SSD storage and it’s maybe no surprise that the on-demand price is $32.77 per hour (though that price goes down to less than $20/hour for one-year reserved instances and $11.57 for three-year reserved instances.

Image Credits: AWS

On the extreme end, you can combine 4,000 or more GPUs into an EC2 UltraCluster, as AWS calls these machines, for high-performance computing workloads at what is essentially a supercomputer-scale machine. Given the price, you’re not likely to spin up one of these clusters to train your model for your toy app anytime soon, but AWS has already been working with a number of enterprise customers to test these instances and clusters, including Toyota Research Institute, GE Healthcare and Aon.

“At [Toyota Research Institute], we’re working to build a future where everyone has the freedom to move,” said Mike Garrison, Technical Lead, Infrastructure Engineering at TRI. “The previous generation P3 instances helped us reduce our time to train machine learning models from days to hours and we are looking forward to utilizing P4d instances, as the additional GPU memory and more efficient float formats will allow our machine learning team to train with more complex models at an even faster speed.”

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