This post is curated by Keith Teare. It was written by Mike Dudas (@mdudas). The original is [linked here]
Semil (@semil) retweeted:
– Mike Dudas (@mdudas)20:00 – 2020/09/18
Government to ban WeChat on Sunday to ‘safeguard national security of the US’, while TikTok to be banned by 12 November
The US government will ban downloads of the Chinese-owned video sharing app TikTok and the use of China’s popular messaging and payments app WeChat to “safeguard the national security of the United States”.
Oper8r is focused on enabling the next generation of great founders in VC by empowering the next generation of great emerging micro-VCs that fund them.
Rolling funds could bring new investors and sources of capital into the ecosystem, while giving LPs some control over the timing of their commitments to VC
The way rolling funds are structured, they may challenge the long-term nature of VC as an asset class, which could create misalignment for VCs, LPs, and founders
Rolling funds downplay investment concepts that could lead to VC outperformance, such as longer-term meaningful ownership, power-law investing, portfolio construction, and encourages stock picking versus relationship building
From a mechanics and cost perspective, rolling funds are not radically different from traditional funds, given VCs can already hold multiple closes with traditional structure, and rolling funds are not much cheaper to start
Rolling funds can empower a more diverse group of future GPs who otherwise might now have had the opportunity to invest, but are still restricted to accredited investors investing in other accredited investors
Our goal at Oper8r is to empower emerging VCs and bring more credibility and transparency to early-stage VC where we think there is a consistently large opportunity for founders to get great GP partners and LPs to invest in hungry and unique GPs. We are pro-VC and pro-innovation. We strive to make VC better overall, for founders, GPs, and LPs. In particular, we believe in developing products and platforms that enable alignment across founders, GPs, and LPs by improving process, information flow, and transparency.
Some context: I want to make it clear that I applaud the AngelList team for continuing to expand the boundaries of the VC industry, creating opportunities for new innovators and investors to enter the market. Building on an opportunity presented by the Jumpstart Our Business Startups (JOBS) Act of 2012, AngelList introduced its rolling funds product, which rolled out in Beta earlier this year, and more recently was announced through a larger public effort. I see these efforts as largely positive, leveraging technology to drive innovation in the VC market. But I also want to share my view on how this product fits in the current VC ecosystem of founders, GPs, and LPs.
Why I like the rolling funds concept:
Brings more capital to innovation. Few investment platforms are capitalizing on Rule 506(c) of Regulation D, which had an intention to help finance more startups. In 2019 alone, AngelList enabled the financing of over 1,600 startups, and AngelList pushing the boundaries through rolling funds should enable more financing of early-stage start-ups.
Empowers new VCs. Currently, the expectation is that rolling funds will attract more operator-angels and those with large media followings to enter the business of VC.
Enables more diversity in VC. Women and people of color can leverage the structure to raise VC funds, which may have a great economic benefit of bringing capital to opportunities traditionally underserved by VC. (More discussed here to this point by Minal Hasan.)
Gives more discretion to the LP over liquidity profile and commitment. The traditional VC fund structure locks up the LP’s capital for a minimum of 10 years; with rolling funds, LPs would now have the option to invest into VC with a shorter duration, which may give some LPs who are concerned about illiquidity more comfort. (As an aside, an active secondary market providing liquidity to early-stage VCs could also fill this role.)
Facilitates fundraising for long-tail LP’s by being a good channel for LP discovery, especially since rolling funds can be broadly solicited and generally advertised. (Although there may still be a limit on how many LPs you can take in as LPs into your fund by law. See here for an indication of where these VC funds may hit a regulatory wall.)
Promotes accountability of VCs by measuring performance on a quarterly basis. If VCs have to answer their investors every quarter, it will be much more clear who is and who isn’t performing, which may help the “market” figure out earlier who has the Midas touch.
Why I find the rolling funds concept problematic and wanting:
Makes VCs and LPs measure performance on a quarterly basis, which is at odds with the reality of how long it takes to build a great company. Throwing away the traditional VC lock-up period may affect how VC is viewed as a long-term oriented business that should have a longer lock-up period to allow companies time to grow. It is to be determined how this structure could further drive short-termism in VC.
Because VCs can already hold multiple closes with a traditional VC fund structure, rolling funds are not radically different than what already exists. From what I have experienced, most emerging VCs raising traditional funds already have multiple closes during a fundraising process.
Because LPs already make relatively short-term decisions on whether to re-up (about every 2 years), rolling funds are not radically different than what already exists. In the current market, VCs raise traditional funds about every 2 years, so LPs are already making decisions to invest on a short-term basis (even if their capital gets committed for a long-term duration).
If VCs have to ask for commitment/re-commitments on a quarterly basis, this could make the relationship between the VC and LP more transactional, and less focused on first finding alignment on long-term investment objectives. If the VC and LP are not engaging, building trust, and finding alignment, does this actually help the VC scale over time?
Causes the LP to potentially miss the power law dynamics of VC that usually create returns at the fund level, which could negatively impact LP performance. If LPs are new to the asset class, and don’t understand VC assets, then rolling funds may drive LPs to buy high or sell low. This is not aligned with LPs’ objective to access VC to achieve outperformance in their portfolios.
Never creates a forcing function for LPs to commit to VCs in the fundraising process. On the one hand, rolling funds let an LP invest (or withdraw funds) on a quarterly basis. On the other hand, this could mean the LP is never forced to make a decision because another decision point is only a quarter away. In traditional VC funds, LPs are forced into making a decision when the fund is open. If the LP does not commit during that fundraising period, then the LP can’t invest at the original cost-basis. If larger investors, mainly institutional LPs, are not being forced into a commitment decision and initial funds are already being financed by friends and family with the traditional structure, then it’s not clear why this structure truly changes the current market dynamics.
May create conflicts between LPs who commit in different time periods. As the VC, which LPs are you serving if you are closing a new fund creating different LP bases every quarter? VCs should be aware about potential conflicts of interest with respect to access, terms, and timing of deals.
Is another fund product that strays away from optimizing performance for the LP. If returns are calculated on a quarterly basis, this could create misalignment, similar to how an AngelList syndicate may misalign incentives, because absolute performance is generated on a short-term oriented vehicle, versus a long-term oriented vehicle where the VC has to manage the long-term success of the fund.
May downplay decision-making frameworks for making new investments. My view is that pattern recognition and experience developed over time based on a long-term understanding of successes and failures can contribute to good investment decisions. If rolling funds do not attract this type of investor, then while it should enable deployment of more capital, it does not necessarily provide the long-term partners VC-backed entrepreneurs are looking for as they scale their businesses.
May make being a VC a part-time business. If you are investing part-time, for example, because you are running another business full-time, this may mean that the companies being financed do not get the attention they require. Full-time VCs, on the other hand, provide capital, as well as platforms to help their portfolio companies (the performance of these platforms can be debated in another post). While it’s cool to be a VC (so they say in Europe), being part-time may erode some investment lessons that could prevent costly errors in the long-run (presuming VC is an apprenticeship business)
Rolling funds focus on making raising capital easy for VCs, and not about managing risk or enhancing LP returns. While rolling funds have an intention to “democratize access to VC”, enabling less well-versed LPs to invest in the highest risk assets in VC may not be the best long-term for the VC industry if too many LP’s are negatively impacted through this structure.
Rolling funds ignore the important concept of portfolio construction, which is a valuable exercise for fund managers, especially as it relates to reserves and liquidity management. Is this necessarily a bad thing for a first-time fund? Well, that depends if you think follow-on dollars and protecting equity dilution is a good thing. Or if you’ll need capital for that pay-to-play provision down the line.
According to the fine print that I’ve seen, as an LP, you can still cancel your “subscription” to the fund at any time, which may not be favorable for a VC trying to build a long-term business. Again, this seems to potentially disadvantage VCs who will have to dedicate time to fundraising, but the slightest mis-step or psychological change of the LP may lead to cancelled subscriptions.
From what I can tell, the cost structure of running the fund does not change for the VC starting a rolling fund. For rolling funds, AngelList charges VCs three times: fund administration fees, entity structure fees, and carry if they help you secure LPs.
There’s still a glass ceiling when it comes to rolling funds enabling more diversity in VC, given the exemption that rolling funds fall under requires that they are led by accredited investors marketing to other accredited investors, which is less than 10% of U.S. households. Effectively if you don’t have a high salary or $1 million (excluding your house) in the bank, this may prevent certain groups from still accessing LP dollars.
Making Change at Scale. At the SaaStr Annual event (held virtually this year) Greylock general partners David Wadhwani and Sarah Guo discussed the key elements to successfully navigating operational phase shifts, which David has experienced numerous times over the course of his two-decade career as a software executive at companies such as AppDynamics and Adobe. David detailed 5 things every company and founder should do to navigate phase shifts successfully, illustrated by examples of how they played out during his own experience. (Greymatter)
Greylock Fund 16. We announced Greylock 16 — a billion dollar fund. With Fund 16, we will continue our focus on early stage investing. While we primarily invest in enterprise and consumer software at Seed and Series A, the size of our fund gives us the flexibility to make new company investments in Series B and beyond including growth stages. Our fund size also allows us to support companies as a primary/lead investor through company journeys. In our most recent fund, 75% of investments made were seed or series A, and the rest were in series B and beyond. Notably, 10% of the companies we backed in our last fund started up right in our offices. (Bloomberg, Blog)
Sumo Logic IPO. Congrats the entire Sumo Logic team on their IPO (Nasdaq: SUMO). Over the past decade, Sumo has established itself as the leader in continuous intelligence. With a cloud-native platform, Sumo has redefined the scale, elasticity and reliability of security, business and operational intelligence. Greylock partners Joseph Ansanelli and Asheem Chandna write about the journey from idea to IPO — and shared the company’s first seed deck. (Blog)
Abnormal Security partners with Microsoft. Abnormal Security will move its software onto the tech giant’s Azure cloud. Microsoft, in return, promises to sell Abnormal’s services to its large enterprise clients, which Microsoft says is its first such arrangement. (WSJ)
Greylock-backed companies are looking for amazing talent. Check out our jobs page for all the available roles. Our core talent team is always looking to connect with engineers, product managers, and designers who are thinking about exploring early stage start-up as a next move in their career. Reach out: CoreTalent@greylock.com
Hello from the midst of Disrupt 2020: after this short piece for you I am wrapping my prep for a panel with investors from Bessemer, a16z and Canaan about the future of SaaS. Luckily, The Exchange this morning is on a very similar topic.
Today we’re parsing some data that Bessemer and Forbes shared regarding their yearly Cloud 100 list. It’s a grouping of private cloud and SaaS companies, giving us a good look into valuation trends over time and also where the most valuable startups are focusing their efforts.
The data show a changing focus from the biggest and most impressive private SaaS and cloud companies. And the valuation trends show how growing private valuations could limit future returns, given historical results.
Of course, modern cloud valuations make it hard to be bearish on SaaS revenue multiples, but all the same, how much higher can they go? Every startup looks cheap when money is cheap. Let’s get into the numbers.
The Cloud 100 cycles companies in and out as time passes. As the list is focused on private companies, cloud and SaaS firms that sell to another company or go public leave the cohort. And new companies join, keeping the total group at precisely 100 companies.
Here are the top five sectors those 100 companies are focused on, in order of popularity:
Follow me @samirkaji for my thoughts on the venture market, with a focus on the continued growth with the emerging manager landscape
Recently, AngelList’s Rolling Fund product has been a frequent topic of discussion within early-stage investing circles. Over the last few weeks, I’ve had dozens of conversations with LP’s and GP’s to get their thoughts on the product.
There have also been some great Rolling Fund articles; Minal Hassan wrote a great early summary here, and Winter Mead penned a very thoughtful and balanced piece from an LP’s perspective in weighing the pros and cons from his perspective.
Before I provide a few of my thoughts on Rolling Funds, here are a couple of refresher points.
– The Rolling Fund product is an evergreen master series LP structure, where each quarter represents a separate “cell”. Less marketed but currently also available, is a traditional venture fund set up through the AngelList platform. For this post, I’m primarily focusing on the former.
– Rolling Fund managers raise funds using the 506(c) provision of the JOBS Act, enabling general solicitation for private securities offerings.
Can Rolling Funds scale? Right now, the clear product-market fit for Rolling Funds is proof of concept funds or those that are part-time investors (both of which place the most value on speed and convenience). Can Rolling Funds become a product used by investors looking to raise larger, institutionally run firms? I think a few things will need to be fleshed out, notably:
Having covered emerging venture for the past ten years (and venture as a whole for 20+), I think this is an enormous innovation for the industry. And while I believe there are some “bugs” that give credence to some very well placed concerns relating to potential GP/LP areas of economic misalignment, many of these (and others) are also present in traditional venture capital. I’m personally excited to see how this product evolves over time.
I have written extensively on this blog over the last decade and a half about the significant negative consequences that the two large mobile operating systems have on distribution of software. I am strongly opposed to the monopolies that Apple and Google have over mobile apps that run on iOS and Android.
I am rooting for Epic/Fortnite in their battle with Apple over the 30% tax that Apple charges developers for distribution in their app store. But more than the tax, what bothers me about these monopolies is the innovation tax they impose on the broad tech sector with their terms of service/rules.
There is no better place to see that than crypto, the next big wave in computing (after web and mobile). There are a number of reasons that decentralized crypto apps (dapps) have not gone mainstream, but certainly one of them is that the Apple and Google app stores don’t allow a number of important features that decentralized apps require.
The founder and CEO of our portfolio company Coinbase, Brian Armstrong, explained this well in a tweetstorm last week:
He ended with this tweet:
Recently Apple announced a way for developers to suggest updates to the App Store policies. Our team is planning to submit a formal request for Apple to allow its users to earn crypto and see a list of decentralized finance apps. We’ll keep you updated on what we hear back.
— Brian Armstrong (@brian_armstrong) September 11, 2020
Coinbase, Epic, and Spotify are not alone in their struggles with Apple and Google. They are simply large enough and protected enough to go public with their struggles. The truth is every developer that distributes software through these two app stores struggles with them.
In what world does it makes sense for two large and powerful companies to completely control software distribution on mobile phones? In no world does it make sense. It must stop.
USV TEAM POSTS: Hanel Baveja — Sep 10, 2020
Mental Healthcare 3.0 Part 2
Playing with unicorns is a new weekly live streaming show on startups, entrepreneurship, and venture capital. I will be streaming every Thursday at 12 pm EST on LinkedIn, Facebook, YouTube, Twitter, and Twitch. I will post the video to YouTube after each episode and the audio to the podcast section of Spotify and iTunes. I will also post every episode on my blog.
I was asked to create a live streaming show and podcast many times over the last few years, but I was not inspired. Almost every show has a host interviewing amazing guests, with the same guests making the rounds on every show in their category. I did not want to be redundant with those efforts. On top of that, running FJ Labs is all encompassing. I did not feel I would have the time to put together an amazing roster and do a great job.
Instead, as readers of my blog probably noticed, I became a guest on a wide range of podcasts and live streaming shows. It was fun and interesting, but with enough experience I realized that what was missing was a distilled version of the content. This was reinforced by the fact that most entrepreneurs and aspiring entrepreneurs I meet have a common set of questions that I find myself answering repeatedly: how to fundraise, how VCs evaluate startups, how to come up with a good startup idea etc.
As a result, I thought it would be most valuable to cover a specific topic every week. I will share my perspective before opening it up to questions from the audience. This is not to say I will not have guests on the show, but when I do, it will mostly be for them to present something practical (e.g. how to test customer acquisition channels for a pre-launch idea to estimate customer acquisition cost), rather than a traditional interview where they share their story.
The objective of this show is not to be mass market, but to help Internet entrepreneurs understand how to build scalable venture backed startups. I will try to be educational, even for those with limited experience in the startup world, when covering broader concepts like fundraising. However, I will also be more technical and detail oriented when doing deep dives on specific topics like “the future of food”, “how to match supply and demand in marketplaces” or “how to decide which business model to pick.”
To have diversity in the content offering, I imagine that some weeks I will host “ask me anything” sessions, organize quick pitches that I react to, or just comment on happenings in the tech sector. I will also cover topics and ideas suggested by viewers. If some entrepreneurs are up for it, I would love to stream a company evaluation where I assess one of the startups pitching FJ Labs for funding.
I expect the show duration to vary between 10 minutes and 1 hour. Note that this is unscripted, unedited, and self-produced, so do not expect high production values with jazzy effects. Instead, I will focus on providing valuable information to startup founders.
I do not know how many episodes I will end up creating, but this should be a fun experiment and I cannot wait to see what comes of it. The first episode is Thursday, September 17 at 12 pm EST. I will cover fundraising.
In the meantime, enjoy in introduction video for the show.
Amid the uncertainty brought about by COVID-19, data from @Upwork’s #FreelanceForward report shows that independent professionals are benefiting from income diversification, schedule flexibility, and increased productivity. See the full report: https://t.co/tQeEgl6Fya pic.twitter.com/1m168O1Yse
— Hayden Brown (@hydnbrwn) September 15, 2020
Bill Gurley (@bgurley) retweeted:
Amid the uncertainty brought about by COVID-19, data from @Upwork’s #FreelanceForward report shows that independent professionals are benefiting from income diversification, schedule flexibility, and increased productivity. See the full report: upwork.com/i/freelance-fo… pic.twitter.com/1m168O1Yse
– Hayden Brown (@hydnbrwn)07:24 – 2020/09/15
Back in 2010, Kyle Conroy wrote a blogpost entitled, What if I had bought Apple stock instead?:
Currently, Apple’s stock is at an all time high. A share today is worth over 40 times its value seven years ago. So, how much would you have today if you purchased stock instead of an Apple product? See for yourself in the table below.
Conroy kept the post up-to-date until April 1, 2012; at that point, my first Apple computer, a 2003 12″ iBook, which cost $1,099 on October 22, 2003, would have been worth $57,900. Today it would be worth $311,973.
I thought of this meme, which pops up every time Apple’s stock hits a new all-time high, while considering the price Apple paid for P.A. Semi back in 2008; for a mere $278 million the company acquired the talent and IP foundation that would undergird its A-series of chips, which have powered every iPad and every iPhone since 2010, and, before the end of the year, at least one Mac (the rest of the line will follow within two years).
So I was curious: what would $278 million in 2008 Apple stock look like today? The answer is $5.5 billion, which, honestly, is still an absolute bargain, and a reminder that the size of an acquisition is not necessarily correlated with its impact.
Over the weekend Nvidia consummated the biggest chip deal in history when it acquired Arm1 from Softbank for around $40 billion in stock and cash. Nvidia founder and CEO Jensen Huang wrote in a letter to Nvidia employees:
We are joining arms with Arm to create the leading computing company for the age of AI. AI is the most powerful technology force of our time. Learning from data, AI supercomputers can write software no human can. Amazingly, AI software can perceive its environment, infer the best plan, and act intelligently. This new form of software will expand computing to every corner of the globe. Someday, trillions of computers running AI will create a new internet — the internet-of-things — thousands of times bigger than today’s internet-of-people. Uniting NVIDIA’s AI computing with the vast reach of Arm’s CPU, we will engage the giant AI opportunity ahead and advance computing from the cloud, smartphones, PCs, self-driving cars, robotics, 5G, and IoT.
These are big ambitions for a big purchase, and Wall Street apparently agrees; yesterday Nvidia’s market cap increased by $17.5 billion, nearly covering the $21.5 billion in shares Nvidia will give Softbank in the deal. Indeed, it is Nvidia’s stock that is probably the single most important factor in this deal. Back in 2016, when Softbank acquired Arm, Nvidia was worth about $34 billion; after yesterday’s run-up, the company’s marketcap was $318 billion.
The first takeaway is that selling Arm for $32 billion means that the company was yet another terrible investment by Softbank; simply buying Nvidia shares — or, for that matter, an S&P 500 index fund, which is up 55% since then — would have provided a much better return than the ~5% Softbank earned from Arm.
The second takeaway is the inverse: Nvidia is acquiring a company that was its marketcap peer four years ago for a relative pittance. Granted, Nvidia’s stock may not stay at its current lofty height — the company has a price-to-earnings ratio of over 67, well above the industry average of 27 — but that is precisely why a majority-stock acquisition makes sense; Nvidia’s stock may retreat, but Arm will still be theirs.
Beginning my analysis with stock prices is not normally what I do; I’m generally more concerned with the strategies and business models of which stock price is a result, not a driver. The truth, though, is that once you start digging into the details of Nvidia and ARM, it is rather difficult to see what strategy might be driving this acquisition.
Start with Nvidia: the company is perhaps the shining example of the industry transformation wrought by TSMC; freed of the need to manufacture its own chips, Nvidia was focused from the beginning on graphics. Its TNT cards, released in the late 1990s, provided 3D graphics for games while also powering Windows (previously hardware 3D graphics were only available via add-on cards); its GeForce line, released in 1999, put Nvidia firmly at the forefront of the industry, a position it retains today.
It was in 2001 that Nvidia released the GeForce 3, which had the first pixel shader; instead of a hard-coded GPU that could only execute a pre-defined list of commands, a shader was software, which meant it could be programmed on the fly. This increased level of abstraction meant the underlying graphics processing unit could be much simpler, which meant that a graphics chip could have many more of them. The most advanced versions of Nvidia’s just-announced GeForce RTX 30 Series, for example, has an incredible 10,496 cores.
This level of scalability makes sense for video cards because graphics processing is embarrassingly parallel: a screen can be divided up into an arbitrary number of sections, and each section computed individually, all at the same time. This means that performance scales horizontally, which is to say that every additional core increases performance.
It turns out, though, that graphics are not the only embarrassingly parallel problem in computing. Another obvious example is encryption: brute forcing a key entails running the exact same calculation over-and-over again; the chips doing the calculation don’t need to be complex, they simply need as many cores as possible (this is why graphics cards are very popular for blockchain applications; miners are basically endlessly brute-forcing encryption keys).
What is most enticing for Nvidia, though, is machine learning. Training on large datasets is an embarrassingly parallel problem, which means it is well-suited for graphics cards. The trick, though, is in decomposing a machine learning algorithm into pieces that can be run in parallel; graphics cards were designed for, well, graphics, which meant that programmers had to work in graphics programming languages like OpenGL.
This is why Nvidia transformed itself from a modular component maker to an integrated maker of hardware and software; the former were its video cards, and the latter was a platform called CUDA. The CUDA platform allows programmers to access the parallel processing power of Nvidia’s video cards via a wide number of languages, without needing to understand how to program graphics.
Here the kicker: CUDA is free, but that is because the integration is so tight. CUDA only works with Nvidia video cards, in large part because many of the routines are hand-tuned and optimized. It is a tremendous investment that has paid off in a major way: CUDA is dominant in machine learning, and Nvidia graphics cards cost hundreds of dollars ($1500 in the case of the aforementioned RTX 3090). Apple isn’t the only company that understands the power of differentiating premium hardware with software.
Arm’s business model could not be more different. The company, founded in 1990 as a joint venture between Acorn Computers, Apple, and VLSI Technology, doesn’t sell any chips of its own; rather, it licenses chip designs to companies which actually manufacture ARM chips. Except even that isn’t quite right: most ARM licensees actually contract with manufacturers like TSMC to make physical chips, which are then sold to OEMs. The entire ecosystem is extremely modular; consider an Oppo smartphone, with a MediaTek chip:
Arm chips appear in many more devices than smartphones — most micro-controllers in embedded systems are Arm designs — and Arm designs more than CPUs; the company’s catalog includes everything from GPUs to AI accelerator chips. It also licenses less than full designs: Apple, for example, designs its own chips, but uses the ARM Instruction Set Architecture (ISA) to communicate with them. The ARM ISA is the platform that ties this entire ecosystem together; programs written for one ARM chip will run on all ARM chips, and each of those chips results in a licensing fee for Arm.
What makes Arm’s privileged position viable is the same one that undergirds TSMC’s: neutrality. I wrote about the latter in Intel and the Danger of Integration:
In 1987, Morris Chang founded Taiwan Semiconductor Manufacturing Company (TSMC) promising “Integrity, commitment, innovation, and customer trust”. Integrity and customer trust referred to Chang’s commitment that TSMC would never compete with its customers with its own designs: the company would focus on nothing but manufacturing.
This was a completely novel idea: at that time all chip manufacturing was integrated a la Intel; the few firms that were only focused on chip design had to scrap for excess capacity at Integrated Device Manufacturers (IDMs) who were liable to steal designs and cut off production in favor of their own chips if demand rose. Now TSMC offered a much more attractive alternative, even if their manufacturing capabilities were behind.
In time, though, TSMC got better, in large part because it had no choice: soon its manufacturing capabilities were only one step behind industry standards, and within a decade had caught-up (although Intel remained ahead of everyone). Meanwhile, the fact that TSMC existed created the conditions for an explosion in “fabless” chip companies that focused on nothing but design.
For example, in the late 1990s there was an explosion in companies focused on dedicated graphics chips: nearly all of them were manufactured by TSMC. And, all along, the increased business let TSMC invest even more in its manufacturing capabilities.
That article was about TSMC overtaking Intel in fabrication, but a similar story can be told about Arm overtaking Intel in mobile. Intel was relentlessly focused on performance, but smartphones needed to balance performance with battery concerns. Arm, which had been spending years designing highly efficient processors for embedded applications, had both the experience and the business model flexibility to make mobile a priority.
The end result made everyone a winner (except Intel): nearly every smartphone in the world runs on an ARM-derived chip (either directly or, in the case of companies like Apple, the ARM ISA), which is to say that Arm makes money when everyone else in the mobile ecosystem makes money.
Notice that an ARM license, unlike the CUDA platform, is not free. That makes sense, though: CUDA is a complement to Nvidia’s proprietary graphics cards, which command huge margins. ARM license fees, on the other hand, can and are paid by everyone in the ecosystem, and in return everyone in the ecosystem gets equal access to Arm’s designs and ISA. It’s not free, but it is neutral.
That neutrality is gone under Nvidia ownership, at least in theory: now Nvidia has early access to ARM designs, and the ability to push changes in the ARM ISA; to put it another way, Nvidia is now a supplier for many of the companies it competes with, which is a particular problem given Nvidia’s reputation for both pushing up prices and being difficult to partner with. Here again Apple works as an analogy: the iPhone maker is notorious for holding the line on margins, prioritizing its own interests, and being litigious about intellectual property; Nvidia has the same sort of reputation. So does Intel, for that matter; the common characteristic is being vertically integrated.
Of course Nvidia is insistent that ARM licensees have nothing to worry about. Huang noted in that letter to Nvidia employees:
Arm’s business model is brilliant. We will maintain its open-licensing model and customer neutrality, serving customers in any industry, across the world, and further expand Arm’s IP licensing portfolio with NVIDIA’s world-leading GPU and AI technology.
Notice that last bit: Huang is not only arguing that Nvidia will serve Arm customers neutrally, but that Nvidia itself will adopt Arm’s business model, licensing its IP to competitive chip-makers. It’s as if this is an acquisition in reverse: the $318 billion acquirer is fitting itself into a world defined by its $40 billion acquisition.
Color me skeptical; not only is Nvidia’s entire business predicated on selling high margin chips differentiated by highly integrated software, but Nvidia’s entire approach to the market is about doing what is best for Nvidia, without much concern for partners or, frankly customers. It is a luxury afforded those that are clearly best in class, which by extension means that sharing is anathema; why trade high margins at the top of the market for low margins and the headache of serving everyone?
In short, this deal feels like the inverse of the P.A. Semi deal not simply in terms of the price tag, but in its overall impact on the acquirer. I have a hard time believing that Nvidia is going to change its approach.
Or maybe that’s the entire point.
By far the best articulation of the upside of this deal came, unsurprisingly, from Huang. What was notable about said articulation, though, was that it came 46 minutes into the investor call about the acquisition, and only then in response to a fairly obvious question: why does Nvidia need to own ARM, instead of simply license it (like Apple, which has a perpetual license to the ARM ISA, and is not affected by this acquisition)?
What was so striking about Huang’s answer was not simply its expansiveness — I’ve transcribed the entire answer below — but also the way in which he delivered it; unlike the rest of the call, Huang’s voice was halting and uncertain, as if he were scared of his own ambition. I know this excerpt is long, but it’s essential:
We were delightful licensees of ARM. As you know we used ARM in one of our most important new initiatives, the Bluefield GPU. We used it for the Nintendo Switch — it’s going to be the most popular and success game console in the history of game consoles. So we are enthusiastic ARM licensees.
There are three reasons why we should buy this company, and we should buy it as soon as we can.
Number one is this: as you know, we would love to take Nvidia’s IP through ARM’s network. Unless we were one company, I think the ability for us to do that and to do that with all of our might, is very challenging. I don’t take other people’s products through my channel! I don’t expose my ecosystem to to other company’s products. The ecosystem is hard-earned — it took 30 years for Arm to get here — and so we have an opportunity to offer that whole network, that vast ecosystem of partners and customers Nvidia’s IP. You can do some simple math and the economics there should be very exciting.
Number two, we would like to lean in very hard into the ARM CPU datacenter platform. There’s a fundamental difference between a datacenter CPU core and a datacenter CPU chip and a datacenter CPU platform. We last year decided we would adopt and support the ARM architecture for the full Nvidia stack, and that was a giant commitment. The day we decided to do that we realized this was for as long as we shall live. The reason for that is that once you start supporting the ecosystem you can’t back out. For all the same reasons, when you’re a computing platform company, people depend on you, you have to support them for as long as you shall live, and we do, and we take that promise very seriously.
And so we are about to put the entire might of our company behind this architecture, from the CPU core, to the CPU chips from all of these different customers, all of these different partners, from Ampere or Marvell or Amazon or Fujitsu, the number of companies out there that are considering building ARM CPUs out of their ARM CPU cores is really exciting. The investments that Simon and the team have made in the last four years, while they were out of the public market, has proven to be incredibly valuable, and now we want to lean hard into that, and make ARM a first-class data center platform, from the chips to the GPUs to the DPUs to the software stack, system stack, to all the application stack on top, we want to make it a full out first-class data center platform.
Well, before we do that, it would be great to own it. We’re going to accrue so much value to this architecture in the world of data centers, before we make that gigantic investment and gigantic focus, why don’t we own it. That’s the second reason.
Third reason, we want to go invent the future of cloud to edge. The future of computing where all of these autonomous systems are powered by AI and powered by accelerated computing, all of the things we have been talking about, that future is being invented as we speak, and there are so many great opportunities there. Edge data centers — 5G edge data centers — autonomous machines of all sizes and shapes, autonomous factories, Nvidia has built a lot of software as you guys have seen — Metropolis, Clara, Isaac, Drive, Jarvis, Aerial — all of these platforms are built on top of ARM, and before we go and see the inflection point, wouldn’t it be great if we were one company.
And so the timing is really quite important. We’ve invested so much across all of these different areas, that we felt that we really had to take the opportunity to own the company and collaborate deeply as we invent the future. That’s the answer.
It turns out this is very much an Nvidia vision after all. Nvidia is not setting out to be a partner, someone that gets along with everyone in exchange for a couple of pennies in licensing fees. Quite the opposite: Huang wants to own it all.
In this vision Nvidia’s IP is the CUDA to its graphics chips — the complement to its grander ambitions. Huang has his sights set firmly on Intel, but while Intel has leveraged its integration of design and manufacturing, Nvidia is going to leverage its integration of chip design and software. Huang’s argument is that it is the lack of software — a platform, as opposed to simply a chip or a core — that is limiting ARM in the data center, and that Nvidia intends to build that software.
On one hand, this is exciting for ARM licensees, particularly companies like Amazon that have invested in ARM chips for the data center; note, though, that Nvidia isn’t doing this out of charity. Huang twice mentioned the importance of capturing the upside he believes Nvidia will generate, which ultimately means increased license fees. Sure, Nvidia will be able to make more changes to ARM to suit the data center than they could have as licensor, but the real goal is to tie ARM into an Nvidia software platform until licensees have no choice but to pay what will undoubtedly be ever-increasing licensing fees (which, it should be noted, will still result in chips that less expensive than Intel’s).
I don’t know if it will work; data centers are about the density of processing power, which is related to but still different than performance-per-watt, ARM’s traditional advantage relative to Intel, and there are a huge amount of 3rd-parties involved in such a transition. There is a lot about this vision that is out of Nvidia’s control — it’s more of a dream. What is comforting in a way, though, is just how true this dream is to what makes Nvidia unique: this isn’t about adopting ARM’s approach, it’s about co-opting it for a vision of integration that makes Nvidia an object of inevitability, not affection.
And, to return to the beginning, it is a bet that is a relatively free one. If Nvidia’s stock is over-priced, then it is buying Arm for an even bigger discount than it seems; the vision Huang laid out, though, is a reason to believe Nvidia’s stock price is actually correct. Might as well roll the dice on a P.A. Semi-type outcome.
Three additional notes about this transaction:
Sequoia Capital sets up hedge fund for China tech investment Funds Global Asia
– Elad Gil (@eladgil)06:02 – 2020/09/15
We founded Opendoor to make it simple and instant to buy and sell a home, to delight customers, and to build an iconic, once in a generation company. Today marks a major milestone as we work to make Opendoor available to millions of homeowners every day. businesswire.com/news/home/2018… twitter.com/Opendoor/statu…
– Eric Wu (@ericwu01)05:09 – 2020/09/15
Airmeet, a 1-year-old virtual events platform based in Bengaluru, India, raised $12 million in Series A funding.
Subscribe to the Crunchbase Daily
New investor Sequoia Capital India led the round joined by Redpoint Ventures, with participation from existing investors Accel India, Venture Highway, Global Founders Capital and Gokul Rajaram. Airmeet has raised approximately $15 million since the company was founded last year, including a $3 million seed round last year, co-founder Lalit Mangal told Crunchbase News.
Airmeet’s platform features a ballroom-style social lounge with virtual tables for serendipitous encounters and a “speed networking” lobby where participants can spontaneously meet and make new connections in one- to-five-minute increments.
Although the company focuses on helping event organizers host interactive and immersive events ranging from a professional meetup to a large-scale festival, the origins of the company came from being a remote company, Mangal said.
“In India, there is not enough awareness of remote work,” he said. “More people are moving out of big cities, and this is a new way to build connections.”
Airmeet will use the new funding on product development and accelerating growth in regions of importance. In addition, the company plans to grow its team from 60 to 100 across six countries.
Until now, much of the company’s growth has been by word of mouth, with more than 10,000 events hosted on the platform since July, Mangal said. The goal is to support 10 million people on the platform and to host more than 1,000 events per day.
Abhishek Mohan, vice president of Sequoia Capital India, said in a statement that the COVID-19 pandemic has shifted behaviors in many industries as digitization has gained in popularity. As a result, the global online events space, which is poised to grow nearly tenfold to $744 billion in the next 10 years, is ripe for market leaders to drive the transition to online events.
“Airmeet’s mission is to create a global platform to enable millions of community managers and event organizers across the world to engage with and expand their audience,” he added. “And with Lalit and [his] team’s focus, execution and innovative thinking, they are strongly placed to achieve their goal.”
Social Lounge photo courtesy of Airmeet
Illustration: Li-Anne Dias
Two weeks ago, Microsoft told bankers it was confident it was the frontrunner in a bid to acquire TikTok’s operations in the U.S. against competing bidders such as Oracle. In one discussion with banks about potentially financing the deal for the ascendant viral video app, a Microsoft executive said the company was well-positioned to win the backing of the Trump White House, which had set the auction process in motion in July alleging the app posed a threat to national security, according to a person with direct knowledge of the meeting.
Then last week, Microsoft executives told some banks that the company no longer was considering using bank loans for the deal, a decision some bankers viewed as abrupt.