Key iPhone X Supplier Receives Qualification and Meaningfully Expands Capacity

Finisar (FNSR) reported earnings for the Oct-17 quarter and the company announced they began shipping production quantities of VCSEL arrays. Finisar is Apple’s 2nd largest VCSEL array supplier, which powers 3D sensing applications such as facial recognition through a flood immolator and dot projector on the face of the iPhone X (see below). In addition, the company announced they acquired a 700,000 square foot facility in Sherman, Texas, which will allow them to scale production of their VCSEL arrays. This new site is expected to go live in 2H18. With the combination of volume orders beginning, as well as capex initiatives, we believe Finisar received final qualification from Apple, and will begin shipping larger quantities of VCSEL arrays in the Jan-18 quarter and throughout CY18.

Impact to Apple. In terms of a read on demand for iPhone X, Finisar’s comments are in-line with previous comments, so we are not making any changes to our iPhone estimates. What was incremental was acquisition of the Sherman, Texas production facility which suggests that Apple will add the VCSEL array to all of its new phones starting the fall of 2018. Today the VCSEL array is limited to the iPhone X. Separately, our daily checks suggest iPhone X remains supply constraint. We believe the VCSEL laser is causing production bottlenecks for the iPhoneX and with Finisar now receiving Apple qualification we expect the supply/demand imbalance will ease in the next month.

What they said. Finisar VCSEL revenue in the quarter was in the low-single-digit millions, but the company anticipates sales can grow to “tens of millions” of dollars per quarter beginning in Jan-18 and beyond. Once they are at full capacity they will see revenues reaching $30M. However, this compares to Apple’s largest VCSEL array supplier, Lumentum, who recorded $40M in VCSEL revenue in the Sep-17 quarter.

Finisar and Lumentum continue to talk about one customer (Apple) driving demand for VCSEL arrays. We believe both companies remain supply constrained, but Apple has secured a high percentage of all VCSEL lasers created, which we view as a large competitive advantage that will make Apple a leading AR player in the smartphone space.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Why the Money’s on 3D and AR for Mobile

Written by guest author Matan Libis, VP of Product at WakingApp.

Remember when VR headsets were going to be as ubiquitous as iPhones?

The launch of Facebook’s Oculus Rift and HTC’s Vive in the spring of 2016 was met with understandable excitement: the technology was impressive and the user experience exhilarating. But any dream of mass adoption beyond gamers has so far been just that. As TechCrunch reported, VR revenue in 2016 fell far short of the $3.8 billion projections.

There may yet come a day when VR is realized for its full commercial potential, but in the immediate future, the tech world is setting its sights on AR and 3D for mobile. The oversize and unexpected success of Pokémon GO ($600 million in AR mobile revenue in the first three months alone) last year turned heads and reframed the conversation.

And unlike VR, there’s more to AR than just the “wow factor.” AR has real business use cases that can be applied now, from the manufacture and design of the Internet of Things (which one report estimates could be a $7 trillion AR market by 2027), to 3D ads on mobile, to customer service and educational training. For those reasons, Tractica predicts that AR usage on mobile will grow to 1.9 billion unique monthly active users in 2022, from 342.8 million in 2016—to the tune of $18.5 billion in annual mobile AR revenue.

The tech giants are already signaling a shift to AR. Facebook, which bought Oculus for $2 billion and poured millions more into its VR efforts, announced the launch of a platform for augmented reality at Facebook’s annual developer conference in April. Microsoft is adding an AR viewer directly into Windows 10 later this year. And Apple has just released its ARKit, hoping to open the AR market to users of all kinds, with apps for gaming, design, home improvement and much more. Last year, the company’s CEO Tim Cook envisioned a future when we “have AR experiences everyday, almost like eating three meals a day. It will become that much a part of you.”

In fact, some of Snapchat’s 166 million users have already internalized this message. Those silly selfie lenses have brought AR into everyday usage, and last month the company added 3D objects to the mix. It’s not a stretch to imagine 3D/AR as the next big format for sharing data, just as we once texted each other jpgs, then videos, then GIFs.

The question is, why strive to build a device as universally used as a mobile phone when you can add an AR or 3D layer to existing phones? Mobile-first has to be the mantra of any business today. And the good news is that for companies that want in on this AR/3D wave, the barriers need not be so high.

A mobile-optimized platform allowing anyone—even non-programmers—to easily integrate 3D and AR/VR into existing apps – has the potential to revolutionize business at many levels.

For example, Autodesk has recently enabled AR/VR in its software so that CAD users and customers can experience their designs in real time. Microsoft, too, is using AR in its Power BI iOS app to give its customers the ability to augment dashboard tiles within the Power BI app by displaying AR content directly above a scanned QR code. The possibilities are really endless – easy access to AR would allow engineers to gain a real picture of what their creations will be like in the real world, it will allow interior decorators to build a virtual scenario that lets clients walk around and experience for themselves the designed space that they have invested in, and it is already being applied in retail sales; there’s Amazon’s new AR View that lets customers visualize online products in their own home, and stores like Gap and Adidas are using AR to show customers how they will look in outfits with “virtual dressing rooms”. Industrial companies can use AR technology to virtually train employees instead of exposing them to risk by placing them, untrained, in sensitive environments.

The rapid adoption of AR technology is happening and not only are large corporations jumping onboard, but small and medium sized businesses are as well. For AR and 3D, the future is bright—and it’s happening now.

This piece originally appeared on WakingApp. For more, follow their blog and LinkedIn.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

2017 Loup Ventures Holiday Gift Guide

Here are a few gift recommendations for the 2017 holiday season:

And here’s a look ahead to 2018 with some of the products we’re hoping for:

  • Apple HomePod | Apple’s foray into the smart speaker market.
  • Apple iPhone X Plus | We’d love a larger screen for our iPhone Xs.
  • Oculus Go | Oculus’ $199 standalone VR headset.
  • Magic Leap | Augmented Reality glasses.
  • Tesla Model 3 | Already on the market, we’re hoping to see shorter reservation times.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Nvidia Foundational Player In Future of Tech; Introducing 5-Yr Model

Today we’re rolling out our 5-year model for Nvidia, joining Loup Ventures’ Apple, Tesla, and iRobot model coverage. It’s important we write on Nvidia given its products are an integral part of the future of technology, based on their use in datacenters, autonomous vehicles, virtual and augmented reality platforms, cryptocurrency mining and eSports. We’re believers in the long-term story of Nvidia. While shares of NVDA has performed exceptionally well this year, up 100% YTD (market cap of $129 billion), we think there is further upside given Nvidia’s foundational exposure to frontier technologies.

25+% CAGR Story Through 2023. We expect Nvidia’s core gaming business to continue to grow, but decrease as an overall percentage of revenue (57% today, to 41% by 2023). In addition, we see Nvidia’s datacenter and automotive segments taking second and third place, growing to 36% and 14% of revenues respectively.  We believe Nvidia will see 20+% annual revenue growth through 2023, driven primarily by four catalysts:

Catalyst #1 – Demand for core gaming business products remains strong.  Historically, Nvidia has been known for providing high-quality GPUs for gaming. Nvidia was well-known in the PC gaming space in the mid-t0-late 1990s, and even won the contract to provide graphics hardware for the original Microsoft Xbox. Nvidia has maintained its leadership in the space, and stands as the go-to GPU component for gamers. Despite competition from AMD, ASUS, and Intel, Nvidia has remained a leader. In addition there are two trends that add to the growth of Nvidia’s gaming business:

ESports continues to rise in popularity. Newzoo expects the ESports market to reach $1.5B by 2020, up from $696M in 2017. Not only are more users participating in ESports, but more advertisers are flocking to the industry as well.

Gaming is becoming more social. This is driving engagement and bringing more people on to various platform, including PC platforms where Nvidia’s products are often used. While this can partially explain the rise in ESports, the trend impacts users that opt out of participating in eSports in favor of playing with their friends. Most platforms are spending more time creating online communities where users can interact with each other. Separately, with more kids using tablets and mobile phones at an early age, the exposure and transition to gaming is greater than ever before. As parents continue to let devices act as virtual babysitters, the number of children that get into gaming grows.

Catalyst #2 – Companies are adopting artificial intelligence in order to remain competitive. Nvidia’s datacenter business (20% of revenue today, to 36% by 2023) has seen triple digit growth for the past six quarters. A big part of this growth is due to the expanding use of artificial intelligence by companies, specifically deep learning. Even more positive for Nvidia, we are only in the early innings of the game. Just as all companies evolved to be internet companies in the late 1990s and early 2000s, and mobile companies in the late 2000s, they will soon evolve to be AI companies. On Nvidia’s last earnings call, CEO Jensen Huang shared:

“…Artificial intelligence and its emergence and applications to solving problems that we historically thought were unsolvable. Solving the unsolvable problems is a real realization. I mean, this is happening across just about every industry we know, whether it’s Internet service providers, healthcare, manufacturing, transportation, logistics, you name it.” – Jensen Huang

We expect Nvivia’s datacenter segment to continue to see high growth as companies rely more on artificial intelligence. By 2023, we expect Nvidia’s datacenter business to account for over one-third of its revenues and be growing at 30% annually.

Catalyst #3 – The market for autonomous vehicles will be bigger than most people think. Nvidia’s opportunity in the automotive space (6% of revenue today, to 14% by 2023) is bigger than many anticipate. As stated in our Auto Outlook 2040, we expect 90% of vehicles on the road in 2040 to have level 4 or 5 automation, which would require a platform such as Nvidia’s DRIVE PX. Nvidia’s products are used in two different instances as it relates to autonomous vehicles. First, Nvidia’s DGX system is used to train neural networks at data centers. Second, Nvidia’s DRIVE PX platform provides cars with the necessary on-board computing strength for autonomous capabilities. Currently, Nvidia has partnered with Toyota, Mercedez-Benz, Audi, Volvo, and Tesla, among other. We see the ramp of autonomous vehicles beginning in late 2020 as autonomous taxis enter the field, and further expanding in 2021 as autonomous consumer vehicles enter the market. By 2023, we expect Nvidia’s automotive segment growth to accelerate from 16% in 2017 to 100% y/y in 2023. 2023 is only the beginning of autonomous vehicles, and Nvidia’s automotive segment will continue to accelerate past the 5-year window. Based on our auto outlook, we feel 2028 is the year where there will be an influx of demand for level 4 and level 5 autonomous vehicles. We expected Nvidia’s automotive segment growth will continue to accelerate until that time.

Catalyst #4 – Nvidia has planted seeds in other industries with bright futures. OEM & IP is 8% of revenue today, to 3% by 2023.

Virtual Reality. Nvidia’s GPUs are a core component for virtual reality solutions. Today, high-quality VR solutions require a headset tethered to a desktop or laptop computer, which are often running off of an Nvidia GPU. While we believe that VR content will move to standalone devices in the future, those devices will still require enough processing power to delivery high-quality experiences. Nvidia’s solution, the Tegra mobile processor line, is currently a leading option for manufacturers. Nvidia is well-positioned to benefit from the growth of virtual reality gaming, as its products are used in three (mobile, PC-based, standalone) of the four VR solutions, missing out on only console-based VR; for now.

Augmented Reality. We’ve written many times before about the future of augmented reality and the impact that it will have on how we interact with the world in the future. Similar to VR, AR requires sufficient computing capacity on any device. As the market for AR develops, Nvidia will benefit as either a manufacturer of specific solutions for customers, or tangentially through expanding cloud use for deep learning algorithms used by AR applications.

Cryptocurrencies. Lastly, Nvidia is poised the benefit from the continued growth of cryptocurrencies. Cryptocurrencies require individuals to dedicate computing power to the the blockchain, those that do are referred to as miners. Miners often turn to GPUs for the necessary processing power to complete blocks on the blockchain. Here is an explanation of how mining works, and why it is necessary.

If you read that article, your reaction might match James Franco’s above. Putting it another way, miners rely on GPUs to provide a cryptocurrency network with the necessary processing power to function. As a particular cryptocurrency is mined (with GPUs), customers will ask for specific ASICs to be built by companies such as Nvidia (positively impacting OEM and IP). As these custom ASIC components are deployed, the specific coin’s mining market becomes monopolized, and forces smaller miners to move a different currency in order to remain profitable. The smaller miners will turn back to GPU-based solutions (positively impacting Gaming) before the cycle repeats itself. Because of this ebb-and-flow and the volatile nature of cryptocurrencies, modeling the impact of cryptocurrency mining is difficult. While highly speculative and volatile, we feel that cryptocurrencies will be a part of the future. We are modeling OEM and IP business to grow by the low single digits in the future.

Bottom Line. Artificial intelligence, autonomous vehicles, virtual reality, and augmented reality are technologies that will have a profound impact on our lives. As these technologies take hold, companies supporting the development of the underlying components are sure to benefit. Betting on Nvidia is betting on frontier technologies, and Nvidia has planted seeds in numerous areas that we are optimistic about. Despite competition from Intel and AMD, Nvidia will continue to be the dominant component supplier in various spaces.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Eight Fun Facts About Computer Vision

Our experience of the world is intensely visual. Researchers suggest over half of our brain power is devoted to processing what we see. We talk a lot about how artificial intelligence will transform the world around us, automating physical and knowledge work tasks. In order for such a system to exist, it’s clear that we must teach it to see. This is called computer vision, and it is one of the most basic and crucial elements of artificial intelligence. At a high level, endowing machines with the power of sight seems simple, just slap on a webcam and press record. However, vision is our most complex cognitive ability, and machines must not only be able to see, but understand what they are seeing. They must be able to derive insights from the entirely new layer of data that lies all around them and act on that information.

Despite being an important driver of innovation today, computer vision is little understood by those outside of the tech world. Here are a handful of facts that help put some context around what computer vision is and how far we’ve come in developing it.

1.)  Computer scientists first started thinking about vision about 50 years ago. In 1966, MIT professor Seymour Papert gave a group of students an assignment to attach a camera to a computer and describe what it saw, dividing images into “likely objects, likely background areas, and chaos.” Clearly, this was more than a summer project, as we are still working on it half a century later, but it laid the groundwork for what would become one of the fastest growing and most exciting areas of computer science.

2.)  While computer vision (CV) has not reached parity with human ability, its uses are already widespread, and some may be surprising. Scanning a barcode, the yellow first down line while watching football, camera stabilization, tagging friends on Facebook, Snapchat filters, and Google Street View are all common uses of CV.

3.)  In some narrow use cases, computer vision is more effective than human vision. Google’s CV team developed a machine that can diagnose diabetic retinopathy better than a human ophthalmologist. Diabetic retinopathy is a complication that can cause blindness in diabetic patients, but it is treatable if caught early. With a model that has been trained on hundreds of thousands of images, Google uses CV to screen retinal photos in hopes of earlier identification.

4.)  One of the first major industries being transformed by computer vision is an old one you might not expect: farming. Prospera, a startup based in Tel-Aviv, uses camera tech to monitor crops and detect diseases like blight. John Deere just paid $305M for a computer-vision company called Blue River. Their technology is capable of identifying unwanted plants and dousing them in a focused spray of herbicide to eliminate the need for coating entire fields in harmful chemicals. Beyond these examples, there are countless aerial and ground based drones that monitor crops and soil, as well as robots that use vision to pick produce.

5.)  Fei-Fei Li, head of Stanford’s Vision Lab and one of the world’s leading CV researchers, compares computer vision today to children. Although computers can “see” better than humans in some narrow use cases, even small children are experts at one thing – making sense of the world around them. No one tells a child how to see. They learn through real-world examples. Considering a child’s eyes as cameras, they take a picture every 200 milliseconds (the average time an eye movement is made). So by age 3, the child will have seen hundreds of millions of pictures, which is an extensive training set for a model. Seeing is relatively simple, but understanding context and explaining it is extremely complex. That’s why over 50% of the cortex, the surface of the brain, is devoted to processing visual information.

6.)  This thinking is what led Fei-Fei Li to create ImageNet in 2007, a database of tens of millions of images that are labeled for use in image recognition software. That dataset is used in the ImageNet Large Scale Visual Recognition Challenge each year.  Since 2010, teams have put their algorithms to the test on ImageNet’s vast trove of data in an annual competition that pushes researchers and computer scientists to raise the bar for computer vision. Don’t worry, the database includes 62,000 images of cats.

7.)  Autonomous driving is probably the biggest opportunity in computer vision today. Creating a self-driving car is almost entirely a computer vision challenge, and a worthy one — 1.25 million people die a year in auto-related deaths. Aside from figuring out the technology, there are also questions of ethics like the classic trolley problem: Should a self-driving vehicle alter its path into a situation that would kill or injure its passengers to save a greater number of passengers in its current direction? Lawyers and politicians might have to sort that one out.

8.)  There’s an accelerator program specifically focused on computer vision, and we’re excited to be participating as mentors. Betaworks is launching Visioncamp, an 11-week program dedicated to ‘camera-first’ applications and services starting in Q1 2018. Betaworks wants to “explore everything that becomes possible when the camera knows what it’s seeing.”

We’re just scratching the surface of what computer vision can accomplish in the future. Self-driving cars, automated manufacturing, augmented and virtual reality, healthcare, surveillance, image recognition, helpful robots, and countless other spaces will all heavily employ CV. The future will be seen.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.