Tag: Alexa

Investment Themes for 2019

2018 was a busy year for Madrona and our portfolio companies. We raised our latest $300 million Fund VII, and we made 45 investments totaling ~$130 million. We also had several successful up-rounds and company exits with a combined increase of over $800 million in fund value and over $600 million in investor realized returns. We don’t see 2019 letting up, despite the somewhat volatile public markets. Over the past year we have continued to develop our investment themes as the technology and business markets developed and we lay out our key themes here.

For the past several years, Madrona has primarily been investing against a 3-layer innovation stack that includes cloud-native infrastructure at the bottom, intelligent applications (powered by data and data science) in the middle, and multi-sense user interfaces between humans and content/computing at the top. As 2019 kicks off, we thought it would be helpful to outline our updated, 4-layer model and highlight some key questions we are asking within these categories to facilitate ongoing conversations with entrepreneurs and others in the innovation economy.

For reference, we published our investment themes in previous years and our thinking since then has both expanded and become more focused as the market has matured and innovation has continued. A quick scan of this prior post illustrates our on-going focus on cloud infrastructure, intelligent applications, ML, edge computing, and security, as well as how our thinking has evolved.

Opportunities abound within AND across these four layers. Infinitely scalable and flexible cloud infrastructure is essential to train data models and build intelligent applications. Intelligent applications including natural language processing models or image recognition models power the multi-sense user interfaces like voice activation and image search that we increasingly experience on smartphones and home devices (Amazon Echo Show, Google Home). Further, when those services are leveraged to help solve a physical world problem, we end up with compelling end-user services like Booster Fuels in the USA or Luckin Coffee in China.

The new layer that we are spending considerable time on is the intersection between digital and physical experiences (DiPhy for short), particularly as it relates to consumer experiences and health care. For consumers, DiPhy experiences address a consumer need and resolve an end-user problem better than a solely digital or solely physical experience could. Madrona companies like Indochino, Pro.com and Rover.com provide solutions in these areas. In a different way, DiPhy is strongly represented in Seattle at the intersection of machine learning and health care with the incredible research and innovations coming out of the University of Washington Institute for Protein Design, the Allen Institute and the Fred Hutch Cancer Research Center. We are exploring the ways that Madrona can bring our “full stack” expertise to these health care related areas as well.

While continuing to push our curiosity and learning around these themes, they are guides not guardrails. We are finding some of the most compelling ideas and company founders where these layers intersect. Current company examples include voice and ML applied to the problem of physician documentation into electronic medical records (Saykara), integrating customer data across disparate infrastructure to build intelligent customer profiles and applications (Amperity), or cutting edge AI able to run efficiently in resource constrained edge devices (Xnor.ai).

Madrona remains deeply committed to backing the best entrepreneurs, in the Pacific NW, who are tackling the biggest markets in the world with differentiated technology and business models. Frequently, we find these opportunities adjacent to our specific themes where customer-obsessed founders have a fresh way to solve a pressing problem. This is why we are always excited to meet great founding teams looking to build bold companies.

Here are more thoughts and questions on our 4 core focus areas and where we feel the greatest opportunities currently lie. In subsequent posts, we will drill down in more detail into each thematic area.

Cloud Native Infrastructure

For the past several years, the primary theme we have been investing against in infrastructure is the developer and the enterprise move to the cloud, and specifically the adoption of cloud native technologies. We think about “cloud native” as being composed of several interrelated technologies and business practices: containerization, automation and orchestration, microservices, serverless or event-driven computing, and devops. We feel we are still in the early-middle innings of enterprise adoption of cloud computing broadly, but we are in the very early innings of the adoption of cloud native.

2018 was arguably the “year of Kubernetes” based on enterprise adoption, overall buzz and even the acquisition of Heptio by VMware. We continue to feel cloud native services, such as those represented by the CNCF Trail Map, will produce new companies supporting the enterprise shift to cloud native. Other areas of interest (that we will detail in a subsequent post) include technologies/services to support hybrid enterprise environments, infrastructure backend as code, serverless adoption enablers, SRE tools for devops, open source models for the enterprise, autonomous cloud systems, specialized infrastructure for machine learning, and security. Questions we are asking here include how the relationship between the open source community and the large cloud service providers will evolve going forward and how a broad-based embrace of “hybrid computing” will impact enterprise customer product/service needs, sales channels and post-sales services.

For a deeper dive click here.

Intelligent Applications with ML & AI

The utilization of data and machine learning in production has probably been the single biggest theme we have invested against over the past five years. We have moved from “big data” to machine learning platform technologies such as Turi, Algorithmia and Lattice Data to intelligent applications such as Amperity, Suplari and AnswerIQ. In the years ahead, “every application is intelligent” will likely be the single biggest investment theme, as machine learning continues to be applied to new and existing data sets, business processes, and vertical markets. We also expect to find interesting opportunities in services that enable edge devices to operate with intelligence, industry-specific applications where large amounts of data are being created like life sciences, services to make ML more accessible to the average customer, as well as emerging machine learning methodologies such as transfer learning and explainable AI. Key questions here include (a) how data rights and strategies will evolve as the power of data models becomes more apparent and (b) how to automate intelligent applications to be fully managed, closed loop systems that continually improve their recommendations and inferences.

For a deeper dive click here.

Next Generation User Interfaces

Just as the mouse and touch screen ushered in new applications for computing and mobility, new modes of computer interaction like voice and gestures are catalyzing compelling new applications for consumers and businesses. The advent of Alexa Echo and Show, Google Home, and a more intelligent Siri service have dramatically changed how we interact with technology in our personal lives. Limited now to short simple actions, voice is becoming a common approach for classic use cases like search, music discovery, food/ride ordering and other activities. Madrona’s investment in Pulse Labs gives us unique visibility into next generation voice applications in areas like home control, ecommerce and ‘smart kitchen’ services. We are also enthused about new mobile voice/AR business applications for field service technicians, assisted retail shopping (E.g., Ikea’s ARKit furniture app) and many others including medical imaging/training.

Vision and image recognition are also rapidly becoming ways for people and machines to interact with one another as facial recognition security on iPhones or intelligent image recognition systems highlight. Augmented and virtual reality are growing much more slowly than initially expected, but mobile phone-enabled AR will become an increasingly important tool for immersive experiences, particularly visually-focused vocations such as architecture, marketing, and real estate. “Mobile-first” has become table stakes for new applications, but we expect to see more “do less, but much better” opportunities both in consumer and enterprise with elegantly designed UIs. Questions central to this theme include (a) what ‘high-value’ new experiences are truly best or only possible when voice, gesture and the overlay of AR/VR/MR are leveraged? (b) what will be the limits of image (especially facial recognition) in certain application areas, (c) how effective can image-driven systems like digital pathology be at augmenting human expertise, and (d) how will multi-sense point solutions in the home, car and store evolve into platforms?

For a deeper dive click here.

DiPhy (digital-physical converged customer experiences)

The first twenty years of the internet age were principally focused on moving experiences from the physical world to the digital world. Amazon enabled us to find, discover and buy just about anything from our laptops or mobile devices in the comfort of our home. The next twenty years will be principally focused on leveraging the technologies the internet age has produced to improve our experiences in the physical world. Just as the shift from physical to digital has massively impacted our daily lives (mostly for the better), the application of technology to improve the physical will have a similar if not greater impact.

We have seen examples of this trend through consumer applications like Uber and Lyft as well as digital marketplaces that connect dog owners to people who will take care of their dogs (Rover). Mobile devices (principally smartphones today) are the connection point between these two worlds and as voice and vision capabilities become more powerful so will the apps that reduce friction in our lives. As we look at other DiPhy sectors and opportunities, one where the landscape will change drastically over the coming decades is physical retail. Specifically, we are excited about digital native retailers and brands adding compelling physical experiences, increasing digitization of legacy retail space, and improving supply chain and logistics down to where the consumer receives their goods/services. Important questions here include (a) how traditional retailers and consumer services will evolve to embrace these opportunities and (b) how the deployment of edge AI will reduce friction and accelerate the adoption of new experiences.

For a deeper dive click here.

We look forward to hearing from many of you who are working on companies in these areas and, most importantly, to continuing the conversation with all of you in the community and pushing each other’s thinking around these trends. To that end, over the coming weeks we will post a series of additional blogs that go into more depth in each of our four thematic areas.

Matt, Tim, Soma, Len, Scott, Hope, Paul, Tom, Sudip, Maria, Dan, Chris and Elisa

(to get in touch just go to the team page – our contact info is in our profiles)

AWS re:Invent – the Big Announcements and Implications

The momentum continues to build and scale in leaps and bounds. That’s the overwhelming observation and feeling at the end of the 5th annual conference that Amazon hosted in Las Vegas last week for AWS (Amazon Web Services).

Here are some of the key take-aways that we think will have the highest industy impact.

Event-driven Functions and Serverless Computing

Serverless has definitely arrived. As expected, there were a number of new capabilities announced around Lambda, including C# language support, AWS Lambda@Edge to create a “CDN for Compute” and AWS Step Functions to coordinate the components of distributed applications using visual workflows through state machines. Beyond this, it was clear that Lambda, and the serverless approach overall, is being broadly woven into the fabric of AWS services.

In the world of event-driven functions, thinking about a standard way for people to publish events that make it easy to consume those events is going to be critical. Whichever platform gets there first will likely see a tremendous amount of traction.

Innovation in Machine and Deep Learning

AWS has had a machine learning service for a while now, and it was interesting to see a whole slew of new machine learning, deep learning and AI suite of services including Amazon Image Rekognition, Amazon Polly (Text to Speech deep learning service) and Amazon Lex (Natural Language Understanding engine inside Alexa that is now available as a service).

While the concrete use cases are still relatively spare, we – like Amazon – believe this functionality will be integrated into the functionality of virtually all applications in the future.

It is also clear that the proprietary data used to train models are what create differentiated and unique intelligent apps. The distinction between commodity and proprietary data is going to be critical as algorithms become more of a commodity.

Enterprise Credibility

In past years, whether it was intended or unintended, the perception was that taking a bet on AWS meant taking a bet on the public cloud. In other words, there was an unintended consequence of AWS as “all in on public cloud or nothing”. With the VMWare partnership, which was announced a couple months ago, but solidified on stage with VMWare’s CEO, Amazon clearly is supporting the hybrid infrastructure that many enterprises will be dealing with for years to come.

Equally noteworthy was the appearance of Aneel Bhusri, CEO of Workday, on stage to announce that Workday was moving to AWS as their primary cloud for production workloads. Clearly no longer just the realm of primarily dev and test, this is perhaps the strongest statement yet that the public cloud – and AWS in particular – is enterprise production capable.

Moving Up a Layer From a Set of Discrete Services to Solution-based Services

One big theme that showed through this year at AWS was the movement from a set of discrete services to complete solutions both for developers and for operators of applications and services. The beauty of this all is that AWS continues to move forward on this path in a way that is highly empowering for developers and operators.

This approach really shone through during Werner Vogels keynote on Day 2. He laid out AWS’ approach for the “modern data architecture” and then announced how the new service AWS Glue (fully managed data catalog and ETL service) covers all the missing pieces in terms of their end-to-end solution for a modern data architecture on AWS.

Eat the Ecosystem

One of the implications of AWS’ continued growth towards complete solutions is that they continue to eat into the domain of their partner ecosystem. This has been an implied theme in years past, but the pace is accelerating.

Some of the examples that drew the biggest notice:

• AWS X-Ray (analyze and debug distributed applications in production) which aims directly at current monitoring companies like New Relic, AppDynamics and Datadog
• AWS Lightsail (virtual private servers made easy) that, at $5/month, will put significant pressure on companies like Digital Ocean and Linode
• Rekognition (image recognition, part of AI suite described above) that provides a service very similar to Clarifai, who had actually been on a slide just a few prior to the service announcement!

No one should be surprised that AWS’ accelerating expansion will step on the toes of partners. An implication, as @benkepes tweeted, is that the best way to partner and extend AWS is to go very deep for a given use case because AWS will eventually provide the most common horizontal scenarios.

Partner Success = AWS Success

Although some of the new services conflicted with partner offerings, the other side of the coin was that AWS continues to embrace partners and is vested in partners’ success. They clearly understand that having their partners be successful ultimately contributes to more success for AWS. Having customers like Salesforce, WorkDay and Twilio take a complete bet on AWS , making the product of a partner like Chef be available as a fully-managed service on AWS, having a partner like Netflix excited to switch off their last datacenter as they are completely on AWS, and having a company like VMWare embrace AWS as their public cloud partner are some of the great examples of how Amazon is systematically working to ensure that their partners remain successful on AWS, all of which accrues more value and consumption of AWS.

Summary

The cloud opportunity is gigantic and there is room for multiple large players to have a meaningful position strength. However, as of today, Amazon is not just the clear leader but continues to stride forward in an amazing way.

First Published by Geekwire.

AWS re:Invent 5th Anniversary Preview: Five Themes to Watch

The 5th Annual AWS re:Invent is a week away and I am expecting big things. At the first ever re: Invent in 2012, plenty of start-ups and developers could be found, but barely any national media or venture capitalists attended. That has all changed and today, re:Invent rivals the biggest and most strategically important technology conferences of the year with over 25,000 people expected to be in Las Vegas the week after Thanksgiving!

So, what will be the big themes at re: Invent? I anticipate, from an innovation perspective, they will line up with the 3 layers of how we at Madrona think about the core of new consumer and enterprise applications hitting the market. We call it the “Future of Applications” technology stack shown below.

future-of-applications
Future of Applications (Madrona Venture Group Slide, November 2016)

The Themes We Expect at 2016 re:Invent

Doubling Down on Lambda Functions

First is the move “beyond cloud” to what is increasingly called server-less and event-driven computing. Two years ago, AWS unveiled Lambda functions at re:Invent. Lambda quickly became a market leading “event-driven” functions service. The capability, combined with other micro-services, allows developers to create a function which is at rest until it is called in to action by an event trigger. Functions can perform simple tasks like automatically expanding a compute cluster or creating a low resolution version of an uploaded high resolution image. Lambda functions are increasingly being used as a control point for more complicated, micro-services architected applications.

I anticipate that re:Invent 2016 will feature several large and small customers who are using Lambda functions in innovative ways. In addition, both AWS and other software companies will launch capabilities to make designing, creating and running event-driven services easier. These new services are likely to be connected to broader “server-less” application development and deployment tools. The combination of broad cloud adoption, emerging containerization standards and the opportunities for innovating on both application automation and economics (you only pay for Lambda functions on a per event basis) presents the opportunity to transform the infrastructure layer in design and operations for next-generation applications in 2017.

Innovating in Machine and Deep Learning

Another big focus area at re:Invent will be intelligent applications powered by machine/deep learning trained models. Amazon already offers services like AWS ML for machine learning and companies like Turi (prior to being acquired by Apple) leveraged AWS GPU services to deploy machine learning systems inside intelligent applications. But, as recently reported by The Information, AWS is expected to announce a deep learning service that will be somewhat competitive with Google’s TensorFlow deep learning service. This service will leverage the MXNet deep learning library supported by AWS and others. In addition, many intelligent applications already offered to consumers and commercial customers, including AWS stalwarts such as Netflix and Salesforce.com, will emphasize how marrying cloud services with data science capabilities are at the heart of making applications smarter and individually personalized.

Moving to Multi-Sense With Alexa, Chat and AR/VR

While AWS has historically offered fewer end-user facing services, we expect more end-user and edge sensors/devices interactions leveraging multiple user interfaces (voice, eye contact, gestures, sensory inputs) to be featured this year at re:Invent. For example, Amazon’s own Alexa Voice Services will be on prominent display in both Amazon products like the Echo and third party offerings. In addition, new chat-related services will likely be featured by start-ups and potentially other internal groups at Amazon. Virtual and augmented reality use cases for areas including content creation, shared-presence communication and potentially new device form factors will be highlighted. Madrona is especially excited about the opportunity for shared presence in VR to reimagine how people collaborate with man and machine (all powered by a cloud back-end.). As the AWS services stack matures, it is helping a new generation of multi-sense applications reach end users.

Rising Presence of AWS in Enterprises Directly and With Partners

Two other areas of emphasis at the conference, somewhat tangential to the future of applications, will be the continued growth of enterprise customer presentations and attendance at the conference. The dedicated enterprise track will be larger than ever and some high-profile CIO’s, like Rob Alexander from Capital One last year, will be featured during the main AWS keynotes. Vertical industry solutions for media, financial services, health care, and more will be highlighted. And, an expanding mix of channel partners, that could include some surprising cloud bedfellows like IBM, SAP and VMWare, could be featured. In addition, with the recent VMWare and AWS product announcements, AWS could make a big push into hybrid workloads.

AWS Marketplace Emerging as a Modern Channel for Software Distribution

Finally, the AWS Marketplace for discovering, purchasing and deploying software services will increase in profile this year. The size and significance of this software distribution channel has grown significantly the past few years. Features like metered billing, usage tracking and deployment of non “Amazon Machine Image (AMI)” applications could see the spotlight.

Over the years, AWS has always surprised us with innovative solutions like Lambda and Kinesis, competitive offerings like Aurora databases and elastic load balancing, as well as customer centric solutions like AWS Snowball. We expect to be surprised, and even amazed, at what AWS and partner companies will unveil at re: Invent 2016.