DeepScale

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Overview

DeepScale AI is a computer vision startup focused on real time automotive perception systems that give cars self driving capabilities.  The team deploys onto cars pre-trained neural networks able to take information from any type of sensor system (including cameras, LiDar, etc.).  They are focused on "efficient" deep learning that is high powered but doesn't rely on expensive and specialized hardware.

DeepScale has a standard software licensing model that charges per sensor and per car to the manufacturer.  Their technology has already been licensed by a number of manufacturers and will be in customer cars in the next few years

The team is around 20 employees and is based in California. 

Why I like Them

What most people don't realize is that existing autonomous vehicles such as Waymo's are massively expensive.  The industry isn't cost-sensitive currently but it will have to become extremely cost conscience as it scales.  The current modus operandi for solving deep learning challenges is to throw more expensive hardware at it.  Automotive manufacturing is a low margin business and would never reach close to profitability with autonomous cars cost structure as they are being developed today.

 I like that DeepScale has thought ahead on this and is focused on creating computer vision systems that work on cars existing electronics (known as ECUs) rather than requiring additional specialized and expensive chips to be installed.  Under the current cost structures of automobile manufacturers, autonomous vehicles will not be able to be sold even close to current car prices, so the team's focus on the business side of the technology is particularly noteworthy.  By using systems already in the latest vehicles, they help automotive manufacturers save on cost by doing more with less.  Think of DeepScale as building efficient automotive AI.  

I also like the competitive nature of the product.  Their systems continue to gather data in the field and are able to be continuously updated with upgraded neural networks pushed to cars remotely that have already been sold.

Disclosure:  I have spoken to members of the team.

Where are the New S Curves?

S Curves are a business concept forecasting out the growth and development of new innovations as they progress through their technology life cycle.  They generally are considered to have 4 phases starting with Research and Development, Ascent where the technology starts seeing some real usages, Maturity where the technology is well established with slow growth remaining, and the Decay phase where other new technologies surpass it.  Wikipedia goes into much more detail here.  

S curves matter because they help you identify when the optimal time to invest is and when it's time to move on.  In other words, they are helpful in predicting growth and getting in front of it.  The big take away from the idea of S curves is that technology does not grow linearly, you have a long period of little to no growth with very few adopters, and then in a short time frame (1-3 years) the technology blossoms with it appearing to most people as coming out of nowhere  by magic to alter their daily lives.  

The dominant S curve of the last decade has easily been mobile, but its been in the maturity phase for the last few years.  Another S curve in the mature phase would be social media.  Every decade or so there is a dominant S curve but there are simultaneously other, smaller S Curves, that likely aren't as impactful in reshaping society but still bring about permanent change.

Some of the new S curves I am watching closely and where I see them in their cycle:

  • Artificial Intelligence - Despite all the hype this one is very early in the R & D phase with a ways to go.  We haven’t seen anything here yet.  This will likely really become the dominant S Curve of its time 10-20 years from now.
  • Drones - Ascent phase.
  • Autonomous Cars - R & D phase but will go into the ascent phase by 2020.  This will likely be the next big one after mobile over the next decade in that it will reshape society.
  • Blockchain - Ascent phase, even though with this one I don't think it will be as big as many people and the mainstream media will have you believe.
  • Genomics/CRISPR - Very early R & D phase.  We haven't even scratched the surface.
  • Virtual Reality - The ascent phase but I don't think virtual reality will be nearly as big or society changing as other S curves on this list.  I remain a sceptic on this one.
  • Augmented Reality - Solidly R & D phase but I think we will start to see it hit the Ascent phase in the not to distant future.
  • Alternative Energy sources/Battery technology - Early ascent phase but moving much more quickly than people think.  Check out my post here for more details. 
  • Cloud Computing - End of the ascent phase/beginning of the maturity phase.
  • Voice Interfaces - Beginning of the ascent phase.
  • 5G Technologies/IoT - About to hit the ascent phase as they come out of R & D.  The interesting thing here is I see 5G as being the catalyst that really kicks IoT (aka sensors being everywhere and in everything) into the ascent phase as well.  These S curves are even more intertwined than others.
  • Computer Vision - A subset of Artificial Intelligence above but one that is moving much faster along the S curve than other technologies that make up AI.  Currently in the beginning of the ascent phase.
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The State of AI 2018

Nathan Benaich and Ian Hogarth just released a great (and long) deck on the current state of AI as of the end of June 2018.  It is packed full of excellent information and data. 

A few items of interest that stood out to me:

  • The rise of Transfer Learning where a model trained on one data set for one task can be applied with much less training to a new and different task.
  • That AI right now seems to be more about having newer and better hardware (GPUs and TPUs) than anything else.  The limiting component for deep learning today is hardware with GPUs best for offline training of AI models, necessiating large CapEx investments in expensive hardware in the coming years for tech companies that want to remain competitive.
  • AI has become a service offered by the big cloud providers.
  • Some great case studies of AI being used today to disrupt different industries including pharma, Enterprise automation, transportation and cybersecurity.
  • One of their last slides has their big AI predictions over the next 12 months - I will be genuinely curious to see how many they get right.

6 River Systems

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Overview

6 River Systems is a robotics startup that creates warehouse fulfillment robots and AI systems.  The team builds both the AI software that manages the robots as well as the physical robots themselves.  In most fulfillment warehouses today workers pick items for shipping off the shelves by following a piece of paper and manually picking their route.  In contrast, 6 River systems has the worker or "picker" as they are called in the industry follow the robot as it optimizes for the route while picking items off the shelf and giving them to the robot to carry.  The system dramatically increases the key metric in fulfillment centers of items picked/ hour.  Their system is quick to deploy, easy to use, and generates value from the first day of deployment.  Customers include 3rd party logistics companies, industrial suppliers, traditional retailers, and young eCommerce companies.

6 River Systems differs from Amazon's famous Kiva robots by having the pickers go to the item whereas in Amazon's fulfillment centers the robots actually bring the shelves to the picker.  6 River Systems will never have the throughput of Amazon style systems, as they don’t eliminate walking, but they are able to sell their product with much less equipment and for far less than an Amazon style system.  The company likes to describe this as having 80%  of the benefit of warehouse robotics at 20% of the cost.  

In terms of business model the company sells the systems and software as well as offers a Robotics as a Service option where they lease the robots out.  The Robotics as a Service offering is popular as many companies in this space have thin operating margins and don't like to make expensive capital expenditures.  6 River Systems robots will be used at 30 sites by the end of this year.

The company is based in Boston and has 60 people.

Why I like Them

eCommerce continues to boom and will grow over the coming years globally as physical retail continues to shrink.  Automating fulfillment centers will only become more important as companies try to stay competitive.  6 River Systems has the perfect product offering to replace what today is mostly a manual process.  Collaboration robotics, where both a human and robot work together simultaneously, is the big trend to watch over the next decade in the field.

Like a number of people who follow the technology industry I am very excited for the future of robotics and automation.  The team was kind enough to explain their view that the reasons robotics is starting to see widespread adoption today include the intersection of: 

  • The miniaturaization and drop in costs of hardware including sensors, mainly due to the growth of the smartphone industry
  • The rise of Open Source software allowing for accelerated software development especially by small startups
  • Cloud based computing allowing infinite computing capacity for a low cost 

Disclosure:  I have spoken to members of the team.

Investor Discussion Series: Niko Bonatsos of General Catalyst

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Niko Bonatsos is a managaing director and former entrepreneur at General Catalyst.

What Trends are you currently investing in, especially any that are more under the radar?

At General Catalyst we are generalist investors looking to be inspired by ridiculously ambitious entrepreneurs.  Lately I’ve been spending a lot of time on Augmented Reality and Virtual Reality.  VR is better than ever but still early.  I’m also spending a lot of time in the crypto space.   Other areas I’m interested in investing around include the end of life space which includes life insurance, finding caregivers, setting up wills, etc.   Another non-sexy area I am looking to invest is the medical tourism industry such as a booking.com for medical tourism.  This is a huge space that is not yet followed by the mainstream.

You’ve written a bit and invested around augmented reality.   What do you think of Augmented Reality right now?

AR is still in its early days with the platforms having a vested interest to push it hard which you are seeing as all mobile devices became AR capable.  Pokemon Go’s success was a great example of the potential of the space. 

There are also very interesting enterprise use cases for mobile first AR products such as collaboration, technician help applications, etc.  We are also seeing a lot of high quality talent coming into the space.  Even more importantly some enterprise focused AR plays are starting to make money so this is really happening right now.  Recently I invested in 6D.ai, platform as a service that is solving data persistency and building the ARcloud. 

Gaming will be the first killer application on this platform.  Houzz recently did a study on an AR feature in their product that showed when customers use the AR feature they would spend a lot more money.  AR will also be a boon to eCommerce.

What are some resources you use to stay up to date on the space?

I read a lot of stuff.  I also get to meet a lot of super high quality people including angel investors, executives, and entrepreneurs.  I then simply put in the hours to learn the space. 

Any advice to young venture capitalists and angel investors out there in sourcing deals?

●      Assume you will lose all your $ when you invest as an angel - only invest what you can afford to lose.

●      Come up with a mental framework (e.g. I only invest in people that I’d start a company with, etc.) of what type of opportunities you want to invest in.

●      As an angel investor the stuff you think will do well won’t do well and the stuff you think won’t do well will do well. 

●      Double down on stuff you are very certain will work out very well.

Any predictions for 2018-2019?

There will be a VR company with a million daily active users.  At least 3 or 4 more Pokemon Go types of companies that are AR enabled.  There will emerge a second killer app for crypto (beyond digital money) with crypto scaling so people can build off of them as platforms.