3D Printing Funding Over Time – Q3 2016

3D Printing Funding Over Time
3D Printing Funding Over Time
The above graph summarizes the total funding raised by 3D Printing companies for each year. 2015 was the best year so far with over $302M raised; 2014 is in second place with over $251M raised to date.
We are currently tracking 365 3D Printing companies in 9 categories across 41 countries, with a total of $1.2 Billion in funding. Click here to learn more about the full 3D Printing landscape report and database.

Future of TV Activity by Selected Investors – Q3 2016

Future of TV Activity by Selected Investors
Future of TV Activity by Selected Investors
The above analysis summarizes the total number of investment rounds Future of TV investors participated in, and the number of unique Future of TV companies funded by selected investors. Accel takes the lead with 27 investments and 14 Future of TV companies backed, followed by Intel with 25 investments and 12 Future of TV companies backed.
We are currently tracking 687 Future of TV companies in 11 categories across 36 countries, with a total of $20.3 Billion in funding. Click here to learn more about the full Future of TV landscape report and database.

Insurance Technology Company Founding Date Distribution

The following infographic summarizes the founding date distribution of Insurance Technology companies to show the percentage of Insurance Technology companies that were founded within a specific time period. It shows that the founding of Insurance Technology companies reached its peak from 2014-Present, with 27% of the companies being founded during this period. Company founding was at the lowest in 2000-2001 and 2002-2003, with only 2% of the companies being founded during those four years. We are currently tracking over 535 companies in 13 categories across 47 countries, with a total of $4.59 Billion in funding. To see the full list of 535 Insurance Technology companies, contact us using the form on www.venturescanner.com.

Insurance Tech Founding Dates

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you have any questions, reach out to info@venturescanner.com.

Digital Health Market Update

We have updated our digital health market map and it is attached below. We are currently tracking over 760 companies in 23 categories across 28 countries, with a total of $15.1B in funding. To see the full list of companies, contact us using the form on www.venturescanner.com.

Digital Health Visual Map

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you have any questions, reach out to info@venturescanner.com.

An Image is Worth a Thousand Words

This series of articles examines innovation in the Artificial Intelligence (AI) space. Our first post provided an introduction to the Artificial Intelligence startup landscape, our second post reviewed the top trends and companies within the Smart Home Robots category, and our third post reviewed those within the Deep Learning/Machine Learning category.

We researched the Artificial Intelligence sector and identified 881 companies with $3.07 B in funding across 13 categories. To see the full list of 881 Artificial Intelligence companies, contact us using the form on www.venturescanner.com. This article demonstrates how our technology and analysts can help corporations exhaustively scan for all the relevant companies in a given sector, and provide deep dives into categories of interest to identify the best startups for them to work with.

This week we are going to examine the Image Recognition category within the Artificial Intelligence sector, which is comprised of 103 companies with $455M in funding. Image recognition is the method of processing and analyzing images to understand and produce information from them, as well as identifying objects and faces in those images.

Artificial Intelligence Map-Image Recognition
Artificial Intelligence Map-Image Recognition

Image Recognition Trends

Here are some of the major trends that we are seeing in the image recognition space:

  • Multiple Object Recognition: Google researchers have developed a program twice as effective at locating and distinguishing multiple objects of various sizes in a single image, such as identifying different fruits in a fruit plate.
  • Image Description: Teams at Stanford and Google have independently created technologies that are able to recognize and describe entire scenes of photographs and videos in prose with great accuracy.
  • Gesture Recognition: NYU and Facebook AI Lab Director Yann LeCun has built a deep learning model capable of predicting the position of human limbs in images. This could lead to better gesture control and motion capture systems.
  • Facial Recognition: Facebook developed a program called “DeepFace,” which could determine if two faces in photos are the same person with 97.25% accuracy.

Interesting Image Recognition Startups

We have selected a few companies to highlight, based upon our analysts’ evaluations of their traction, technology differentiation, funding amount, and founding team pedigree.

  • Vicarious focuses on image recognition, segmentation, and scene parsing technologies. The company announced it can crack any type of CAPTCHA with at least 90% accuracy. It has raised $72M from notable investors including Vinod Khosla, Elon Musk, Mark Zuckerberg, and Aaron Levie.
  • Clarifai specializes in deep learning algorithms for visual search. It is developing an API for developers to access its image search technology and plans to license its software to corporate users. Its notable investors include Google Ventures, Nvidia, and Qualcomm Ventures.
  • Cortica specializes in deep learning image recognition technology that automatically extracts the core concept in images and videos and maps them to keywords. The company has over 100 patent applications and has raised $37.9M.
  • AlchemyAPI focuses on deep-learning-based text analysis. It also offers deep-learning-based image recognition APIs for face detection/recognition, image tagging, and image link extraction. The company has raised $2M in February 2013.
  • Superfish is building visual search technology focused on consumer applications. It has created 3 visual search mobile apps for animal, furniture, and product recognition. The company has raised $19.3M from notable investors including DFJ.

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you would like to learn more about how Venture Scanner could help you research and analyze any sector, contact us at info@venturescanner.com

Going Deep on Deep Learning Technology

This series of articles examines innovation in the Artificial Intelligence (AI) space. This showcases how our technology and analysts can help corporations exhaustively scan for all the relevant companies in a given sector landscape, and provide deep dives into categories of interest to identify the best startups for them to work with. Our first post provided an introduction to the Artificial Intelligence startup landscape, and our second post reviewed the top trends and companies within the Smart Home Robots sector.

This week we are going to examine another category in the Artificial Intelligence sector—the Deep Learning/Machine Learning category, which is comprised of 76 companies with $259M of funding. Machine learning is the technology of computer algorithms that improve themselves based on its learning from existing data, while deep learning is a specialization of machine learning that focuses on deeply layered neural networks.

Artificial Intelligence Map-Deep Learning 2

Machine Learning/Deep Learning Trends

The Artificial Intelligence sector has seen steady growth, as private investment in this sector has been expanding 62% a year on average for the past four years. Here are some of the major trends we’re seeing in the space:

  • Corporate Recruiting: Major corporations are recruiting researchers to join their in-house AI teams, such as Facebook, Google, Yahoo, Intel, Dropbox, LinkedIn, Pinterest, and Twitter.
  • Consolidating Industry Structure: We believe that the future of machine learning technology will be dominated by an oligarchy of companies, as the companies with more data and resources will have an AI learning advantage relative to others.
  • Broadening of Use-Cases: The technology will also evolve from having domain-specific use cases (such as recognizing faces) to more general-purpose applications (such as recognizing objects in pictures).
  • Deep Learning Processing Effectiveness: For the deep-learning sub-discipline, advances in cheap parallel computing, better algorithms, and increases in data volume have led to the ability to process information more accurately and in real-time.

Interesting Deep Learning/Machine Learning Startups

We have selected a few companies to highlight, based upon our analysts’ evaluations of their traction, technology differentiation, funding amount, and founding team pedigree.

  • Metamind builds deep learning technologies to solve natural language processing tasks, image classification problems, and database tasks. The company is comprised of a strong team from Stanford and received $18M in December 2014 from Khosla Ventures.
  • Scaled Inference aims to build a cloud platform for machine learning that’s accessible by developers through APIs. It will also offer specific services in pattern recognition, anomaly detection, prediction, and predictive ranking.
  • Sentient develops technology where Artificial Intelligence can be operated in a distributed fashion across millions of AI processing nodes. It has been seeking partnerships in the medical research, fraud detection, public safety, e-Commerce, and other industries.
  • GraphLab (Dato) builds a machine learning analytics engine used for making recommendations in consumer services. The company is comprised of a strong team from Carnegie Mellon and has raised $6.8M from New Enterprise Associates.
  • Numenta takes a different approach in deep learning by recognizing time-based patterns and making predictions. Its first product, Grok, is used for early detection of anomalies in IT systems, energy use prediction, rogue behavior detection, and geospatial tracking.

Stay tuned for next week, when we will examine the trends and some interesting companies within the Image Recognition category.

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you would like to learn more about how Venture Scanner could help you research and analyze any sector, contact us at info@venturescanner.com

What’s Going On With Smart Home Robots?

This is the second of a four part series looking into innovation in the Artificial Intelligence (AI) space. Our first post provided an introduction to the Artificial Intelligence startup landscape.

In last week’s article, we showed you how our technology and analysts can quickly develop a broad market landscape in very little time. This week, we’re going to look at an example of how our service can provide a deep dive into a category of interest. This can help corporations find the best startups to work with once they understand the strategic landscape.

The category we’re going to look at today is Smart Home Robots, which comprises of 35 companies with $196M of funding. This category includes automatic mechanical devices with a level of artificial intelligence that are built for the consumer household.

Smart Home Robot Key Trends

A recent Business Insider article shows the large growth potential for the home robots sector, with the market projected to be worth $1.5B in 2019 (up from $673M in 2014). This implies a compound annual growth rate (CAGR) of 17.39%, which is projected to be 7 times faster than industrial robots.

Despite this rapid growth, we find that the sector is still very much in its developmental stage. Most of the home robots are wheel-based and single-purpose, with the general-purpose humanoid robots still in the research phase.

AI blog post pic 3

Interesting Smart Home Robot Startups

We have selected Aldebaran Robotics and Jibo as some Smart Home Robots companies to highlight due to their significant funding, experienced founding team, differentiated technology, and our unique analyst opinions.

Aldebaran Robotics produces humanoid robots with mechanical, electronic, and cognitive features for home and entertainment purposes. Use cases for these robots include teaching math to your children and waking you up in the morning. The company has acquired a total funding of $20.3M from notable investors such as Intel Capital and Innovation Capital. Aldebaran currently produces a variety of different robot types:

  • Pepper: a 4-ft humanoid home robot on three wheels with a tablet-screen on its chest and an “emotional engine”.
  • Nao: a 1.9-ft humanoid robot mainly being used for research and education purposes.
  • Romeo: a 4.6-ft humanoid robot with arms and legs.

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The other company, Jibo, produces a small personal assistant home robot with features including:

  • Facial recognition to give personalized reminders (the robot recognizes who you are, and reminds you about your specific schedule),
  • Face-tracking telepresence,
  • Ability to learn preferences, and
  • Storytelling capabilities.

One of Jibo’s key differentiators is their ability to recognize and express emotive cues such as winks, smile, and laughter to enable more personalized interactions. Jibo attracted high consumer interest with its Indiegogo crowdfunding campaign raising $2.2M, far surpassing its original goal of $100,000. The project enjoys a credible development team, the MIT Personal Robots Group, and its consumer version is estimated to become available in 2015.

al blog post picture 2

Stay tuned for next week, when we will examine the trends and some interesting companies within the Machine Learning/Deep Learning category.

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you would like to learn more about how Venture Scanner could help you research and analyze any sector, contact us at info@venturescanner.com