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.
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.
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