You don’t need a robotic arm to reach out and snag our $100,000 Early Stage Challenge, held every year during the Emerging Companies Summit at our GPU Technology Conference. But apparently it doesn’t hurt. Following a two-hour high-tech shootout with a dozen fledgling startups, Sadako Technologies emerged on top, receiving a check for $100k on the spot.
Barcelona-based Sadako has created a robot that uses machine learning to sort recycling and then extract specific types of valuable waste, like PET plastic bottles. Present at the competition was the CEO of data-visualization specialist MapD, winner of the first Early Stage Challenge two years ago, which just last week closed a $10 million funding round.
Eugenio Garnica, Sadako’s CEO and co-founder, used his allotted four-minute presentation slot during the Shark Tank-like competition before a packed room of more than 250 to describe how his GPU-powered robot differentiates types of trash and then snatches it with a specially designed gripper. While only three units have thus far been sold, he said the robot has a payback period of under 16 months, and there’s strong interest in a market worth up to $3 billion.
Our Toughest Early Stage Challenge Yet
Sadako emerged from what the four-judge panel called the toughest competition since the Early Stage Challenge began three years ago. The dozen startups, initially selected from a group of more than 100 applicants, hailed from a half-dozen countries. Among them were specialist drone makers and firms that use computer vision and AI for purposes such as helping the blind see the world, extracting more accurate weather forecasts and testing the integrity of food quality. (A full list is below.)
Each CEO was interviewed by a panel that included tech pundit Rob Enderle; George Hoyem, investment partner at In-Q-Tel; Brandon Farwell, a partner at Rothenberg Ventures; and Jeff Herbst, vice president of business development at NVIDIA. NBC Bay Area TV anchor and tech reporter Scott McGrew moderated. After the last presentation, the audience and panel voted for the winner.
The Early Stage Challenge was just one of a series of featured events at the Emerging Companies Summit, which also included sessions on China’s startup scene and startups focused on VR.
The Early Stage Challenge competitors were:
- Aerialguard (Israel) – Provides autonomous situational awareness for drones and UAVs, dramatically increasing safety, survivability and mission capabilities.
- CogniCor (Spain) – Uses AI and natural language processing for handling product queries, claims and other customer support issues.
- Lucid VR (U.S.) – Develops LucidCam, a stereoscopic 3D camera for consumers with 180-degree wide-angle lenses and spatial audio.
- Linkface (China) – Offers facial recognition technology powered by deep learning. Its cloud platform provides free services for non-commercial use and high-concurrency services for business use.
- Intelligent Voice (U.K.) – Offers speech-to-text technology and analysis of unstructured communications for compliance purposes, including the collection, processing and analysis of audio and other data types.
- Horus Technology (Italy) – Develops a wearable device that uses computer vision and machine learning to aid visually impaired people, describing the environment through bone conduction.
- Hypercubes (U.S.) – Develops satellites that reveal unprecedented details of Earth, with the ability to remotely classify chemical compositions for applications such as precision farming, mining, and oil and gas operations.
- BriSky Technology (China) – Develops all-weather industrial drones that use computer vision and deep learning to conduct tasks such as autonomous inspections of power lines, wind turbines, traffic monitoring, surveillance and public security.
- TempoQuest (U.S.) – Develops software as a service to meet the need for faster, more accurate weather forecasts for commercial users and government agencies.
- Entropix (U.S.) – Enables inexpensive cameras like those in smartphones and drones to capture extremely high resolution images at up to 8K.
- Analytical Flavor Systems (U.S.) – Uses machine learning and AI to identify and predict in real-time flaws, contamination and batch-to-batch deviations for food and beverage producers.