SkyHive is on a mission to organize the world’s workforce data and help people acquire future skills needed to adapt—enabling the reskilling required for a more efficient global economy. We’ve built the only Quantum Labor Analytics platform to optimize human economies in real-time for companies, communities, and countries. Leveraging a knowledge graph of more than 2 trillion relationships, we illuminate the reskilling journey and enable our clients to create a capable and future-proof workforce, closing skills-gaps and unleashing human potential for all.

At the Stanford Human Perception Laboratory1. We are creating Synthetic perception - bio mimicking how the human sensory systems gathers information from the environment via cranial nerves. In the present application this would be through multimodal inputs paralleling human senses including but not exclusive to the following examples cameras (vision) , microphone (auditory), haptics (touch), physical/virtual sensors (taste and smell).   Synthetic perception provides machines the capabilities to perceive like humans, enabling machines to interact within physical, virtual and immersive environments in a manner similar to humans, including decision making and actions in the context/situation of the machine’s environment. These capabilities augment human-machine interfaces and provides both human-centered experiences and enables human-centered devices - these devices include but are not exclusive to HMD devices (AR/VR/MxR), wearables, and robotics.2. We are developing the universal sensory index as a composite of biometric/multi-modal/multi-sensory data found in physical/virtual/immersive environments and including both physical and virtual sensory data.    The universal sensory index will dynamically change based on presence and/or absence of sensors, context/situational environment, weighting of sensory inputs, access to demographic/PII data, cyber protection, privacy, user sovereignty/ownership to name a few dependencies.  The Universal sensory index with advance AI capabilities by enabling machines the ability to sense and infer the environment in terms of perception, decision making with layered common sense reasoning based on context/situation of environment and recommendations/predictions/actions based on cause and effect to self, objects, situation and environment in the multitude of settings inclusive but not exclusive to physical, virtual and immersive settings.

Co-creator of FogHorn that enables data-driven application development for multi-tier IoT infrastructures

Top-ranked applied AI conference that brings together top researchers (in academia and research labs) and AI practitioners (data scientists, engineers, and product professionals at leading tech companies and startups). Past sponsors include Google, Microsoft, Facebook, Amazon, etc.www.aifrontiers.com

Peritus is dedicated to building AI assistants to make tech workers more productive to achieve our vision of zero-touch customer service. Our patented cloud-first Knowledge Engine uses advanced NLP and machine learning to enable continuous learning from content, discussions, case management, and product development systems. We embrace a human-in-the-loop philosophy to train data sets, refine recommendation quality, and learn from implicit user feedback.

Defining the future of work for the next billion employees. Neva is an AI platform for employee service used by many of the world's most respected organizations.

The Hive is a company creation studio, we either invest in early stage startups or create companies from the scratch. Our main focus is on large scale data processing and AI.Created Euclid, a general-purpose platform built at The Hive to address the problem of developing and serving production-grade machine learning models in a matter of weeks and not months. Euclid is designed to standardize machine learning workflows and tools such as data labeling, monitoring, model management, etc., to build and operate these systems at scale.As a CTO of Hive I play the role of CTO of CTOs for our portfolio companies helping them drive the technical side of the things.

Lead the Big Data and Large Scale Machine Learning team.Responsible for advanced research and development of data platform using Apache Spark.Designed and Developed personalization system to handle 500 million users with over 200 billion events.Large Scale Collaborative Filtering based Recommendation Engine.Machine Learning Toolset/API Mobile Platform DevelopmentDesign and tune the server backend architecture to scale to over 10M DAU.