With massive amounts of computational power, machines can now effectively uncover underlying structure in data as well as recognize objects and translate speech in real time. Deep learning, a new discipline in AI and machine learning uses neural network models that automate the learning of data representations and features. It achieves things we never previously thought possible in areas such as conversational intelligence, natural language processing, computer vision and IoT.
In the recent years, we have seen computer vision technologies commercially deployed in consumer applications due to commoditization of cameras in mobile devices, as well as applications in autonomous vehicles, medical imaging, etc. Applications of deep learning techniques like convolutional neural networks (CNNs) in the recent years have brought accuracy levels of object recognition in images to higher than that of human cognition. Since then, the research community has been making great strides in scene recognition through automation of image feature extractions and labeling. Computer image rendering for mobile image, video and AR/VR visual perceptions has been scaled up by recently launched cloud rending services that utilize utility GPU processing farms. All these developments have matured computer vision for production enterprise applications. The Hive focuses on business applications of computer vision in eCommerce, autonomous navigation, logistics & transportation, enterprise automation and industrial services & process management.
The late 2000s saw massive consolidation of compute capacity through the rapid growth in utility cloud computing for consumer and enterprise applications. This trend has been counter-balanced by the large-scale deployment earlier this decade of intelligent compute devices on a person (phones, wearables), and Internet of Things in homes, workplaces and industrial sites. This has led modern consumer and IoT applications to go beyond a cloud-only deployment model to utilizing compute resources available at the Edge of its interface with the clients. The key advantages of such edge intelligence include better economics of data transmission (specially in high-volume, high-velocity scenarios), enhanced data security & privacy features, real-time responsiveness, ability to capture context from ambient physical environments (called “ambient intelligence”), and higher levels of business continuity (due to distributed service deployment). Applications of edge intelligence (in different contexts also known as Ambient Intelligence or Fog Computing) in industrial operations, smart-infrastructure and datacenter operations will continue to be one of key focus areas for The Hive. Past co-creations within The Hive have explored applications of Edge Intelligence in Industrial IoT (FogHorn), IoT security (Sensify Security) and consumer IoT (Snips).
The post-2008 world has seen a severe regulatory clampdown and increase in overhead of compliance on businesses. Blockchains present a new information system that manifests multilateral trust & transparency. These are decentralized systems of record or distributed ledgers, which can efficiently enforce multilateral consensus between all counter-parties on every transaction recorded. Core systems in today’s enterprises use relational databases with unilateral consensus across a given institution, and deploy reconciliation, settlement and audit services to build consensus across institutions. Blockchains break down these large batch services by systemically incorporating them in a digital protocol based consensus that includes all counterparties and stakeholders of the transaction. Blockchain protocols also build redundancy to tolerate malicious counterparties within pre-designed threshold limits. The Hive is exploring business applications built on blockchain networks addressing usecases in financial services, insurance, commerce, supply-chain management and industrial operations.
Context computing anticipates user needs by leveraging real-time data streams on people, places and things with the corpus of historical data to proactively offer better customer experiences. Context computing uses "in the moment" data corresponding to the current user situation such as actions, behavior, emotion, location, etc. as well as user intent to make better predictions. Context aware computing is receiving increased attention in social media and advertising, mobile and wearable devices, and also the enterprise.
The cognitive enterprise is the hallmark of enterprise automation; wherein both operational and strategic decision-making can be automated from artificial intelligence (AI) based extraction of high-level inferences from transactional and operational data. This disruptive generation of cognitive systems is paradigm shifting in terms of their relationships with processes and people in the enterprise. Cognitive systems are taking over enterprise decision-management and are geared to deliver business outcomes with unprecedented levels of consistency, predictability and quality. Cognitive systems will also be able to define processes and navigate through decisions through their deep understanding of patterns in data & autonomy in consuming enterprise’s resources. The role of people in enterprises is shifting from decision-management to policy management.
The Hive has co-created startups that are creating cognitive systems for automation of enterprise services
Autonomous agents are shaping the future of enterprise process delivery and define modern interfaces between people & processes in the enterprise. Enterprise processes are being transformed from being people-led to being driven by autonomous agents. Agents bring large-scale asynchronous communication between people (customers, partners, employees) and enterprise processes, while delivering business outcomes with greater predictability & precision. Agents can adapt processes to scale collaborations between people dispersed across organizations and geographies. Adoption of autonomous agents began a few years back for modern agile application development & deployment processes (called “ChatOps”); it is geared to bring sweeping disruption across other functions including IT service, customer support, sales & marketing, supply-chain management & procurement et al. It is also very relevant in verticals that are heavy on people-led processes like financial services, insurance, credit, healthcare, and legal services.The Hive is focused on co-creating specialized autonomous agents with deep competencies in enterprise business functions and specific verticals.
The Internet of Things (IoT) is often dubbed as the fourth industrial renaissance owing to the wide scale disruption it is bringing to smart machines & autonomous operations, product lifecycle management, asset financing, service & support, and business models for utilizing assets. It is bringing a new class of industrial cyber-physical systems that offers unprecedented levels of agility and operational capabilities. At its core, industrial operations are transforming into consumption of an agile portfolio of software applications, cloud/edge services and entitlements that can be distributed and deployed non-intrusively. Furthermore, the ability to capture and analyze large volumes of machine data brings new capabilities to respond to changes, decision-making and interacting with the ambient physical environment. The combination of these two competencies is driving business disruption in aviation, transportation, manufacturing, logistics, energy, and other sectors. The Hive has been active in the IoT market since 2013 and has developed and funded startups for the Industrial Internet based on artificial intelligence and data technologies. They include startups that provide a platform for monetization & business operations, edge intelligence and edge security services.
The ubiquitous access to mobile platforms combined with the behavioral changes of the millennial generation is redefining aspects of interaction and transaction in commerce & consumer financial services. The new generation of consumers is showing a strong preference towards consuming services like retail, payments, and banking in the form of conversational sessions with human or non-human autonomous agents. This makes these services immersive in the consumers’ social fabric creating a collaborative consumption experience. The experience is further enriched by context that flows freely through the conversations. The major mobile platforms have released strong conversational agent frameworks to facilitate the same seamlessly.
The rapid growth of the global digital economy over this decade has brought unprecedented relevance and priority to cybersecurity. This has burdened enterprises’ cybersecurity efforts with exploding costs & complexities skewing the economics of cyber-attacks in the favor of adversaries. The Internet of Things is bringing a new generation of low-cost and low-energy endpoints, expanding the attack surface and vulnerabilities. Fortunately, advancements in artificial intelligence and blockchain technology platforms hold the promise to tilt the balance away from the adversaries. Applications of AI can drive deeper automation of security operations, and cover a wider scope of incidents, alarms & systems per unit of human scrutiny. Blockchain platforms offer the ability to interoperate securely with systems and users with requiring .expensive trust frameworks
ADVISORS & INVESTORS
WHAT OTHERS ARE SAYING
“Augmented Pixels, a startup featured in The Pitch last fall, has raised $1 million in seed funding and moved into The Hive enterprise accelerator.”
“On the surface, The Hive looks like a conventional Silicon Valley incubator. It provides funding, networking, and advice to early stage startups.”