DeepBrainz AI BRAIN, an AI R&D Unit
AI Research and Development (AIRD)
R&D for the SOTA AI
Deep Learning R&D for Innovation
Advancing cutting-edge AI
Product Innovation through cutting-edge R&D
Best Value from AI Technology Innovation
Delivering the best value from AI for Innovation
Advancing Tomorrow’s State of the art AI for everyone
We work on Artificial Intelligence and Computer Science problems that define tomorrow’s technology.
Our approach
DeepBrainz tackles the most challenging problems in Artificial Intelligence and Computer Science. Our team aspires to make discoveries that impact everyone, and core to our approach is to share our research and tools to fuel progress in the field. Our researchers will publish regularly in academic journals, release projects as open-source, and apply research to DeepBrainz products.
The Problems that DeepBrainz AI primarily focuses on solving are in/from the field of AI and Machine Learning by conducting cutting-edge AI research including the basic & long term research and fundamental applied research along with the product innovation and contribution.
Our Primary Research Focus Areas
We address the problems arise from the various challenges of Deep Learning, which is the emerging and popular sub-field of ML.
The AI Explainability and Interpretability
The difficulty of explaining in human terms results from AI models i.e explicability or interpretability of the large and complex (deep learning) models (i.e. explainable AI XAI).
The Bias in Data and Algorithms
The risk of the bias in data and algorithms that causes the unintended bias and the security threats in some important use cases, for instance, in healthcare and cybersecurity that are concerned more social in nature.
The Generalizability or Generalization of AI Learning
The generalizability of the learning i.e. generalization of the AI models continues to have difficulties in carrying their experiences from one set of circumstances to another.
The Labeling/Annotation of Massive Training Datasets
The challenges in labeling and annotation of massive training datasets which is crucial for supervised learning.
The Creation and Acquisition of such Massive Datasets
The difficulties of creating and obtaining such massive datasets that are sufficiently large and comprehensive.
Product-Domain Based Research
DeepBrainz Research for our products at DeepBrainz portfolio is for excelling in everything that it does.
Privacy, Security And Abuse Prevention
Applied AI Research
Basic AI Research
Future Long-Term Research Areas - I
Machine Intelligence, Machine Perception (Computer Vision), Natural Language Processing, Conversational AI, Speech Processing, Machine Translation, Data Management, Data Mining and Modeling
Future Long-Term Research Areas - II
Distributed Systems and Parallel Computing, Human-Computer Interaction and Visualization, Algorithms and Theory, Hardware and Architecture, Software Engineering, Software Systems, Robotics, Autonomous Driving, Artificial General Intelligence AGI
StartUs Insights' Innovator Guide
“Indian startup DeepBrainz AI develops an integrated end-to-end autonomous AI platform. Equipped with AI-first Software-as-a-Service (SaaS) with the edge AI services, their solutions find applications for autonomous healthcare, connected and level-5 autonomous driving vehicles, as well as conversational AI for enterprises and consumers. Moreover, DeepBrainz AI employs several techniques to develop their products, from transparency algorithms and autonomous meta-learning to all forms of machine and imitation learning.”
DeepBrainz AI R&D for AI Ethics, Policy, and Risk - IN A TECHNICAL REPORT by Global Catastrophic Risk Institute (GCRI)
“DeepBrainz’s AI R&D project, is in a Corporate-Humanitarian-Engaged On Safety Cluster, for engaging on AI Safety and Ethics… The project articulates the importance of the democratization of code, making AI research accessible to anyone… The project expresses interest in commercializing AI and marketing it as a product or business solution… The project new to the 2020 survey shows a range of stances on safety and explicitly focuses on potential long-term risks and presents thorough discussions of these risks and how to address them… The project seeks to commercialize AI as a means to other ends, such as benefiting humanity…” – in a technical report by Global Catastrophic Risk Institute.
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