DeepBrainz AI Research

DeepBrainz AI Research & Development (AIRD)

 

DeepBrainz AI BRAIN, an AI R&D Unit

AI Research & Development (AIRD)

R&D, Innovation to the SOTA AI

"AI For ALL" Via R&D, Innovation To Deep Learning

Cutting-edge (AI) Technologies

AI Product Innovation by Cutting-edge Technologies

Best Value from AI/Technology

Delivering The Best Value Via AI R&D & Innovation

Advancing Tomorrow’s State of the art AI for ALL

We work on Artificial Intelligence & 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
Our Near Future Long-Term Research Areas (Industry 4.O)

Machine Intelligence, Machine Perception, (Computer Vision), Natural Language Processing, Autonomous Driving, Healthcare (Health & Bioscience), Conversational AI, Robotics, Speech Processing, Machine Translation, Data Management, Data Mining and Modeling, Distributed Systems and Parallel Computing, Human-Computer Interaction and Visualization, Artificial General Intelligence AGI.

Other Future research areas

Algorithms and Theory, Education Innovation, Hardware and Architecture, Information Retrieval and the Web, Mobile Systems, Networking, Software Engineering, Software Systems, Quantum Computing, Blockchain, AR/VR, 3D Printing.

Reach Out To Us To Explore The Research Opportunity

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