Why DeepBrainz
A Brief Note on DeepBrainz’s Innovation, Improvement & Scalability
DeepBrainz Technologies Private Limited (DeepBrainz), A DPIIT (DIIP) Recognized AI & Technology Startup Company, Member of Google Cloud Partner Advantage Program: Building, Advancing, and Democratizing Tomorrow’s State-of-the-art AI, Cutting-edge Technologies, “Empowering HUMANITY Universally!” via “AI for ALL”.
Mission: “Advancing, Building, and Democratizing Tomorrow’s State-of-the-art AI for ALL to Access, and Use, for Empowering Humanity Universally”
Vision: “AI for ALL is the key to Empowering Humanity Universally!”
Core Values: “Passion, Purpose, Determination, Curiosity, Innovation, Think Bigger, Move Faster, Work Smarter, Integrity, Inclusive Diversity, Focus Impact, Creativity of Fun & Cool Ideas, Emergent leadership, Make a Difference, Problem Solving, Effectiveness & Efficiency, Strategic Focus, Commitment, Disciplined Growth, Communication, Responsibility!”
And, these values are subject to change and evolve!
As AI is revolutionizing every industry and having a profound impact on Humanity, a greater impact than electricity and the most important thing humanity ever worked on and is fundamentally changing the way how everything works, DeepBrainz as A DIPP Recognised AI Company primarily focuses on working in the field of Deep Learning, which is part of a broader family of machine learning methods based on artificial neural networks.
DeepBrainz, A DPIIT Recognized AI Startup believes that AI Transformation can only occur when data, analytics & processes aligned across departments toward One Outcome, and developing & deploying a custom AI solution through strategic focus, a willingness to discover new ways to approach for our business, and a commitment to Innovation by implementing a custom AI solution & becoming an analytics-forward organization with an era of exponential change for our evolution which is now ready to begin.
We DeepBrainz have just started building MVP as “DeepBrainz Universal AI” that is for Entreprises such as Healthcare, etc., End Users (Consumers) & Developers. And, We’re exploring the best ML and Deep Learning Methods and will soon have Models in Production.
DeepBrainz Universal AI: A strategic, game-changing, high-level master project by R&D & Custom AI Algorithms Development
DeepBrainz Universal AI, is an AI Product as Platform, incorporates the services of Automated Large-Scale Machine Learning & Deep Learning for Computer Vision, NLP, Robotics with Ethical Policies, Open & Authentic Large-Scale Datasets Auto ML/Data Infrastructure for In-House AI Capability that provides AI-as-a-Service through Open, Authentic, Large-Scale or Massive Datasets as Unified Data Warehouse with Strategic Data Acquisition from AI/Data Strategies, “Empowering Humanity Universally” via “AI for ALL” Strategy & Policy.
Building DeepBrainz Universal AI, an AI Product as a Software, Infrastructure, Platform offers various Services for Everything from Building, Democratizing the State-of-the-art AI Developing AI i.e. AI Building AI itself for Enterprises, End-users, and Developers to Advancing Tomorrow’s State-of-the-art AI through Disruptive Innovations and is the strategic & game-changing master project with custom AI Algorithms Development with Hybrid AI Product Patterns of Computer Vision, Natural Language Processing NLP (Large-Scale Deep Learning), Next-In-Sequence Prediction, Collaborative Filtering via AI Canvas that focuses on advancing, building, democratizing Tomorrow’s Advanced State-of-the-art AI for the future DeepBrainz EthicalAGI (Auto-E-AGI) for Automated & Ethical Artificial General Intelligence and future Ethical Superintelligence EthicalASI.
We DeepBrainz AI who currently “Standing on the shoulders of giants” i.e follow the top AI giants in the global industry such as Google AI (https://google.ai), DeepMind AI, OpenAI.
We as DeepBrainz, with various strategies, OKRs & CFRs to solve the biggest, large-scale real-world & business problems across industries for everyone, using Computer Science and Artificial Intelligence particularly in the areas of Machine Learning/Deep Learning, Computer Vision, NLP and Robotics towards AGI (General AI) to deliver the highly unique solutions via Custom AI Algorithms Development for Products focusing Innovation such as “Universal AI” which is our scheduled Product concerning EthicalAGI (Auto-E-AGI), an automated General/Complete/Strong AI, as a Service, Platform, Infrastructure, will incorporate large-scale Auto ML/Data Infrastructure for In-House AI Capability that provides AI-as-a-Service via Cutting-edge Technologies such as Serverless Computing & Artificial Intelligence through Effective Serverless AI Engineering, and Strategic Data Acquisition as Open, Authentic, Large-Scale/Massive Datasets with Unified Data Warehouse, Deep Learning for Computer Vision, NLP, Robotics with Ethical Policies, that works toward future Ethical Superintelligence EthicalASI.
DeepBrainz’s Philosophies and Principles are yet to be accessible on the official site.
What are the problems DeepBrainz is solving?
The Problems that DeepBrainz primarily focuses on solving are in/from the field of AI and Machine Learning. We address the problems arise from the various challenges of Deep Learning, which is the emerging and popular sub-field of Machine Learning, are as follows:
- The Challenges in Labeling of training datasets which is crucial for Supervised learning,
- The Difficulties of creating and obtaining such massive datasets that are sufficiently large and comprehensive.
- The Difficulty of explaining in human terms results from AI models i.e. Explicability or Interpretability of the large and complex (deep learning) models.
- 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 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.
While being solved the above-said problems for advancing Tomorrow’s State-of-the-Art AI, DeepBrainz also aims to focus on Building an In-House AI Capability and Leveraging AIaaS (AI-as-a-Service) for Our Own AI-based Customized Product for Innovation that is being built to the Enterprises and Consumers to further address the problems from the various major important & potential use cases across the industries’ sectors, and functions especially High Tech, Healthcare, Automotive, Education, Agriculture, Retail through Cutting-edge Technologies such as Machine Learning for democratizing AI Technologies.
How does DeepBrainz propose to solve these problems?
The proposed solutions to the problems that DeepBrainz solves as follows:
- Using the promising new emerging techniques, for addressing the data labeling problem, such as Reinforcement Learning (Deep Reinforcement Learning), In-Stream Supervision, Unsupervised Learning;
- Developing a strategy to acquire massive datasets via say Data Strategy such as Strategic Data Acquisition, and Unified Data Warehouse;
- Achieving Explicability of AI Models through DeepBrainz AI Research for the explainability and interpretability of the AI/Deep Learning models;
- Developing the capability of such AI models using “Transfer Learning” to transfer knowledge to another domain, and Neural Architecture Search NAS;
- Solving Bias via DeepBrainz AI Research to end the Risk of Bias in Data & Algorithms by understanding how the processes used to collect training data can influence the behavior of models they are used to train.
We begin to build a complete in-house AI capability, AI-as-a-Service for DeepBrainz and Everyone. It’ll overcome the “last mile” problem of AI to deliver step-change performance with our key data engineering process, robust data maintenance and governance processes and modern software disciplines such as Agile and AnalyticsOps (Analytics + DevOps).
We also often consider redefining the followings whenever possible,
- Formulating the Data and AI use cases, based on business priorities;
- Understanding the current state of our Data and AI projects and enablers;
- Defining the Data and AI vision and the execution roadmap, including investments;
- Executing the first use cases aiming at production readiness;
- Scaling up operations.
While being done with the above solutions, we strictly have the strategic action plans for the execution to become the provider of AI technology, applier of AI technology, and policymaker, who sets the context for both.
Among several other tools and technologies being used at DeepBrainz, we, for now, make use of the open-source tools such as, “PyTorch & Ecosystems” for the Research in Deep Learning and another open-source tool such as, “TensorFlow & Ecosystems” for Deep Learning Models in Production. The other tools and technologies that are being used here at DeepBrainz will soon be announced after the release of the MVP i.e. Minimum Viable Product to the industry market.
We’re now moving from Ideation stage (i.e. the development of POC and Prototype for our viable product) to the Validation stage for MVP Development & Release as our product and service are to be built and released to the market at this current level and still working hard with core values and mission towards our vision to move to further stages of the startup such as Early Traction, and Scaling.
What is the uniqueness of DeepBrainz’s proposed solution?
As AI has the potential to create value across sectors and also the organizations across the world planning to adopt significant deep learning efforts, we as DeepBrainz do the following to have an Impact.
The uniqueness of our solution is that as our proposed solution is designed and developed in such ways that will help further solve the following crucial and challenging problems as follows:
- It solves the case with AI techniques and data available, where the value is clearly proven, but the cost and complexity of deploying AI are still daunting.
- It helps justify the cost and issues around privacy and personal identification, societal concerns, and regulations, as regulatory constraints are especially prevalent in use cases related to personally identifiable information from the use and commercialization of individual data on online platforms, the use, and storage of personal information are especially sensitive in sectors such as banking, health care, and pharmaceutical and medical products, as well as in the public and social sectors.
- It additionally addresses the cases, where the value is not yet clear, and the most unpredictable scenario is where either the data (both the types and volume) or the techniques are simply too new and untested.
As the solutions further address these issues, businesses and other users of data for AI will need to continue to evolve our business model related to data use in order to address societies’ concerns, as regulatory requirements and restrictions can differ by the countries and the sectors.
And the Uniqueness of the proposed solution is to further deliver many solutions to the several other problems to be solved in the world.
How does DeepBrainz generate revenue?
While coming to generating revenue and Marketing Strategies such as B2B, B2C, and B2D which are being utilized in accordance with the use-cases, DeepBrainz will aim to solve for the enterprises, the consumer, and the developers respectively.
The business revenue models evolve and change over the use of data for AI. As the AI Landscape can be divided into two segments in the following:
- Infrastructure: We’re planning to run in the back-end and provide computational services to others. For such cases, the business model, we plan to follow will be generally based on API calls.
- Application: We do plan to have applications in the B2B and B2C space, then later in B2D. Significant activity, however, is seen in the B2B space where we also plan to offer SaaS-based subscription services, while some may end up being purchased by important firms after several proofs-of-concept.
We additionally do plan for the development of a tailored-made solution and then make you pay monthly running costs as well as operational support/training, as we are also an AI development team specialized in building tailored-made solutions for clients.
We do plan to provide the data necessary to build the PoC. It’s the known fact, “The more people using AI, the faster it learns.”
AI solutions are priced by transaction or completed computation via Serverless Computing. You’ll be required to pay as much as you use AI i.e. “Pay-as-you-go” method.
We are still working for an entirely new ecosystem and emerging business model.
