Despite the rising demand, most computer programmers and data scientists lack the specialized knowledge and tools required to build deep learning software solutions for their organizations. To address this, DimensionalMechanics™, launched its next-gen NeoPulse™ Framework 2.0, and an easy-to-use programming language, called NML 2.0, to make artificial intelligence (AI) more accessible to any software developer.
The company also announced it closed its A-2 round with $1,249K. The Company converted $4,220 of debt to Preferred Stock and closed on an incremental $1,249k raise for a total round of $5,469k Friday, April 6th bringing the total raised to $7.9 million.
NeoPulse Framework 2.0 enables organizations to solve the most complicated AI challenges at a fraction of the time and cost using current methods or developing their own solutions in-house. Many organizations have vast quantities of structured and unstructured data, but lack the capabilities to convert the data into organizational assets or intelligence. Leveraging NeoPulse Framework 2.0 and DimensionalMechanics methodologies, organizations can build sophisticated AI solutions based on all data types – video, numerical, text, images or audio.
According to Gartner’s “2018 Will Mark the Beginning of AI Democratization,” a survey of 3,160 CIOs view making progress with AI initiatives as one of their top-five priorities for 2018. “In 2018, organizations will strive to improve their understanding of what AI is best suited to, and how to deploy it,” says Chirag Dekate, research director at Gartner. “By 2020, 85% of CIOs will be piloting AI programs through a combination of buy, build and outsource efforts.” The post goes on to say, “However, CIOs will have to overcome challenges. Many are dealing with data of poor or uncertain quality. Their organizations often have minimal AI skills. Some CIOs are struggling to understand the capabilities of new AI techniques, and how to identify use cases to which AI may be applied productively.”*
With NeoPulse, our AI builds your AI,” said Rajeev Dutt, CEO of DimensionalMechanics. “We’ve created a platform for AI development that lets developers of all skill levels rapidly answer data-driven questions using a cost-effective and repeatable approach. Our NML language is purpose-built for deep learning, yet easy enough to learn in just days. Developers can now create AI models in a fraction of the time and cost than was ever possible before. Our versatile platform and software tools can be used across any industry and any data types, and provides CIOs with a common AI platform for use throughout their organizations. We’re confident that our next-gen NeoPulse can help accelerate the adoption of machine learning for organizations of all sizes and technical capabilities.”
NeoPulse Framework 2.0: Simplifying AI
NeoPulse Framework 2.0 gives developers the power to create custom AI models to answer real-world business questions, based on their own data, without being machine learning (ML) experts themselves. And, for those with ML expertise, it can dramatically reduce the amount of code required to create AI models by up to 85%. NeoPulse Framework 2.0 consists of four main elements:
- NeoPulse Modeling Language 2.0 (NML) is an intuitive DSL (domain specific language) that fully automates the creation of new AI models to tackle common ML problems (e.g. classification, regression, etc.) regardless of data type (e.g. video, audio, images, etc.). The language is Turing-complete and can accomplish in dozens of line of code what in conventional languages (e.g. Python) would take hundreds of lines of code. A programmer can learn NML in a matter of days with a simple command line interface that is executed by NeoPulse AI Studio, and add their own ML algorithms.
- NeoPulse AI Studio 2.0 is an AI that builds AI. This AI-as-a-service is a server-based application, powered by its own robust AI, dubbed “the oracle,” that helps automate the process of creating custom AI models. The most significant advancement in the new NeoPulse Framework 2.0 is the addition of next-gen hyperparameter optimization, which significantly outperforms conventional Bayesian optimization approaches. Instead of relying on ML experts for the difficult tasks of identifying key parameters needed for data analysis, AI Studio’s “oracle” is able to set those hyperparameters when programmers either do not know how, or are not inclined to do so. This advancement also means that AI Studio is typically able to outperform ML experts attempting to solve the same problem.
- Portable Inference Models (PIMs) are portable AI models, created by NeoPulse AI Studio 2.0 that can be deployed across different computers, either locally on-premise or in the cloud. The files are containerized artificial neural networks that can be queried using a runtime layer.
- NeoPulse Query Runtime 2.0 (NPQR) is a simple program that allows any application to access the AI models (PIMs) using web-based REST APIs.
DimensionalMechanics gives organizations the versatility to have their AI solutions in the cloud or on-premise. NeoPulse Framework 2.0 is available via cloud deployment, with NeoPulse AI Studio and NeoPulse Query Runtime, downloadable within Amazon Web Services (AWS) Marketplace. An on-premise version of NeoPulse Framework 2.0 is expected to be available later this year.
DM on AWS was easy to implement and works flawlessly. Their technology integrated right into our existing data and AI pipelines which is often a major barrier to an AI strategy,” said Tony Kippen, VP of Business Intelligence, Limeade.
DimensionalMechanics is currently working with Fortune 500 companies within the media and entertainment industry for use in a variety of applications such as: event recognition within video (e.g. when a goal or basket is scored in a sporting event); predicting which images/headlines are likely to generate more user engagement; network pattern anomaly detection; image/text/audio/video analysis; and much more. However, the company also expects to serve a wide range of industries including: infrastructure, medical, education, and many others.
*Smarter with Gartner, 2018 Will Mark the Beginning of AI Democratization, December 19, 2017
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