Diveplane GEMINAI is the DMP Industry’s First Verifiable Synthetic ‘Twin’ Dataset
Global provider of Explainable AI software product, Diveplane announced the availability of GEMINAI, the industry’s first verifiable synthetic ‘twin’ dataset. Diveplane GEMINAI empowers businesses and government organizations to easily and safely sell, share and analyze sensitive datasets without the fear of mishandling, loss or theft.
Twin Data Sets and Their Modeling
Diveplane’s latest productcreates a verifiable synthetic ‘twin’ dataset with the same statistical properties of the original data, but without including the real-world confidential or personal information. Users can leverage AI-based GEMINAI to freely navigate through National & International privacy laws e.g. GDPR, PHI & HIPAA. For example, GEMINAI could generate “synthetic patients” with specific medical conditions who fit certain demographic profiles, all without the PHI from your original data set.
The ‘twin’ dataset looks, acts, and feels realistic for the purposes of data modeling and analysis, but does not contain any personally identifiable information (PII), which is critical for businesses that need to adhere to national and international privacy laws and compliance requirements, like GDPR, PHI and HIPAA.
“We love seeing AI increasingly adopted by many industries, but we’re finding that not all AI is created and trained equally,” said Dr. Michael Capps, CEO of Diveplane.
Michael added, “Many businesses are forced to use inaccurate or incomplete data to train their AI due to privacy requirements, which can lead to the AI making poor or misleading decisions. With GEMINAI, we’re eliminating that risk by creating a verifiable synthetic ‘twin’ of the dataset, so that businesses don’t need to sacrifice the quality of their AI for the sake of privacy. GEMINAI offers the best of both worlds and we’re excited to introduce this first-of-its-kind technology to the market.”
GEMINAI is a completely unique and better solution to a longstanding AI problem – the balance between privacy and data accuracy.
How Customers Could benefit from Explainable AI
GEMINAI goes beyond simply masking certain slices of information, like name and social security numbers, which can leave the data vulnerable to misuse or mishandling.
GEMINAI can be used to:
Assist with medical research efforts. Imagine the potential if a hospital was able to share its truly anonymized patient records with nonprofits and research universities, in an effort to rapidly advance the medical field and save more lives. GEMINAI can create those anonymized records so medical organizations do not need to worry about breaching HIPAA.
Secure the multi-billion dollar data sharing industry. Data is being shared and sold at an incredible rate, and rarely do organizations take the extra step to de-identify their datasets. GEMINAI easily creates synthetic data that does not contain any personally identifiable information, so there is no danger of unintentionally revealing an individual or entity if the information gets into the wrong hands.
Generate the appropriate data needed to train neural network systems. AI runs on data but often there isn’t enough data, or enough of a specific profile, to ensure that it is accurately performing. GEMINAI provides those datasets needed to ensure a true representation and improve AI functionality.
Diveplane was founded in 2018 to fix AI’s credibility problem. The company believes that to have responsible AI, the market needs understandable AI that is trainable, interpretable and auditable. GEMINAI is the first product that the company is introducing to the market and the technology has already been named a finalist in the UBS Future of Finance Challenge 2019.
Diveplane has seen significant growth and interest from the market, growing its team across all departments within the business. The company also continues to build out its impressive C-suite, including CEO Dr. Mike Capps and CTO Dr. Christopher Hazard, and they’ve recently welcomed Alan Cross as CCO.
“We’ve been scaling our sales and marketing efforts significantly due to the momentum we’re seeing in the market, which is why it was critical for us to bring on Alan as our Chief Commercial Officer,” added CEO Michael Capps.
Michael concluded, “It’s cool that neural networks can beat the best humans at board games, but when you start thinking about machines making life-altering decisions it requires a much more serious and thoughtful approach that can be thoroughly audited and understood. It’s critical that humans are able to understand why AI makes the decisions that it does and also ensure that the AI is learning based on authentic, unbiased datasets – which is exactly the reason we founded the company.”
Diveplane is keeping the humanity in artificial intelligence (AI). The company was founded by Dr. Michael Capps, former President of Epic Games, in 2018 and develops technology that helps businesses and government organizations understand AI with a trainable, interpretable and auditable. Diveplane headquartered in Raleigh, North Carolina.