DarwinAI Announces Explainability Platform for Neural Network Performance
First Version of Explainability Toolkit Now Available to Select Enterprise Customers via Darwin’s Generative Synthesis Platform
DarwinAI, a Waterloo, Canada startup creating next-generation technologies for Artificial Intelligence development, announced the next milestone in its product roadmap with the release of its explainability toolkit for network performance diagnostics.
Based on the company’s Generative Synthesis technology, this first iteration of the tool provides granular insights into neural network performance. Specifically, the platform provides a detailed breakdown of how a model performs for specific tasks at the layer or neuron level. This deep understanding of the network’s components and their involvement in specific tasks enables a developer to fine-tune the model designs for efficiency and accuracy.
The introduction of explainability comes two months after the company announced its emergence from stealth, its Generative Synthesis platform, and $3 million in seed funding, co-led by Obvious Ventures and iNovia Capital, as well as angels from the Creative Destruction Lab accelerator in Toronto.
“Understanding network efficiencies at such a granular level is how our platform is able to achieve such fantastic optimization results,” said Sheldon Fernandez, CEO of DarwinAI. “With our explainability tool, we are now surfacing this information to our clients, which allows them to better fine-tune their networks for specific tasks. All this is made possible by our patented Generative Synthesis technology, which scrutinizes deep neural networks using AI itself.”