Firefly Neuroscience Inc. saw its actions increase by more than 31% on Monday following the announcement of its new Claire platform powered by NVIDIA GPU L40S technology. The AI neuroscience company has unveiled significant treatment improvements that could accelerate the discovery of brain biomarkers and improve clinical information for neurological and mental health disorders. Trading at $ 3.40 From the editorial time, the action has grown after months of partnerships with the technological giant via their Connect program.
Nvidia Partnership offers an increase in major performance for the Firefly Claire platform
The new Clear (Cleaning EEG Artefacts) platform of Firefly represents a breakthrough in brain waves analysis technology, resolving one of the greatest challenges of neuroscience research. EEG recordings, which measure electrical activity in the brain, are notoriously difficult to work due to the interference of muscle movements, flashes and environmental noise. The platform uses advanced signal treatment and automatic learning to filter these artifacts, providing researchers with cleaner and more reliable brain data.
By taking advantage of the NVIDIA L40S GPU L40S with the Architecture Ada Lovelace, Firefly has reached treatment speed improvements from 60 to 80% compared to previous methods. This means that researchers can analyze data from brain waves much faster while retaining high quality standards. For a company working with the largest standardized EEG database in the world containing more than 17,000 patients, these efficiency gains result in significant competitive advantages in the race to develop brain biomarkers for various neurological conditions.
The partnership with Nvidia extends beyond the equipment, because Firefly was accepted in the Nvidia Connect program earlier this year. This collaboration positions the company to continue to advance its artificial intelligence capacities and potentially develop what managers call a “basic model of the human brain” – essentially a complete AI system formed on large quantities of brain data to detect the models associated with different …
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