New AI framework autonomously optimizes training data, architectures and algorithms — outperforming human baselines

EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...
Forbes

Understanding Data Encryption: Types, Algorithms And Security

Ofer A. Lidsky is an entrepreneur with over 30 years of experience and is the founder and CEO of Excellent Brain. In today’s digital age, data encryption is vital for protecting sensitive information.
TMCnet

MicroAlgo Inc. Develops Quantum Algorithm Technology for Feedforward Neural Networks to Drive Neural Network Revolution

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced that they have developed a set of quantum algorithms for feedforward neural networks, breaking through the performance ...
Science Daily

New method efficiently safeguards sensitive AI training data

Researchers devised a way to maintain an AI model's accuracy while ensuring attackers can't extract sensitive information used to train it. The approach is computationally efficient, reducing a ...
ascopubs.org

Development of Machine Learning Algorithms Incorporating Electronic Health Record Data, Patient-Reported Outcomes, or Both to Predict Mortality for Outpatients With Cancer

shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area We trained and validated two-phase ML ...
ascopubs.org

Novel Algorithm for the Estimation of Cancer Incidence Using Claims Data in Japan: A Feasibility Study

We developed two algorithms to identify patients with stomach, lung, colorectal, breast, and cervical cancers: diagnosis only (algorithm 1), and combining diagnosis, treatments, and medicines ...
JD Supra

Pricing Algorithms - Price Tags and Personal and Competitor Data: States Step Up Algorithmic Pricing Regulation

As price-setting by computer algorithm becomes increasingly prevalent, states are stepping in to address transparency and fairness concerns that federal legislation has yet to comprehensively tackle.