Lily Nelson
Using AI to Fight Wildfires -- Prevention, ...

In a world overshadowed by the rapid deterioration of its climate, AI engineers are beginning to apply machine learning technology to issues of environmental justice and crisis. In California, where wildfires have ravaged over 570,000 acres of land and forced 41,000 evacuations already this summer, AI is being used to prevent and monitor forest fires throughout the state.

Using AI to Fight Wildfires -- Prevention, Detection, & Monitoring with Computer Vision

machine_learning

DeepSeek, Cost-Effective AI, and the Path to AGI: A Conversation with one of Xyonix's Principal Data Scientists

DeepSeek, Cost-Effective AI, and the Path to AGI: A Conversation with one of Xyonix's Principal Data Scientists

When DeepSeek claimed to have trained a top-tier AI model for a fraction of the usual cost, the tech world took notice—but was it truly a breakthrough, or just clever marketing? With unprecedented transparency and bold promises, DeepSeek challenged the norms of AI development, sparking excitement and skepticism alike. In this article, Xyonix’s Marketing Coordinator, Jessie Dibb, sits down with AI expert Carsten Tusk to cut through the noise, separating fact from hype and unpacking what it means for the future of AI.

Filling in the Gaps: AI-Powered Data Imputation Using Autoencoders

Filling in the Gaps: AI-Powered Data Imputation Using Autoencoders

Missing data can disrupt machine learning workflows, but imputation can help fill in the blanks to keep your models on track. Autoencoders, a type of neural network, excel at reconstructing data by learning complex patterns, outperforming traditional methods like random forest imputation. In our experiment on housing data, autoencoders reduced errors by 3-6 times across features, proving their effectiveness in handling intricate feature relationships. This makes them a powerful tool for imputation and beyond, with applications in denoising, feature extraction, and anomaly detection.

Using AI to Predict Influenza, C19 and Other Infectious Disease Rates

AI can be used to generate regional forecasts of infectious disease rates that, in turn, empower government and other leaders to make prudent social distancing and other preemptive modifications. As a case study, we will look at influenza data supplied by the Centers for Disease Control. Our goal is to use ILI data to train a model that will accurately predict future seasonal flu levels.