Tag: Monitoring

OpenAI's ChatGPT is an AI-powered chatbot with various applications, but it comes with significant risks. Organisations must be aware of potential security issues such as employees inputting sensitive data. Hackers may also leverage ChatGPT for nefarious use cases such as writing clearer phishing emails. Snow Software technology can track ChatGPT usage, providing end-to-end visibility and minimising risk for businesses. Stay safe and secure with Snow Software.

A new study published in Scientific Reports found that a machine learning algorithm predicts a person's level of daytime sleepiness using electroencephalography (EEG) data. The algorithm was 88% accurate in predicting severe sleepiness, potentially leading to the development of non-invasive methods for diagnosing and monitoring sleep disorders like sleep apnea and narcolepsy. Dr. Lara V. Marcuse, the study's lead author, notes that further research is needed to verify these results.

Protect yourself from cyber-criminals using ChatGPT, a popular AI application. Meta, the parent company of Facebook, identified 10 malware families which spread malicious programs made to appear as if providing AI functionality. New security measures include appropriate support to detect & remove malicious software & actors. Stay vigilant & stay safe.

Mona Labs provides an easy and efficient OpenAI monitoring solution. With a single line of code, users can stay connected with their OpenAI usages. Their product, Mona-OpenAI, logs activities, parameters, and responses from the OpenAI server, helping users understand their calls better. It even has a "Get Rest Monitor" function to simplify logging. Porven by its powerful monitoring capability, Mona Labs is one of the leading companies in the industry.

This article outlines the use of machine learning and PALSAR-2 data to monitor changes in soil salinity. To ensure successful land management and conservation, a reliable, accurate method of detecting changing salinity was investigated. The study looked at the effects of polarization of backscattering from soil surface and used a Random Forest algorithm to extract useful information. Our results will help develop effective strategies for monitoring and managing of soil salinity and other land-use changes.