I’ve been exploring the possibility of developing a live, AI-assisted intelligence-gathering and analysis system focused on Reddit’s UFO/UAP communities, and I’m interested in connecting with people who have experience in programming, data science, OSINT, machine learning, or network analysis. The objective is straightforward: Can we use publicly available Reddit data to systematically identify patterns of coordinated inauthentic behavior, automated engagement, and potential narrative manipul...

🚨THE UFO AND NUKES CONNECTION JUST GOT HARDER TO IGNORE Team VASCO has now had another paper pass peer review, and the result is exciting! One of the biggest [Quoted] Double trouble -- our peer-reviewed machine learning/transient paper has also just been published. This is where we clean up the sample and see that the fewer contaminants there are, the stronger the correlation with nukes and the larger the shadow deficit. It also shows that the correlations with nukes is strongest 24 hours be...

[Retweeted] Double trouble -- our peer-reviewed machine learning/transient paper has also just been published. This is where we clean up the sample and see that the fewer contaminants there are, the stronger the correlation with nukes and the larger the shadow deficit. It also shows that the correlations with nukes is strongest 24 hours before a nuclear test. Link: https://t.co/1vJ4jY1FvU

[Retweeted] Double trouble -- our peer-reviewed machine learning/transient paper has also just been published. This is where we clean up the sample and see that the fewer contaminants there are, the stronger the correlation with nukes and the larger the shadow deficit. It also shows that the correlations with nukes is strongest 24 hours before a nuclear test. Link: https://t.co/1vJ4jY1FvU

When I read this part: "It also shows that the correlations with nukes is strongest 24 hours before a nuclear test," I'm reminded about how the tic-tac UAP knew [Quoted] Double trouble -- our peer-reviewed machine learning/transient paper has also just been published. This is where we clean up the sample and see that the fewer contaminants there are, the stronger the correlation with nukes and the larger the shadow deficit. It also shows that the correlations with nukes is strongest 24 hours...

[Retweeted] Double trouble -- our peer-reviewed machine learning/transient paper has also just been published. This is where we clean up the sample and see that the fewer contaminants there are, the stronger the correlation with nukes and the larger the shadow deficit. It also shows that the correlations with nukes is strongest 24 hours before a nuclear test. Link: https://t.co/1vJ4jY1FvU

[Retweeted] Double trouble -- our peer-reviewed machine learning/transient paper has also just been published. This is where we clean up the sample and see that the fewer contaminants there are, the stronger the correlation with nukes and the larger the shadow deficit. It also shows that the correlations with nukes is strongest 24 hours before a nuclear test. Link: https://t.co/1vJ4jY1FvU

Double trouble -- our peer-reviewed machine learning/transient paper has also just been published. This is where we clean up the sample and see that the fewer contaminants there are, the stronger the correlation with nukes and the larger the shadow deficit. It also shows that the correlations with nukes is strongest 24 hours before a nuclear test. Link: https://t.co/1vJ4jY1FvU

A molecule’s shape can carry information that its chemical formula does not. Two amino acids may contain identical atoms yet arrange them as mirror images, a distinction that matters when scientists examine possible traces of life. Researchers at the University of Osaka have developed an electrical method for reading that molecular handedness one molecule at a time. Their system combines atomically pointed gold electrodes with machine learning to interpret the signals produced as molecules en...

RT @DrBeaVillarroel: Dear everyone, Some new and very exciting news from the VASCO team! First, our machine-learning paper has been accepte…