In this video we will be discussing a contamination theory of the obesity epidemic, which is the theory that the large increase in obesity seen in the industrialized world since 1950 is largely caused by contaminants in our food and water. There has been a very dramatic increase in obesity since the 1950s that has accelerated since 1970. In the 1800s the average U.S. man weighed 155lbs (70kg) while today in 2021 he weighs 195lbs (88kg). One possible explanation is that we evolved for an environment without widely available high calorie food, and now eat too much of them. However, in my opinion the evidence better supports contamination as a larger cause. Modern hunter gatherers eat a wide range of diets, often without much variety, and consistently have healthy weights. Some eat large amounts of carbs, others proteins and fats, but they don’t have anywhere near the level of obesity seen in industrialized countries today. Additionally, immigrants to the United States from less industrialized countries generally have lower rates of obesity when they arrive, but become more obese while living in America. The obesity epidemic isn’t just in humans either, wild animals, lab animals, and zoo animals have all gotten fatter even under controlled lab or zoo conditions. Obesity can be induced in lab rats by feeding them a diet of highly processed and palatable human food. Notably higher altitudes are correlated with lower rates of obesity. One possible explanation for this correlation is that contaminants build up in the water supply as they flow downstream. Comparing the rates of obesity geographically in the United States, obesity increases as you follow the Mississippi watershed from the mountains in Colorado, with one of the lowest obesity rates, to the Mississippi’s mouth in Louisiana, one of the most obese states in the nation. Many believe that carbs or sugar cause obesity, however U.S. carbs and sugar intake have decreased since 2000 while obesity has continued to increase. The question then is what contaminants could be causing this? There are a number of theories including Lithium, livestock antibiotics, PFAS chemicals in industrial use, Glyphosate in herbicides, or a combination of contaminants. We would expect the relevant contaminants to have increased since 1950, and dramatically increased since 1970. Lithium fits this description, and is known to cause obesity when ingested in sufficient quantity, but there isn’t conclusive evidence for any individual contaminant. If this is true then what can be done? Since it isn’t known exactly what is causing the obesity epidemic it’s hard to say, but trying to reduce likely contaminants is probably a good strategy. Highly processed food is designed by food manufacturers to be addictive, causes obesity in lab rats, and potentially picks up more contamination with more processing. Replacing processed foods with unprocessed ones like potatoes, fruits, vegetables, and nuts would likely reduce contamination among other health benefits. Contaminants could also bioaccumulate in animals so eating less or higher quality meat may reduce contaminants, and vegetarians currently have lower obesity rates then the general public. Drinking distilled or purified water or getting water from a high elevation close to it’s source could reduce potential contaminants in drinking water. Finally, living in an area with a lower obesity rate could reduce contaminants and socially expose you to healthier habits. For more information I recommend reading Slime Mold Time Mold’s writings on this subject, which curates the current research in a digestible format. https://slimemoldtimemold.com

Translating tags at inference with tag injection in Argos Translate. Links: https://github.com/argosopentech/argos-translate https://github.com/argosopentech/translate-html https://github.com/argosopentech/argos-translate/commit/56db272d775794d7fac2c0ae547100a899dc9067 https://www.argosopentech.com https://forum.opennmt.net/t/suggestions-for-translating-xml/4409/6 https://github.com/argosopentech/argos-translate/discussions/100 Creative Commons CC0

2008 Wikipedia Archive https://2008pedia.xyz https://github.com/argosopentech/2008pedia

In this video I train a custom language model for translation using Argos Train. This model can then be used with OpenNMT, Argos Translate, or LibreTranslate. https://github.com/argosopentech/argos-train Steps: 1. Download and package custom data 2. Rent a GPU from Vast.ai 3. Run Argos Train 4. Download trained model