Tripling the impact of methane reducing feed additives with decentralized AI with Yaniv Altshuler MIT and Metha AI

The efficacy of methane reducing feed additives constantly varies between cows and herds because the rumen microbiome is constantly changing. Certain feed additives that worked really well at that one given her may stop working, or the other way around. Feed additives that were not working can become effective. Using AI based on the genome sequences within the microbiome so that the right additive is used at the right time can triple the impact of feed additives.

Yaniv Altshuler has been working on Artificial Intelligence for the over 20 years focusing on decentralized and scalable AI methods. He is a researcher at MIT and the founder and CEO of Metha.ai where he is using decentralized AI algorthims that are ubiquitous across nature to predict the efficacy of methane reducing feed additives based on the cows microbiome.

More details on how AI can increase the efficacy of feed additives can be found in Yaniv's white paper here:
From Microbes to Methane: AI-Based Predictive Modeling of Feed Additive Efficacy in Dairy Cows

Yaniv holds a PhD in Computer Science, and is the author of over 70 scientific papers and 15 patents. He is also the author of several books including "Security and Privacy in Social Networks" and "Applied Swarm Intelligence".

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