AI Will Have A Major Impact On Atoms, According To AI Analyst

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David Mattin, an Artificial Intelligence (AI) analyst, anticipates a transformative impact of AI on the functioning of proteins in the real world. He highlights a recent Google DeepMind breakthrough that has the potential to make significantly more discoveries than humans.

According to Mattin, AlphaMissense, which classifies missense variants, has the potential for scientists to reduce the occurrence of severe diseases.

AI Will Have A Positive Impact On The Realm Of Atoms

In a recent statement on X (formerly Twitter), Mattin emphasized the significance of AI’s potential to make a positive impact in disease prevention, by exploring atoms in the human body on a deeper level. Atoms of hydrogen, carbon, nitrogen, and oxygen compose roughly 99% of the human body.

“Some changes to protein function are benign. But some cause serious disease.”

In a statement from Google DeepMind on September 19th, it emphasizes that the repercussions of not detecting these issues early can be significant:

“Missense variants are genetic mutations that can affect the function of human proteins. In some cases, they can lead to diseases such as cystic fibrosis, sickle-cell anaemia, or cancer.”

This tool can reportedly help scientists identify disease-causing genetic mutations and explore new therapeutic avenues.

Positive Forecast for the Future of AI

It further highlights the significant gap between the findings of its AI model and those of human researchers:

“We show it categorised 89% of all 71 million possible missense variants as either likely pathogenic or likely benign. By contrast, only 0.1% have been confirmed by human experts.”

AlphaMissense Prediction Data Chart. Source: Google DeepMinds

Furthermore, AI tools accurately predicting variant effects can reportedly enhance research across various fields. These include molecular biology, clinical genetics, and statistical genetics.

The statement highlights the expense associated with uncovering disease-causing mutations. This is due to the uniqueness of each protein, necessitating the design of individual experiments.

Major investment bank Goldman Sach has recently expressed its optimistic view about AI, affirming its belief in the significant potential of AI stocks.

According to Goldman Sachs recent research, AI companies are delivering approximately 60% year-to-date returns. This has sparked concerns of an AI bubble due to concentrated gains.


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