How AI and lab-on-a-chip pave the way for economical solutions.
We could be moving into the end game with the Covid-19 pandemic, at least as far as the severest effects are concerned. Clearly, the virus and its mutations are here to stay, and the future will be about protecting us through immunization and developing better treatments. The fact that effective vaccinations have become available only a year after the pandemic was recognized is remarkable. It’s partly due to the speed with which researchers have been able to do the data crunching needed to model and understand how best to attack the virus.
In the past, the computations involved in sequencing the virus DNA would have taken vast quantities of computer time and prolonged development of the vaccine. Cloud computing using AI accelerators has dramatically shortened the time to complete the technical work involved in creating the vaccines now being rolled out.
It would be great if we could harness our technologies to create an early warning system when clusters of unusual diseases or events occur anywhere in the world. That’s exactly what organizations like BlueDot are doing right now. Indeed, BlueDot says it spotted the cluster of unusual pneumonia cases in Wuhan in December 2019 that we now know was the coronavirus. To monitor the spread of infectious diseases around the world, it analyzes a huge number of variables, not only official public health data but also climate information, international travel patterns, animal and insect population data, and others. This relies on the ability of AI to detect patterns, and exceptions to those patterns, hidden within the enormous body of information. By sifting through the reports and data points collected every few minutes, 24 hours a day, from sources around the world, using techniques like machine learning and natural language processing, BlueDot brings a small number of cases to the attention of experts for further investigation. Only with AI do we have a hope of finding those cases.
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