2020’s Breakthrough Technologies According to MIT

by Ruth Seeley

For most of the 21st Century, the annual MIT Breakthrough Technologies list has identified key tech developments, the ones that will have the biggest impact on our lives and shape our futures.

2020’s list – one of the publication’s most popular features – is out, and MIT Technology Review has also launched a four-part podcast to conduct a deep-dive into some of the technologies featured on the 2020 list.

This year’s 10 Breakthrough Technologies range in subject matter from AI to quantum computing to medicine and health care. They are:

  • Satellite mega-constellations: We can now affordably build, launch, and operate tens of thousands of satellites in orbit at once.
  • AI-designed molecules: Scientists have used AI to discover drug-like compounds with desirable properties.
  • Tiny AI: We can now run powerful AI algorithms on our phones.
  • The quantum internet: Later this year, Dutch researchers will complete a super-secure quantum internet connection between Delft and the Hague.
  • Climate-change attribution: For the first time, researchers can confidently determine whether climate change is driving a specific extreme weather event such as a hurricane, as opposed to just making such events more frequent in general.
  • Hyper-personalized medicine: Novel treatments are now being designed to treat even genetic mutations unique to a single person.
  • Anti-aging drugs: The first drugs that treat ailments by targeting a natural aging process in the body have shown success in human tests.
  • Quantum supremacy: Google has provided the first clear proof of a quantum computer outperforming a classical one.
  • Digital money: The rise of digital money — not cryptocurrencies, but digital versions of national currencies like the Chinese renminbi — will threaten people’s ability to transact in private; it could challenge America’s dominance over the global financial system.
  • Differential privacy: This cutting-edge mathematical technique precisely measures how the privacy of a dataset changes when noise is injected. Already used by consumer tech companies, it will be used in the 2020 Census to protect the identities of 330 million Americans.

Source: MIT Technology Review

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