Skip to Content

Seven Must-Read Stories (Week Ending July 26, 2014)

Another chance to catch the most interesting, and important, articles from the previous week on MIT Technology Review.
  1. Can Technology Fix Medicine?
    Medical data is a hot spot for venture investing and product innovation. The payoff could be better care.
  2. No Man’s Sky: A Vast Game Crafted by Algorithms
    A new computer game, No Man’s Sky, demonstrates a new way to build computer games filled with diverse flora and fauna.
  3. Urban Jungle a Tough Challenge for Google’s Autonomous Cars
    It may be decades before autonomous vehicles can reliably handle the real world, experts say.
  4. Chinese Researchers Stop Wheat Disease with Gene Editing
    Researchers have created wheat that is resistant to a common disease, using advanced gene editing methods.
  5. Could “Force Illusions” Help Wearables Catch On?
    Researchers have made haptic interfaces that create the sensation of being pushed or pulled by an invisible force.
  6. More than a Hundred Genetic Variants Tied to Schizophrenia
    A multinational research collaboration has identified more than 100 genetic loci associated with an increased risk for the psychiatric disease.
  7. Super-Dense Computer Memory
    Researchers have discovered a new way to make chips that could pack terabytes into smartphones.
  8. <

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.