Skip to Content

Seven Must-Read Stories (Week Ending June 4, 2016)

Another chance to catch the most interesting, and important, articles from the previous week on MIT Technology Review.
June 3, 2016
  1. Plan to Fabricate a Genome Raises Questions on Designer Humans
    What will scientists do with $100 million to mass-produce genes in the lab?
  2. How Dirty Is Your Air?
    What one family learned from using a $200 air-quality sensor for a month.
  3. Why Autocorrect for Passwords Is a Great Idea
    Letting people into their online accounts even when they mistype their password could make life easier without compromising security.
  4. Six Months after Paris Accord, We’re Losing the Climate-Change Battle
    A new report from the International Energy Agency includes projections for reductions in energy use and carbon dioxide emissions that could be wildly optimistic.
  5. Monsanto Cultivates a Rose That Doesn’t Wilt
    New advances in biotechnology could keep your flowers in bloom longer.
  6. How Alexa, Siri, and Google Assistant Will Make Money Off You
    While helping us get things done, virtual assistants will also give tech companies valuable new insights into our lives.
  7. Should We Let Internet Companies Define How We Express Ourselves?
    Facebook and Twitter, among others, have agreed to enact a more stringent way of policing hate speech on their platforms in Europe.
  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.