With this difficulty, we wished to have fun our milestone as a publication with out dwelling an excessive amount of on our personal previous. Victory laps are for race vehicles, not magazines. As an alternative, we determined to attempt to use historical past as a method to discover what issues might appear like over the subsequent 125 years.
The longer you report on tech, the extra you understand how usually we get the long run mistaken. Predictions have a manner of not coming true. The issues that appear so clear now can shift and alter, rearranging themselves into wholly new types we by no means considered.
But additionally, predictions that we snigger off as having been so mistaken usually have a manner of coming true ultimately. All through this newest version of MIT Know-how Overview you’ll discover a few of our greatest bets as to what the long run might maintain. We might not get it precisely proper, however we predict we’re not less than pointing towards the place issues are headed.
Right here’s a choice of among the most fascinating tales from the journal:
+ What the long run and its rising applied sciences maintain for these born at the moment, from clever digital companions for all times, to digital first dates.
+ What the uncommon earth steel neodymium exhibits us about our clean-energy future, and the assets we’ll have to create and keep it.
+ Delve into the challenges archivists face as they attempt to protect details about our present lives for these residing far off sooner or later.
+ Why it’s trying probably that one thing shall be developed within the coming a long time that can assist us dwell longer, in higher well being.
+ Learn our investigation into the methods we might all play God within the coming years, due to the flexibility to change our very DNA.
+ How the rise of AI porn may change our expectations of relationships.
MIT Know-how Overview Narrated: An AI startup made a hyperrealistic deepfake of me that’s so good it’s scary
An AI startup created a hyperrealistic deepfake of MIT Know-how Overview’s senior AI reporter Melissa Heikkilä that was so plausible, even she thought it was actually her at first. This know-how is spectacular, to make certain. However it raises large questions on a world the place we more and more can’t inform what’s actual and what’s faux.