In the year of darkness, 2029, the rulers of this planet devised the ultimate plan.
They would reshape the future by changing the past.
The plan required something that felt no pity. No pain. No fear.
Something unstoppable. They created the Terminator.
That, as you can probably guess, is the plot of The Terminator, one of the greatest sci-fi ideas of all time.
James Cameron basically saw that computers were becoming ever more powerful and thought about what might happen if that trend continued.
Eventually, the computers wold be so powerful they would become “self-aware”, and when that happened, humans would no longer be the dominant lifeform on this planet.
In his vision, a world war, unlike anything ever seen in human history, would break out, pitting man against machine. And man, against all-odds, would begin to triumph.
At this point, the computers, knowing their end was inevitable, would use their superior intelligence to bend the laws of physics and create time travel.
They would send back a Terminator to kill John Connor, the leader of the resistance, before he was born by killing his mother.
As this is a film, the human resistance manages to break into the time travel facility and send back a soldier of their own to protect John’s mother, just before the facility is destroyed.
The rest of the film is set in 1984, as the Terminator and the human soldier battle it out to slay or save John’s mother.
So, why am I bringing up The Terminator once again, as I seem to do every six months or so?
Because of a new AI development reported earlier this month, of course.
AI makes scientific discovery from the past in the future
From Vice (of all places):
Using just the language in millions of old scientific papers, a machine learning algorithm was able to make completely new scientific discoveries.
In a study published in Nature on July 3, researchers from the Lawrence Berkeley National Laboratory used an algorithm called Word2Vec sift through scientific papers for connections humans had missed. Their algorithm then spit out predictions for possible thermoelectric materials, which convert heat to energy and are used in many heating and cooling applications.
The algorithm didn’t know the definition of thermoelectric, though. It received no training in materials science. Using only word associations, the algorithm was able to provide candidates for future thermoelectric materials, some of which may be better than those we currently use.
It managed to do this because it can read millions of different research papers in many different languages, from many different scientific disciplines, which allows it to see connections no one person could.
The researchers then showed how the AI could effectively speed up the future by making discoveries years before teams of humans could.
Here’s the interesting part of the Vice article (emphasis mine):
After showing its capacity to predict future materials, researchers took their work back in time, virtually. They scrapped recent data and tested the algorithm on old papers, seeing if it could predict scientific discoveries before they happened. Once again, the algorithm worked.
In one experiment, researchers analyzed only papers published before 2009 and were able to predict one of the best modern-day thermoelectric materials four years before it was discovered in 2012.
So the AI, using only research from pre-2009 managed to make the same discovery that humans took humans until 2012.
But this AI doesn’t just work with the niche subject of thermoelectric materials, as one of its creators, Vahe Tshitoyan, says:
“This algorithm is unsupervised and it builds its own connections. You could use this for things like medical research or drug discovery. The information is out there. We just haven’t made these connections yet because you can’t read every article.”
Minority Report style gestures may debut on Google’s next smartphone
Sticking with a future meets past theme, it looks like we may soon actually get those Minority Report style computers futurists have been dreaming of.
(Note, that’s not a still of Tom Cruise in Minority Report, it’s actually someone mimicking him. I couldn’t find a public licence still from the actual film.)
Only the real-life version won’t even require you to wear weird light-up gloves.
First announced at Google I/O 2015, Project Soli is a Google ATAP endeavor based on radar hardware, most notably for device control via subtle hand movements.
Whether you’re using a watch, phone, or tablet, this miniature radar sensor can, among many other things, differentiate between very fine motions to perform various platform-specific functions. Now, we’re told that 2019 might be the year that Soli finally shows up in Google’s hardware products.
Specifically, we’ve heard that the Soli radar chip is integrated in the Google Pixel 4. We don’t have any idea what this would mean for the product; Google could easily use the chip for anything from gesture-based control while driving to new Assistant interaction methods.
Google’s Soli is basically like a miniature super-sensitive radar system. It will give you precise gesture controls, just like in Minority Report.
Only it will be even better than the vision in Minority Report because it will be able to pick up on tiny finger gestures, not just big sweeping movements.
Since 9to5Goolgle published its original article, it has been confirmed that the Google Pixel 4 will include a Soli chip, and the feature will be called “aware”.
If you want to know more about it, you can watch Google’s video on it here. It really is very impressive.
These two developments – AI speeding up scientific discoveries and new ways of interacting with our electronics – are something Nick O’Connor covered in detail in his book, The Exponentialist.
And not only did he cover these areas, he also looked into the best ways to invest in them. So if you can see the potential of this kind of technology and want to know how to invest in it, pick up a copy of Nick’s book here.
Until next time,
Editor, Exponential Investor
Category: Genetics and Biotechnology