New AI improves itself through Darwinian-style evolution

AutoML-Zero is a proof-of-concept project that suggests the future of machine learning may be machine-created algorithms.

New AI improves itself through Darwinian-style evolution
  • Automatic machine learning is a fast-developing branch of deep learning.
  • It seeks to vastly reduce the amount of human input and energy needed to apply machine learning to real-world problems.
  • AutoML-Zero, developed by scientists at Google, serves as a simple proof-of-concept that shows how this kind of technology might someday be scaled up and applied to more complex problems.

Machine learning has fundamentally changed how we engage with technology. Today, it's able to curate social media feeds, recognize complex images, drive cars down the interstate, and even diagnose medical conditions, to name a few tasks.

But while machine learning technology can do some things automatically, it still requires a lot of input from human engineers to set it up, and point it in the right direction. Inevitably, that means human biases and limitations are baked into the technology.

So, what if scientists could minimize their influence on the process by creating a system that generates its own machine-learning algorithms? Could it discover new solutions that humans never considered?

To answer these questions, a team of computer scientists at Google developed a project called AutoML-Zero, which is described in a preprint paper published on arXiv.

"Human-designed components bias the search results in favor of human-designed algorithms, possibly reducing the innovation potential of AutoML," the paper states. "Innovation is also limited by having fewer options: you cannot discover what you cannot search for."

Automatic machine learning (AutoML) is a fast-growing area of deep learning. In simple terms, AutoML seeks to automate the end-to-end process of applying machine learning to real-world problems. Unlike other machine-learning techniques, AutoML requires relatively little human effort, which means companies might soon be able to utilize it without having to hire a team of data scientists.

AutoML-Zero is unique because it uses simple mathematical concepts to generate algorithms "from scratch," as the paper states. Then, it selects the best ones, and mutates them through a process that's similar to Darwinian evolution.

AutoML-Zero first randomly generates 100 candidate algorithms, each of which then performs a task, like recognizing an image. The performance of these algorithms is compared to hand-designed algorithms. AutoML-Zero then selects the top-performing algorithm to be the "parent."

"This parent is then copied and mutated to produce a child algorithm that is added to the population, while the oldest algorithm in the population is removed," the paper states.

The system can create thousands of populations at once, which are mutated through random procedures. Over enough cycles, these self-generated algorithms get better at performing tasks.

"The nice thing about this kind of AI is that it can be left to its own devices without any pre-defined parameters, and is able to plug away 24/7 working on developing new algorithms," Ray Walsh, a computer expert and digital researcher at ProPrivacy, told Newsweek.

If computer scientists can scale up this kind of automated machine-learning to complete more complex tasks, it could usher in a new era of machine learning where systems are designed by machines instead of humans. This would likely make it much cheaper to reap the benefits of deep learning, while also leading to novel solutions to real-world problems.

Still, the recent paper was a small-scale proof of concept, and the researchers note that much more research is needed.

"Starting from empty component functions and using only basic mathematical operations, we evolved linear regressors, neural networks, gradient descent... multiplicative interactions. These results are promising, but there is still much work to be done," the scientists' preprint paper noted.

A landslide is imminent and so is its tsunami

An open letter predicts that a massive wall of rock is about to plunge into Barry Arm Fjord in Alaska.

Image source: Christian Zimmerman/USGS/Big Think
Surprising Science
  • A remote area visited by tourists and cruises, and home to fishing villages, is about to be visited by a devastating tsunami.
  • A wall of rock exposed by a receding glacier is about crash into the waters below.
  • Glaciers hold such areas together — and when they're gone, bad stuff can be left behind.

The Barry Glacier gives its name to Alaska's Barry Arm Fjord, and a new open letter forecasts trouble ahead.

Thanks to global warming, the glacier has been retreating, so far removing two-thirds of its support for a steep mile-long slope, or scarp, containing perhaps 500 million cubic meters of material. (Think the Hoover Dam times several hundred.) The slope has been moving slowly since 1957, but scientists say it's become an avalanche waiting to happen, maybe within the next year, and likely within 20. When it does come crashing down into the fjord, it could set in motion a frightening tsunami overwhelming the fjord's normally peaceful waters .

"It could happen anytime, but the risk just goes way up as this glacier recedes," says hydrologist Anna Liljedahl of Woods Hole, one of the signatories to the letter.

The Barry Arm Fjord

Camping on the fjord's Black Sand Beach

Image source: Matt Zimmerman

The Barry Arm Fjord is a stretch of water between the Harriman Fjord and the Port Wills Fjord, located at the northwest corner of the well-known Prince William Sound. It's a beautiful area, home to a few hundred people supporting the local fishing industry, and it's also a popular destination for tourists — its Black Sand Beach is one of Alaska's most scenic — and cruise ships.

Not Alaska’s first watery rodeo, but likely the biggest

Image source:

There have been at least two similar events in the state's recent history, though not on such a massive scale. On July 9, 1958, an earthquake nearby caused 40 million cubic yards of rock to suddenly slide 2,000 feet down into Lituya Bay, producing a tsunami whose peak waves reportedly reached 1,720 feet in height. By the time the wall of water reached the mouth of the bay, it was still 75 feet high. At Taan Fjord in 2015, a landslide caused a tsunami that crested at 600 feet. Both of these events thankfully occurred in sparsely populated areas, so few fatalities occurred.

The Barry Arm event will be larger than either of these by far.

"This is an enormous slope — the mass that could fail weighs over a billion tonnes," said geologist Dave Petley, speaking to Earther. "The internal structure of that rock mass, which will determine whether it collapses, is very complex. At the moment we don't know enough about it to be able to forecast its future behavior."

Outside of Alaska, on the west coast of Greenland, a landslide-produced tsunami towered 300 feet high, obliterating a fishing village in its path.

What the letter predicts for Barry Arm Fjord

Moving slowly at first...

Image source:

"The effects would be especially severe near where the landslide enters the water at the head of Barry Arm. Additionally, areas of shallow water, or low-lying land near the shore, would be in danger even further from the source. A minor failure may not produce significant impacts beyond the inner parts of the fiord, while a complete failure could be destructive throughout Barry Arm, Harriman Fiord, and parts of Port Wells. Our initial results show complex impacts further from the landslide than Barry Arm, with over 30 foot waves in some distant bays, including Whittier."

The discovery of the impeding landslide began with an observation by the sister of geologist Hig Higman of Ground Truth, an organization in Seldovia, Alaska. Artist Valisa Higman was vacationing in the area and sent her brother some photos of worrying fractures she noticed in the slope, taken while she was on a boat cruising the fjord.

Higman confirmed his sister's hunch via available satellite imagery and, digging deeper, found that between 2009 and 2015 the slope had moved 600 feet downhill, leaving a prominent scar.

Ohio State's Chunli Dai unearthed a connection between the movement and the receding of the Barry Glacier. Comparison of the Barry Arm slope with other similar areas, combined with computer modeling of the possible resulting tsunamis, led to the publication of the group's letter.

While the full group of signatories from 14 organizations and institutions has only been working on the situation for a month, the implications were immediately clear. The signers include experts from Ohio State University, the University of Southern California, and the Anchorage and Fairbanks campuses of the University of Alaska.

Once informed of the open letter's contents, the Alaska's Department of Natural Resources immediately released a warning that "an increasingly likely landslide could generate a wave with devastating effects on fishermen and recreationalists."

How do you prepare for something like this?

Image source:

The obvious question is what can be done to prepare for the landslide and tsunami? For one thing, there's more to understand about the upcoming event, and the researchers lay out their plan in the letter:

"To inform and refine hazard mitigation efforts, we would like to pursue several lines of investigation: Detect changes in the slope that might forewarn of a landslide, better understand what could trigger a landslide, and refine tsunami model projections. By mapping the landslide and nearby terrain, both above and below sea level, we can more accurately determine the basic physical dimensions of the landslide. This can be paired with GPS and seismic measurements made over time to see how the slope responds to changes in the glacier and to events like rainstorms and earthquakes. Field and satellite data can support near-real time hazard monitoring, while computer models of landslide and tsunami scenarios can help identify specific places that are most at risk."

In the letter, the authors reached out to those living in and visiting the area, asking, "What specific questions are most important to you?" and "What could be done to reduce the danger to people who want to visit or work in Barry Arm?" They also invited locals to let them know about any changes, including even small rock-falls and landslides.

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