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AI tool is built to boost the hunt for gravitational waves

Illustration: Mirrors and lasers in foreground, colliding black holes and gravitational waves in background
An illustration hints at how LIGO uses mirrors and laser beams to detect black hole collisions. (Google DeepMind Illustration)

The Laser Interferometer Gravitational-Wave Observatory, or LIGO, has already won its researchers a Nobel Prize — and now artificial intelligence is poised to take LIGO’s search for cosmic collisions to the next level.

Google DeepMind and the LIGO team say they’ve developed an AI tool called Deep Loop Shaping that has been shown to enhance the observatory’s ability to track gravitational waves — faint ripples in the fabric of spacetime that are thrown off by smash-ups involving black holes and massive neutron stars.

The researchers describe the technique in a proof-of-concept study published today by the journal Science. They hope to make Deep Loop Shaping part of routine operations at LIGO’s detectors in Louisiana and on the Hanford nuclear site in Washington state.

“Deep Loop Shaping is revolutionary, because it is able to reduce the noise level in the most unstable and most difficult feedback loop at LIGO,” lead author Jonas Buchli, a research scientist at Google DeepMind, told reporters.

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AI matches an average programmer’s prowess

Illustration showing programming code
DeepMind’s AlphaCode program takes a data-driven approach to coding. (Google DeepMind Illustration)

Artificial intelligence software programs are becoming shockingly adept at carrying on conversations, winning board games and generating artwork — but what about creating software programs? In a newly published paper, researchers at Google DeepMind say their AlphaCode program can keep up with the average human coder in standardized programming contests.

“This result marks the first time an artificial intelligence system has performed competitively in programming contests,” the researchers report in this week’s issue of the journal Science.

There’s no need to sound the alarm about Skynet just yet: DeepMind’s code-generating system earned an average ranking in the top 54.3% in simulated evaluations on recent programming competitions on the Codeforces platform — which is a very “average” average.

“Competitive programming is an extremely difficult challenge, and there’s a massive gap between where we are now (solving around 30% of problems in 10 submissions) and top programmers (solving >90% of problems in a single submission),” DeepMind research scientist Yujia Li, one of the Science paper’s principal authors, told me in an email. “The remaining problems are also significantly harder than the problems we’re currently solving.”

Nevertheless, the experiment points to a new frontier in AI applications. Microsoft is also exploring the frontier with a code-suggesting program called Copilot that’s offered through GitHub. Amazon has a similar software tool, called CodeWhisperer.

Oren Etzioni, the founding CEO of Seattle’s Allen Institute for Artificial Intelligence and technical director of the AI2 Incubator, told me that the newly published research highlights DeepMind’s status as a major player in the application of AI tools known as large language models, or LLMs.

“This is an impressive reminder that OpenAI and Microsoft don’t have a monopoly on the impressive feats of LLMs,” Etzioni said in an email. “Far from it, AlphaCode outperforms both GPT-3 and Microsoft’s Github Copilot.”

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AlphaGo beats Go masters in stealth games

Image: Go game
The AI program known as AlphaGo has mastered the game of Go. (Credit: Google DeepMind)

For the past week or so, a mystery player has been logging into online Go game servers and beating the world’s best. Today, the player’s identity was revealed at last.

It was none other than AlphaGo, the artificial-intelligence program that triumphed over Go master Lee Sedol last March in a widely publicized $1 million showdown.

Google DeepMind’s co-founder and CEO, Demis Hassabis, let the world in on the secret today in a tweeted statement.

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