🍊 The Juice: Dare Mighty Things
By: Michael Stewart
Tags: Artificial Intelligence, NASA, The Juice, Computer Vision, Deep Learning

🍊 The Juice: Dare Mighty Things

Week of February 22–26, 2021

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Folks at NASA have been smiling all week. Many of them because NASA managed to land their latest rover, Perseverance, on the planet Mars in an absolutely stunning feat of human engineering. Others because that robot subsequently beamed back absolutely mind blowing footage of the stunt. But Ian Clark, the lead developer of the system’s parachute system, was smiling because a handful of internet sleuths managed to piece together the coded message they had cleverly hidden within the canopy. Watching the internet do its thing in real time on Reddit last week was incredible, and there’s a good synopsis of it all in the NY Times.

But let’s talk about that rover. Perseverance is basically an extraterrestrial self-driving car. Actually it’s more like a Martian Tesla, since NASA made an active decision to avoid using a bulky, energy-hungry lidar system in favor of simple stereo vision. Reliability and economy are critical for space missions, it turns out. There was a great piece in Wired last July that gets into the weeds on the autonomous systems NASA developed for Perseverance. “All of its mobile explorers have used a combination of stereo vision and visual odometry to get around. But what makes Perseverance special is that it has dedicated hardware and a suite of fancy new algorithms for machine vision.”

So, I guess if Perseverance happens to run into Starman, at least they’ll have something to talk about.

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#Multimodality

If computer vision has an Achilles’ heel, it’s that current systems are inflexible and only capable of making predictions on a limited set of predefined categories. But current research into multimodal systems — which combine things like computer vision with natural-­language models — is aiming to make AI more robust and adaptable. Is this a step towards artificial general intelligence? See our Paper of the Week for more progress on this front.

AI armed with multiple senses could gain more flexible intelligence, via MIT Technology Review.

#Lookout

This week Amazon announced that Lookout for Vision, their cloud-based computer vision analysis platform, is widely available. The service, which is targeting the manufacturing sector, uses computer vision to identify defects or anomalies in images of the goods. Customers will pay hourly for usage, whether they’re training the model or detecting defects. We could see this being adopted by teams in the manufacturing space that already use AWS but don’t have in house ML.

Amazon launches computer vision service to detect defects in manufactured products, via VentureBeat.

#AssistiveMobility

When an industry is dominated by just a handful of multinational organizations, there’s little incentive to innovate. But now several startup challengers are looking to disrupt the wheelchair industry, and build a better chair for those living with mobility challenges. That means the next generation of wheelchairs will likely include radar and cameras, to power features like intelligent braking, drop detection, and collision avoidance.

Start-ups seek to breathe new life into stagnant wheelchair industry, via The Washington Post.

#Bionics

For many years doctors have pursued sight restoration for those blinded by disease or trauma. Now, one doctor is proposing that, at least in the near term, we should instead be focused on the development of artificial vision. Dr. Michael Beyeler and his team at UC Santa Barbara are working on a smart prosthesis that uses the sort of computer vision you might see in autonomous vehicles. They also presented their work earlier this week at Augmented Humans 2021, and you can catch that presentation here on YouTube.

Building the Bionic Eye…With Car Tech?, via PCMag.

#EthicalAI

On Friday, Google fired Margaret Mitchell, the founder and former co-lead of their ethical AI team. It’s a move that was not entirely unexpected, following Google revoking her corporate access in January, and the restructure that we covered in last week’s newsletter. But it is a shame, considering the work that Mitchell and Dr. Timnit Gebru had been doing to bring attention to bias in Google’s AI systems. Hard not to wonder what’s next for the Ethical AI team over there.

Google fires top AI ethics researcher Margaret Mitchell, via TechCrunch.

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📄 Paper of the Week

Transformer is All You Need: Multimodal Multitask Learning with a Unified Transformer

The year of the transformer continues with this thought provoking work from FAIR (Facebook AI Research). The authors train the same model on 7 different tasks, which span everything from object detection to natural language understanding, and show how the model achieves comparable performance to prior work on all the tasks. That is a scary amount of generalization, especially given the different modalities of each of the tasks (images, text, etc). On our road to AGI, perhaps transformers will be all we need.

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