This week in AI & Machine Learning: a formal definition of Vision AI, the environmental costs of AI, DALL-E and more

A Note from the Author 

I’m Paul Davenport, Plainsight’s Director of Communications, and with your usual AI expert Bennett off enjoying some well-deserved R&R, I’ll be serving you this week’s roundup!

While ‘AI’ and ‘ML’ are commonly understood concepts today, how would experts define Vision AI? With practical applications that run the gamut from livestock counting to PPE compliance, we explain Plainsight’s take on the topic in our latest blog.

In other Plainsight news, our CPO and Co-Founder Elizabeth Spears was featured in an interview with TechRepublic this week discussing our now-famous livestock counting use case and how production-ready computer vision solutions  can be applied across industries.   

Artificial Intelligence News

What are the environmental costs of AI?

It’s no secret that AI is often put on a pedestal, hailed as either the technological key to a better, more interconnected future, or, alternatively, the vehicle driving humanity toward an oppressive, Terminator-esque dystopia. But as a recent article from the Council on Foreign Relations points out, the potential benefits and risks of artificial intelligence aren’t so binary, as even the most well intentioned applications come with an environmental caveat.

 Specifically, the energy used by AI processes  is one of the most immediate concerns being raised by the Council, as “training a single AI system can emit over 250,000 pounds of carbon dioxide,” the article reports. Even the best-intentioned AI use cases come with their caveats, and leaders in the space need to be better aware of the unintended or tangential impacts of the technology when exploring new applications.

DALL-E takes the Internet by storm

If you’ve been on social media over the past month, you’ve likely come across the “Internet’s new favorite meme,” DALL-E Mini. The app, which is hosted by open-source AI company Hugging Face, receives a typed text prompt and then automatically generates nine images representing the tool’s AI-sourced best guess at what the prompt describes. From creating a hamster Godzilla to Darth Vader breakdancing, DALL-E Mini may be the most high-profile, novel application of AI to date, with the platform serving up more than 50,000 images a day in recent weeks, according to Wired. 

3 Predictions for AI’s Business Implications

A recent INC Magazine article took a look at AI through the lens of a post-pandemic world, highlighting how automation became an even bigger business driver in recent years as companies adapted to doing business in the digital realm. Along with helping brands better serve customers at the height of the pandemic, AI was also a driving force in helping companies rethink their environmental impact. Going forward, it’s expected that AI will help smooth the runway for businesses to enter the metaverse. Read more about AI’s future implications in the article

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See you next week! Until then, keep the conversation going on Plainsight’s AI Slack Channel

 

About the Author & Plainsight

Paul Davenport hails from Boston and has an extensive background in tech journalism. He helps Plainsight in its mission to make vision AI accessible to entire enterprise teams.

Plainsight’s vision AI platform streamlines and optimizes the full computer vision lifecycle. From data annotation through deployment, customers can quickly create and successfully operationalize their own vision AI applications to solve highly diverse business challenges.

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