alwaysAI Insider, vol. 20: AI Optimism, Reality and Why Computer Vision Provides the Best of Both
Welcome back, Insiders!?
There’s no shortage of news these days so we appreciate you taking a moment to pause with alwaysAI for the latest in AI.?
What’s new? ?
?? Marc Andreessen published his latest musings on the promise of AI in The Techno-Optimist Manifesto . It was received coolly by most accounts but we found Steven Levy’s take (in Wired ) particularly well-written. “[The Manifesto] is also an over-the-top declaration of humanity’s destiny as a tech-empowered super species—Ayn Rand resurrected as a Substack author.” ??(Or maybe I’m just appreciative of the Ayn Rand reference. ??)?
?? Bill Nye is an optimist too. Nye recently spoke with CNBC’s Tyler Mathisen about AI and the future of humanity (just the kind of light-hearted interview you’d expect from the former Boeing engineer turned “Science Guy”). He likens recent AI technology to the calculator – “good engineering invites right use.”?
?? Meanwhile...AI fears about being a danger to democracy were recently realized in the form of deep fakes – in Slovakia and here in the US .?
??? Cue President Biden who issued the first of its kind AI Executive Order on Monday. The mandates and directives are promising – as is the new AI.gov website. What remains to be seen is how effective the order will be in mitigating AI risks.
??? It’s a daunting task and why we were encouraged to read about Roy Bahat, the head of Bloomberg Beta (Bloomberg LP’s venture capital arm), who offers a framework for thinking about the role of AI in modern society. He compared the effects of AI to three sets of technology: looms (replace people), slide rules (assist people), and cranes (allow people to do something they currently cannot).?
Why it matters?
Bahat's opening line (and why we’ve linked the full article below): not all artificial intelligence is created equal.
It’s the exact sentiment we endeavor to convey here. Computer vision is not generative AI. It’s not capable of deep fakes. It doesn’t aim to be superhuman. It can't interfere with elections. What it can do? Improve operational efficiency. Optimize shelf inventory. Provide real-time visual insights into your business for data you’ve never had access to before.?
It is the must-have technology for any business with blind spots — on a factory floor, warehouse shelf, drive-thru line, or far corner of a retail store. It’s reality. It’s practical AI and it keeps getting better.?
Case in point: we just upgraded and enhanced our entire MLOps suite for even more model training and management capabilities. We've updated and streamlined our model training UI, and now offer multiple GPU options for faster training times, forecasted training times based on your specific parameters as well as real-time session performance. PLUS...our brand new modelIQ is a one-of-a-kind tool that provides unparalleled precision in model evaluation.
Good engineering invites right use. Indeed, Mr. Nye. ??
INDUSTRY ROUNDUP
Computer vision is here and it's only getting better and more accessible. Paul Williamson, Senior Vice President and General Manager, IoT Line of Business, at Arm?writes:?
"Anyone sitting on the vision-innovation sidelines at the moment risks being left behind. That’s not just because of the missed opportunities.
There is almost no reason not to roll up your sleeves and get to work. That’s because virtually all the tools and processes required to kickstart one’s vision journey are readily available.
The only thing holding us back now is our imagination."
Read more .?
Computer vision is helping Home Depot bridge the gap between in-stock inventory and on-shelf availability.
The impact of this kind of real-time visual data is not only helping improve customer experience but also helping to improve employee productivity – alerting them to areas with low or out-of-stock items, optimizing task prioritization, and boosting efficiency.??
领英推荐
The Bloomberg Tech Summit in London wrapped up last week. Among several critical discussions about how AI is disrupting society was Roy Bahat's comparison of AI tools to other historical tools that shaped and reshaped how we work: the loom, slide rules, and cranes. ?
He raises several valuable points as he seeks to answer "Can we build better AI?" But we have to admit, he had us at the opening line. "Not all artificial intelligence is created equal."?
ALWAYSAI INSIGHTS
We are excited to announce the launch of alwaysAI’s new cutting-edge MLOps features. Along with Dataset Management and Remote Deployment, Model Training is the third enhanced feature of alwaysAI 2.0.
What’s new and improved in our MLOps lineup?
Learn more .?
Along with alwaysAI's new and improved MLOps capabilities, we are excited to offer a one-of-a-kind advanced model evaluation tool, modelIQ.?
modelIQ takes the mystery out of model training by providing an overall model evaluation score broken down into several key components (like label, quadrant, and bounding box size).
modelIQ is designed to help you sharpen and refine your model exactly where it's needed, saving you invaluable time and eliminating unnecessary frustration. No other tool provides this precise level of detailed information critical to optimizing model performance.
DEVELOPER DIGEST
From the Institute for Ethical AI & Machine Learning, The Machine Learning Engineer newsletter is a weekly publication packed with curated articles and tutorials on production Machine Learning. What do you get? "Insights on real-world ML best practice encompassing key areas in Model Monitoring, MLOps, DataOps, AIOps + beyond."
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