A growing number of tools now let you stop facial recognition systems from training on your personal photos
Uploading personal photos to the internet can feel like letting go. Who else will have access to them, what will they do with them—and which machine-learning algorithms will they help train?
The company Clearview has already supplied US law enforcement agencies with a facial recognition tool trained on photos of millions of people scraped from the public web. But that was likely just the start. Anyone with basic coding skills can now develop facial recognition software, meaning there is more potential than ever to abuse the tech in everything from sexual harassment and racial discrimination to political oppression and religious persecution.
A number of AI researchers are pushing back and developing ways to make sure AIs can’t learn from personal data. Two of the latest are being presented this week at ICLR, a leading AI conference. Read More
Monthly Archives: May 2021
Watson Orchestrate
Watson Orchestrate gives you interactive AI–in tools like email and Slack–to increase your productivity. This isn’t a static bot programmed by IT. You initiate work in natural language, and Watson Orchestrate uses a powerful AI engine to combine pre-packaged skills, on-the-fly and in-context, based on organizational knowledge and your prior interactions. Read More
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Machine Learning Roadmap
Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO
By supporting multi-modal retrieval training and evaluation, image captioning datasets have spurred remarkable progress on representation learning.Unfortunately, datasets have limited cross-modal associations: images are not paired with other images, captions are only paired with other captions of the same image, there are no negative associations and there are missing positive cross-modal associations. This undermines research into how inter-modality learning impacts intra-modality tasks. We address this gap with Crisscrossed Captions (CxC), an extension of the MS-COCO dataset with human semantic similarity judgments for267,095intra- and inter-modality pairs. We report baseline results on CxC for strong existing unimodal and multi-modal models. We also evaluate a multitask dual encoder trained on both image-caption and caption-caption pairs that crucially demonstrates CxC’s value for measuring the influence of intra- and inter-modality learning. Read More
The Edge: What Does It Mean For Artificial Intelligence?
The edge is an end point where data is generated through some type of interface, device or sensor. Keep in mind that the technology is nothing new. But in light of the rapid innovations in a myriad of categories, the edge has become a major growth business.
“The edge brings the intelligence as close as possible to the data source and the point of action,” said Teresa Tung, who is the Managing Director at Accenture Labs. “This is important because while centralized cloud computing makes it easier and cheaper to process data at scale, there are times when it doesn’t make sense to send data off to the cloud for processing.” Read More
Thousands of Tor exit nodes attacked cryptocurrency users over the past year
For more than 16 months, a threat actor has been seen adding malicious servers to the Tor network in order to intercept traffic and perform SSL stripping attacks on users accessing cryptocurrency-related sites.
The attacks, which began in January 2020, consisted of adding servers to the Tor network and marking them as “exit relays,” which are the servers through which traffic leaves the Tor network to re-enter the public internet after being anonymized. Read More
The Department of Defense’s Looming AI Winter
The Department of Defense is on a full-tilt sugar high about the potential for AI to secure America’s competitive edge over potential adversaries. AI does hold exciting possibilities. But an artificial AI winter looms for the department, potentially restraining it from joining the rest of the world in the embrace of an AI spring.
The department’s frenzy for AI is distracting it from underlying issues preventing operationalization of AI at scale. When these efforts fail to meet expectations, the sugar rush will collapse into despair. The resultant feedback loop will deprioritize and defund AI as a critical weapon system. This is known as an “AI winter,” and the Department of Defense has been here twice before. If it happens again, it won’t be because the technology wasn’t ready, but because the Department of Defense doesn’t know enough about AI, has allowed a bureaucracy to grow up between the people who will use AI and those developing it for them, and is trying to tack “AI-ready” components onto legacy systems on the cheap. Read More
How the US Postal Service Is Using AI at the Edge to Improve Mail
Edge computing systems automate package identification at nearly 200 USPS processing centers.
If you paid attention to the US presidential election in 2020, the US Postal Service scandal probably came across your screen. The agency’s resources were stretched so thin, it was feared, that it would become a bottleneck in an election where an unprecedented number of people would vote by mail.
If you were left with the impression that USPS’s budget was close to if not in the red, you may feel some cognitive dissonance when you read that as an enterprise, it is one of the few success stories about the use of AI by the federal government. Read More
AI.gov
The just launched AI.gov is home of the National AI Initiative and connection point to ongoing activities to advance U.S. leadership in AI. The National AI Initiative Act of 2020 became law on January 1, 2021, providing for a coordinated program across the entire Federal government to accelerate AI research and application for the Nation’s economic prosperity and national security. The mission of the National AI Initiative is to ensure continued U.S. leadership in AI research and development, lead the world in the development and use of trustworthy AI in the public and private sectors, and prepare the present and future U.S. workforce for the integration of AI systems across all sectors of the economy and society. Read More
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