afternoonbuzz

Radio Broadcasting History, Adobe, AI, More: Thursday Afternoon ResearchBuzz, October 19, 2023

NEW RESOURCES

New-to-me, from TVNewsCheck: David Gleason Builds A Digital Archive Worth Honoring. “Fully searchable and well organized, the database not only contains publications about broadcasting, but also of the related fields of advertising, media buying, media research and cable. Visitors to the site will also find music magazines, network and station publications, FCC regulations and decisions, fan magazines, radio enthusiast magazines, technical manuals, programming guides and ‘oddities.'”

TWEAKS AND UPDATES

CNN: Adobe previews new AI editing tools. “Photo-editing software maker Adobe unveiled a slew of new AI-powered tools and features last week at its annual Max event, including a dress that transforms into a wearable screen and streamlined ways to delete elements from photos.”

USEFUL STUFF

MakeUseOf: Public AI vs. Private AI vs. Personal AI: What’s the Difference?. “AIs can be categorized as public, private, or personal AIs. Training and designing an AI system based on these categories can help solve issues on regulatory limitations, data privacy, and security…. To understand the difference between public, private, and personal AI, let’s compare them based on their purpose, performance, data handling, and privacy.”

AROUND THE INTERNET WORLD

Government Technology: NYC Releases AI Action Plan, Business-Focused AI Chatbot. “New York City has launched the MyCity Business Services chatbot in a beta form to help residents get information about starting or operating their businesses. The city also released an AI Action Plan to guide responsible city government use of the tech.”

Wall Street Journal: Elon Musk’s X Courts Political Advertisers Ahead of a Contentious Election Year . “Social-media platform X, formerly known as Twitter, has begun aggressively pitching political advertisers after owner Elon Musk reversed a previous ban on political ads this year.”

SECURITY & LEGAL

Bloomberg: Google’s Deals Lock Up 50% of US Searches, DOJ Expert Says. “Google’s exclusive deals to be the default search engine on mobile devices and PC browsers block rivals from as much as half of all queries conducted in the US, the Justice Department’s economic expert said at the company’s antitrust trial Monday.”

The Verge: Google asks Congress to not ban teens from social media. “Google responded to congressional child online safety proposals with its own counteroffer for the first time Monday, urging lawmakers to drop problematic protections like age-verification tech.”

RESEARCH & OPINION

MIT News: A method to interpret AI might not be so interpretable after all. “As autonomous systems and artificial intelligence become increasingly common in daily life, new methods are emerging to help humans check that these systems are behaving as expected. One method, called formal specifications, uses mathematical formulas that can be translated into natural-language expressions. Some researchers claim that this method can be used to spell out decisions an AI will make in a way that is interpretable to humans. MIT Lincoln Laboratory researchers wanted to check such claims of interpretability. Their findings point to the opposite: Formal specifications do not seem to be interpretable by humans. ”

Brookings Institution: Big Tech won. Now what?. “We have been here before. Many of the abuses of today’s internet barons echo behavior by the industrial barons in the late 19th and early 20th centuries. In that instance, the federal government finally stepped up to constrain industrial abuses with new antitrust and consumer protection laws. Whether 21st century policymakers will similarly step up—especially as artificial intelligence becomes pervasive—is the challenge of the internet era.”

Tech Xplore: Using a large-scale dataset holding a million real-world conversations to study how people interact with LLMs. “A team of computer scientists at the University of California Berkeley, working with one colleague from the University of California San Diego and another from Carnegie Mellon University, has created a large-scale dataset of 1 million real-world conversations to study how people interact with large language models (LLMs). They have published a paper describing their work and findings on the arXiv preprint server.” Good afternoon, Internet…

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