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This week in AI: Generative AI spams academic journals

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Hello guys, welcome to TechCrunch’s regular AI newsletter.

This week in AI, generative AI is beginning to spam academic publications, a discouraging recent development on the disinformation front.

IN post about retraction watchblog tracking the recent retreat from academic research, assistant professors of philosophy Tomasz Żuradzk and Leszek Wroński wrote about three journals published by Addleton Academic Publishers that appear to consist entirely of AI-generated articles.

Magazines feature articles following the identical template, stuffed with buzzwords like “blockchain,” “metaverse,” “internet of things,” and “deep learning.” They list the identical editorial committee – 10 members of that are deceased – and an not easily seen address in Queens, New York, that appears to be home.

So what is going on on? You can ask. Isn’t viewing AI-generated spam simply a value of doing business online lately?

Yeah. But the fake journals show how easily the systems used to guage researchers for promotions and tenure might be fooled – and this could possibly be a motivator for knowledge employees in other industries.

In a minimum of one widely used rating system, CiteScore, journals rank in the highest ten for philosophy research. How is it possible? They quote one another at length. (CiteScore includes citations in its calculations). Żuradzk and Wroński state that of the 541 citations in considered one of Addleton’s journals, 208 come from other false publications of the publisher.

“(These rankings) often serve as indicators of research quality for universities and funding institutions,” Żuradzk and Wroński wrote. “They play a key role in decisions about academic rewards, hiring and promotion, and thus can influence researchers’ publication strategies.”

You could argue that CiteScore is the issue – it’s clearly a flawed metric. And this just isn’t a false argument. However, it just isn’t incorrect to say that generative AI and its abuse are disrupting the systems on which individuals’s lives depend in unexpected – and potentially quite harmful – ways.

There is a future in which generative AI forces us to rethink and redesign systems like CiteScore to be more equitable, holistic and inclusive. The bleaker alternative – and the one which exists today – is a future in which generative AI continues to run amok, wreaking havoc and ruining work lives.

I hope we’ll correct course soon.

News

DeepMind soundtrack generator: DeepMind, Google’s artificial intelligence research lab, says it’s developing artificial intelligence technology to generate movie soundtracks. DeepMind’s AI combines audio descriptions (e.g. “jellyfish pulsating underwater, sea life, ocean”) with the video to create music, sound effects, and even dialogue that match the characters and tone of the video.

Robot chauffeur: : Researchers on the University of Tokyo have developed and trained a “musculoskeletal humanoid” named Musashi to drive a small electric automobile around a test track. Equipped with two cameras replacing human eyes, Musashi can “see” the road ahead and the views reflected in the automobile’s side mirrors.

New AI search engine: : Genspark, a brand new AI-powered search platform, uses generative AI to create custom summaries in response to queries. To date, $60 million has been raised from investors including Lanchi Ventures; In its latest round of financing, the corporate valued it at $260 million post-acquisition, which is decent considering Genspark competes with rivals like Perplexity.

How much does ChatGPT cost?: How much does ChatGPT, OpenAI’s ever-expanding AI-powered chatbot platform, cost? Answering this query is tougher than you think that. To keep track of different ChatGPT subscription options available, we have prepared an updated ChatGPT pricing guide.

Science article of the week

Autonomous vehicles face an infinite number of edge cases, depending on location and situation. If you are driving on a two-lane road and someone activates their left turn signal, does that mean they’ll change lanes? Or that it is best to pass them on? The answer may depend upon whether you are driving on I-5 or the highway.

A gaggle of researchers from Nvidia, USC, UW and Stanford show in a paper just published in CVPR that many ambiguous or unusual circumstances might be solved by, should you can consider it, asking an AI to read the local drivers’ handbook.

Their Big Tongue Driver Assistant or LLaDa, gives the LLM access – even without the power to specify – driving instructions for a state, country or region. Local rules, customs or signs might be found in the literature, and when an unexpected circumstance occurs, e.g. a horn, traffic lights or a flock of sheep, an appropriate motion is generated (stop, stop, honk).

Image credits: Nvidia

This is certainly not an entire, comprehensive driving system, nevertheless it shows another path to a “universal” driving system that also encounters surprises. Or perhaps it is a way for the remainder of us to search out out why people honk at us after we visit unknown sites.

Model of the week

On Monday, Runway, an organization that creates generative AI tools aimed toward creators of film and image content, presented Gen-3 Alpha. Trained on an enormous variety of images and videos from each public and internal sources, Gen-3 can generate video clips based on text descriptions and still images.

Runway claims Gen-3 Alpha delivers “significant” improvements in generation speed and fidelity over Runway’s previous video flagship, Gen-2, in addition to precise control over the structure, style and motion of the videos it creates. Runway says Gen-3 can be customized to offer more “stylistically controlled” and consistent characters, guided by “specific artistic and narrative requirements.”

The Gen-3 Alpha has its limitations – including the indisputable fact that footage lasts a maximum of 10 seconds. But Runway co-founder Anastasis Germanidis guarantees that that is just the primary of several video-generating models to come back in a family of next-generation models trained on Runway’s improved infrastructure.

Gen-3 Alpha is the most recent of several generative video systems to hit the scene in recent months. Others include OpenAI’s Sora, Luma’s Dream Machine, and Google’s Veo. Together, they threaten to upend the film and tv industry as we understand it – assuming they will overcome copyright challenges.

Take the bag

AI won’t take your next McDonald’s order.

McDonald’s this week announced that it should remove automated order-taking technology, which the fast food chain has been testing for the higher a part of three years, from greater than 100 of its restaurants. The technology — developed with IBM and installed in drive-thru restaurants — became popular last 12 months due to its tendency to misunderstand customers and make mistakes.

Recent piece in Takeout suggests that artificial intelligence is losing its grip on fast food operators, who’ve recently expressed enthusiasm for the technology and its potential to extend efficiency (and reduce labor costs). Presto, a significant player in the AI-powered drive-thru lane market, recently lost a significant customer, Del Taco, and is facing mounting losses.

The problem is inaccuracy.

McDonald’s CEO Chris Kempczinski he said CNBC in June 2021 found that its voice recognition technology was accurate about 85% of the time, but that it needed to be assisted by human staff for about one in five orders. Meanwhile, in keeping with Takeout, one of the best version of the Presto system processes only about 30% of orders without human assistance.

So, so long as artificial intelligence is there decimating some segments of the gig economy appear to think that certain jobs – especially people who require understanding a wide range of accents and dialects – can’t be automated. At least for now.

This article was originally published on : techcrunch.com
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Bluesky addresses trust and security issues related to abuse, spam and more

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Bluesky butterfly logo and Jay Graber

Social media startup Bluesky, which is constructing a decentralized alternative to X (formerly Twitter), provided an update Wednesday on the way it’s approaching various trust and security issues on its platform. The company is in various stages of developing and piloting a variety of initiatives focused on coping with bad actors, harassment, spam, fake accounts, video security and more.

To address malicious users or those that harass others, Bluesky says it’s developing recent tools that can have the option to detect when multiple recent accounts are created and managed by the identical person. This could help curb harassment when a foul actor creates several different personas to attack their victims.

Another recent experiment will help detect “rude” replies and forward them to server moderators. Like Mastodon, Bluesky will support a network where self-hosters and other developers can run their very own servers that connect to Bluesky’s server and others on the network. This federation capability is still in early access. But in the long term, server moderators will have the option to resolve how they need to take care of individuals who post rude responses. In the meantime, Bluesky will eventually reduce the visibility of those responses on its app. Repeated rude labels on content will even lead to account-level labels and suspensions, it says.

To curb using lists to harass others, Bluesky will remove individual users from the list in the event that they block the list creator. Similar functionality was recently introduced to Starter Packs, a sort of shared list that will help recent users find people to follow on the platform (check TechCrunch Starter Pack).

Bluesky will even scan lists with offensive names or descriptions to limit the potential of harassing others by adding them to a public list with a toxic or offensive name or description. Those who violate Bluesky’s Community Guidelines might be hidden from the app until the list owner makes changes that align with Bluesky’s policies. Users who proceed to create offensive lists will even face further motion, though the corporate didn’t provide details, adding that the lists are still an area of ​​energetic discussion and development.

In the approaching months, Bluesky also intends to move to handling moderation reports through its app, using notifications relatively than counting on email reports.

To combat spam and other fake accounts, Bluesky is launching a pilot that can attempt to routinely detect when an account is fake, scamming or sending spam to users. Combined with moderation, the goal is to have the option to take motion on accounts inside “seconds of receiving a report,” the corporate said.

One of the more interesting developments is how Bluesky will comply with local laws while still allowing free speech. It will use geotags that allow it to hide some content from users in a particular area to comply with the law.

“This allows Bluesky’s moderation service to maintain flexibility in creating spaces for free expression while also ensuring legal compliance so that Bluesky can continue to operate as a service in these geographic regions,” the corporate shared in a blog post. “This feature will be rolled out on a country-by-country basis, and we will endeavor to inform users of the source of legal requests when legally possible.”

To address potential trust and safety issues with videos which have recently been added, the team is adding features like the flexibility to disable autoplay, ensuring videos are labeled, and providing the flexibility to report videos. They are still evaluating what else might need to be added, which might be prioritized based on user feedback.

When it comes to abuse, the corporate says its general framework is “a question of how often something happens versus how harmful it is.” The company focuses on addressing high-impact, high-frequency issues, in addition to “tracking edge cases that could result in significant harm to a few users.” The latter, while only affecting a small number of individuals, causes enough “ongoing harm” that Bluesky will take motion to prevent abuse, it says.

User concerns will be reported via reports, emails and mentions @safety.bsky.app account.

This article was originally published on : techcrunch.com
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Apple Airpods Now With FDA-Approved Hearing Aid Feature

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The newest AirPods are a part of a growing group of hearing aids available over-the-counter.


Apple’s latest Airpods could help those with hearing impairments. The tech company’s software update has been approved by the FDA to be used as hearing aids.

The FDA approved Apple’s hearing aid feature on September 12. The free update, available on AirPods Pro 2, will amplify sounds for the hearing impaired. However, the feature is simply available to adults 18 and older with an iPhone or iPad compatible with iOS 18.

“Today’s approval of over-the-counter hearing aid software for a commonly used consumer audio product is another step that will increase the availability, affordability, and acceptability of hearing support for adults with mild to moderate hearing loss,” said Dr. Michelle Tarver, acting director of the FDA’s Center for Devices and Radiological Health, in a press release. obtained by .

They confirmed the feature’s use after a clinical trial with 118 participants. The results showed that users “achieved similar perceived benefits to those who received a professional fit on the same device.” Apple also announced the brand new development just days before the agency’s approval.

“Hearing health is an essential part of our overall well-being, yet it is often overlooked — in fact, according to Apple’s Hearing Study, as many as 75 percent of people diagnosed with hearing loss go untreated,” said Sumbul Desai, MD, vice chairman of Health at Apple. press release“We’re excited to deliver breakthrough software features in AirPods Pro that put users’ hearing health first, offering new ways to test and get help for hearing loss.”

What’s more, Apple intends its recent AirPods to supply a “world-first” hearing health experience. Noting that 1.5 billion people suffer from hearing loss, the device also goals to forestall and detect hearing problems.

“Your AirPods Pro will transform into your own personalized hearing aid, amplifying the specific sounds you need in real time, such as parts of speech or elements of your environment,” Desai added in a video announcing the event.

The latest AirPods are a part of a growing variety of over-the-counter (OTC) hearing aids. They usually are not only more accessible, but additionally significantly cheaper than prescription medical devices. While they’re designed for individuals with mild to moderate hearing loss, they’ll initially treat those with limited abilities.

AirPods Pro 2 is available now for $249.


This article was originally published on : www.blackenterprise.com
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LinkedIn collected user data for training purposes before updating its terms of service

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LinkedIn scraped user data for training before updating its terms of service

LinkedIn could have trained AI models on user data without updating its terms.

LinkedIn users within the United States — but not within the EU, EEA, or Switzerland, likely as a consequence of data privacy laws in those regions — have the choice to opt out toggle on the settings screen, revealing that LinkedIn collects personal data to coach “AI models to create content.” The toggle isn’t recent. But, as in early reported According to 404 Media, LinkedIn didn’t initially update its privacy policy to handle data use.

The Terms of Service have already been published. updatedbut that sometimes happens well before an enormous change, equivalent to using user data for a brand new purpose like this. The idea is that this offers users the choice to make changes to their account or leave the platform in the event that they do not like the changes. It looks like that is not the case this time.

So what models does LinkedIn train? Its own, the corporate’s says in a Q&A session, including models to put in writing suggestions and post recommendations. But LinkedIn also says that generative AI models on its platform could be trained by a “third-party vendor,” equivalent to its corporate parent Microsoft.

“As with most features on LinkedIn, when you use our platform, we collect and use (or process) data about your use of the platform, including personal data,” the Q&A reads. “This may include your use of generative AI (AI models used to create content) or other AI features, your posts and articles, how often you use LinkedIn, your language preferences, and any feedback you may have provided to our teams. We use this data, in accordance with our privacy policy, to improve or develop the LinkedIn Services.”

LinkedIn previously told TechCrunch that it uses “privacy-enhancing techniques, including redaction and removal of information, to limit personally identifiable information contained in datasets used to train generative AI.”

To opt out of LinkedIn’s data collection, go to the “Data Privacy” section of the LinkedIn settings menu in your computer, click “Data to improve Generative AI,” after which turn off “Use my data to train AI models to create content.” You may try a more comprehensive opt-out through this typebut LinkedIn notes that opting out is not going to affect training that has already taken place.

The nonprofit Open Rights Group (ORG) has asked the Information Commissioner’s Office (ICO), the UK’s independent regulator for data protection laws, to research LinkedIn and other social networks that train on user data by default. Earlier this week, Meta announced it was resuming plans to gather user data for AI training after working with the ICO to simplify the opt-out process.

“LinkedIn is the latest social media company to process our data without asking for our consent,” Mariano delli Santi, a lawyer and policy officer at ORG, said in a press release. “The opt-out model once again proves to be completely inadequate to protect our rights: society cannot be expected to monitor and prosecute every internet company that decides to use our data to train AI. Opt-in consent is not only legally required, but also common sense.”

The Irish Data Protection Commission (DPC), the supervisory authority responsible for monitoring compliance with the GDPR, the EU’s general privacy rules, told TechCrunch that LinkedIn had last week announced that clarifications on its global privacy policy could be published today.

“LinkedIn has informed us that the policy will include an opt-out setting for members who do not want their data used to train AI models that generate content,” a DPC spokesperson said. “This opt-out is not available to EU/EEA members, as LinkedIn does not currently use EU/EEA member data to train or tune these models.”

TechCrunch has reached out to LinkedIn for comment. We will update this text if we hear back.

The need for more data to coach generative AI models has led to more platforms repurposing or otherwise repurposing their vast troves of user-generated content. Some have even taken steps to monetize that content—Tumblr owner Automattic, Photobucket, Reddit, and Stack Overflow are among the many networks licensing data to AI model developers.

Not all of them made opting out easy. When Stack Overflow announced it will begin licensing content, several users deleted their posts in protest — only to see those posts restored and their accounts suspended.

This article was originally published on : techcrunch.com
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