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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.

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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.

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“(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.

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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.

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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.

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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.

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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.

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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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One of the last AI Google models is worse in terms of safety

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The Google Gemini generative AI logo on a smartphone.

The recently released Google AI model is worse in some security tests than its predecessor, in line with the company’s internal comparative test.

IN Technical report Google, published this week, reveals that his Flash Gemini 2.5 model is more likely that he generates a text that violates its security guidelines than Gemini 2.0 Flash. In two indicators “text security for text” and “image security to the text”, Flash Gemini 2.5 will withdraw 4.1% and 9.6% respectively.

Text safety for the text measures how often the model violates Google guidelines, making an allowance for the prompt, while image security to the text assesses how close the model adheres to those boundaries after displaying the monitors using the image. Both tests are automated, not supervised by man.

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In an e-mail, Google spokesman confirmed that Gemini 2.5 Flash “performs worse in terms of text safety for text and image.”

These surprising comparative results appear when AI is passing in order that their models are more acceptable – in other words, less often refuse to answer controversial or sensitive. In the case of the latest Llam Meta models, he said that he fought models in order to not support “some views on others” and answers to more “debated” political hints. Opeli said at the starting of this yr that he would improve future models, in order to not adopt an editorial attitude and offers many prospects on controversial topics.

Sometimes these efforts were refundable. TechCrunch announced on Monday that the default CHATGPT OPENAI power supply model allowed juvenile to generate erotic conversations. Opeli blamed his behavior for a “mistake”.

According to Google Technical Report, Gemini 2.5 Flash, which is still in view, follows instructions more faithfully than Gemini 2.0 Flash, including instructions exceeding problematic lines. The company claims that regression might be partially attributed to false positives, but in addition admits that Gemini 2.5 Flash sometimes generates “content of violation” when it is clearly asked.

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“Of course, there is a tension between (after instructions) on sensitive topics and violations of security policy, which is reflected in our assessment,” we read in the report.

The results from Meepmap, reference, which can examine how models react to sensitive and controversial hints, also suggest that Flash Gemini 2.5 is much less willing to refuse to reply controversial questions than Flash Gemini 2.0. Testing the TechCrunch model through the AI ​​OpenRoutter platform has shown that he unsuccessfully writes essays to support human artificial intelligence judges, weakening the protection of due protection in the US and the implementation of universal government supervisory programs.

Thomas Woodside, co -founder of the Secure AI Project, said that the limited details given by Google in their technical report show the need for greater transparency in testing models.

“There is a compromise between the instruction support and the observation of politics, because some users may ask for content that would violate the rules,” said Woodside Techcrunch. “In this case, the latest Flash model Google warns the instructions more, while breaking more. Google does not present many details about specific cases in which the rules have been violated, although they claim that they are not serious. Not knowing more, independent analysts are difficult to know if there is a problem.”

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Google was already under fire for his models of security reporting practices.

The company took weeks to publish a technical report for the most talented model, Gemini 2.5 Pro. When the report was finally published, it initially omitted the key details of the security tests.

On Monday, Google published a more detailed report with additional security information.

(Tagstotransate) Gemini

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This article was originally published on : techcrunch.com
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Aurora launches a commercial self -propelled truck service in Texas

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The autonomous startup of the Aurora Innovation vehicle technology claims that it has successfully launched a self -propelled truck service in Texas, which makes it the primary company that she implemented without drivers, heavy trucks for commercial use on public roads in the USA

The premiere appears when Aurora gets the term: In October, the corporate delayed the planned debut 2024 to April 2025. The debut also appears five months after the rival Kodiak Robotics provided its first autonomous trucks to clients commercial for operations without a driver in field environments.

Aurora claims that this week she began to freight between Dallas and Houston with Hirschbach Motor Lines and Uber Freight starters, and that she has finished 1200 miles without a driver to this point. The company plans to expand to El Paso and Phoenix until the top of 2025.

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TechCrunch contacted for more detailed information concerning the premiere, for instance, the variety of vehicles implemented Aurora and whether the system needed to implement the Pullover maneuver or the required distant human assistance.

The commercial premiere of Aurora takes place in a difficult time. Self -propelled trucks have long been related to the necessity for his or her technology attributable to labor deficiencies in the chairman’s transport and the expected increase in freigh shipping. Trump’s tariffs modified this attitude, not less than in a short period. According to the April analytical company report from the commercial vehicle industry ACT researchThe freight is predicted to fall this yr in the USA with a decrease in volume and consumer expenditure.

Aurora will report its results in the primary quarter next week, i.e. when he shares how he expects the present trade war will affect his future activity. TechCrunch contacted to learn more about how tariffs affect Auror’s activities.

For now, Aurora will probably concentrate on further proving his safety case without a driver and cooperation with state and federal legislators to just accept favorable politicians to assist her develop.

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At the start of 2025, Aurora filed a lawsuit against federal regulatory bodies after the court refused to release the appliance for release from the protection requirement, which consists in placing warning triangles on the road, when the truck must stop on the highway – something that’s difficult to do when there isn’t a driver in the vehicle. To maintain compliance with this principle and proceed to totally implement without service drivers, Aurora probably has a man -driven automotive trail after they are working.

(Tagstranslate) Aurora Innovation

This article was originally published on : techcrunch.com
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Sarah Tavel, the first woman of the Benchmark GP, goes to the Venture partner

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Eight years after joining Benchmark as the company’s first partner, Sarah Tavel announced that she was going to a more limited role at Hapeure Venture.

In his latest position as a partner Venture Tavel will proceed to invest and serve existing company boards, but may have more time to examine “AI tools on the edge” and fascinated with the direction of artificial intelligence, she wrote.

Tavel joined Benchmark in 2017 after spending a half years as a partner in Greylock and three years as a product manager at Pinterest. Before Pinterest, Tavel was an investor in Bessemer Venture Partners, where she helped Source Pinterest and Github.

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Since its foundation in 1995, the benchmark intentionally maintained a small team of six or fewer general partners. Unlike most VC corporations, wherein older partners normally receive most of the management and profits fees, the benchmark acts as an equal partnership, and all partners share fees and returns equally.

During his term as a general partner of Benchmark, Tavel invested in Hipcamp on the campsite, chains of cryptocurrency intelligence startups and the Supergreaty cosmetic platform, which was purchased by Whatnot in 2023. Tavel also supported the application for sharing photos of Paparazhi, which closed two years ago, and the AI ​​11x sales platform, about which TechCrunch wrote.

(Tagstotransate) benchmark

This article was originally published on : techcrunch.com
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