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Announcing AI Stage at TechCrunch Disrupt 2024

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AI Stage Disrupt 2024

We are excited to announce that we’ve added a dedicated AI stage presented by Google Cloud to TechCrunch Disrupt 2024. It will join other industry-focused stages similar to Fintech, SaaS, and Space — all under one big roof.

Check out the preliminary roadmap below and check back often for updates – we’ve lots more so as to add to the AI ​​stage.

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AI Stage program at TechCrunch Disrupt 2024

From Search Engines to Knowledge Engines: Perplexity Moves Towards an AI-Enabled Web

with Aravind Srinivas (Perplexity)

EmbarrassmentAI-powered search may or will not be the subsequent step in how we interact with the online and knowledge typically. But the corporate is actually risking every little thing to make that future a reality, even when it ruffles a number of feathers along the best way. Hear how the CEO plans to tackle all comers on this latest tech category.

The Business of Labeling: A Deep Dive into the Scale of AI’s Massive Growth

with Alexander Wang (Scale AI)

In 2016, when AI scales was founded, few people could have predicted that the corporate that builds tools for training, testing, and maintaining generative AI models would eventually grow right into a $14 billion business. In retrospect, it seems almost inevitable that Scale would, well, grow quickly, given the explosive growth experienced by a lot of its early customers, including OpenAI. In this conversation with Scale AI founder Alexander Wang, we discuss the corporate’s journey to date and the role Scale AI currently plays within the generative AI ecosystem.

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How Generative AI Is Flooding the Web with Disinformation

with Pamela San Martin (Oversight Board), Imran Ahmed (CCDH) and speakers to be announced

As generative AI tools develop into more widely available—and cheaper and even free to make use of—they’re being misused by a variety of actors, including state actors, to create deepfakes and spread disinformation online. In this session, we’ll hear from experts in regards to the kinds of deepfakes currently circulating online and a few possible ways to combat this threat.

Are “open” AI models really higher?

with Ali Farhadi (Allen Institute for Artificial Intelligence), Irene Solaiman (Hugging Face), and speakers shall be announced

There’s a war raging within the AI ​​industry between firms supporting “open” AI models (models released under permissive licenses that could be tuned and reused across applications) and closed-source models (models protected by paid services and APIs). Is one approach higher than the opposite? The answer isn’t as obvious because it might sound. In this talk, we’ll explore the differences between open-source and closed-source models, in addition to subtle but necessary variations on open-source licenses.

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with Sarah Myers West (AI Now), Jingna Zhang (Cara) and Ben Zhao (University of Chicago)

The explosion of AI has created latest ethical dilemmas and exacerbated old ones, while lawsuits are pouring in left and right. This threatens each latest and established AI firms, in addition to the creators and staff whose work powers the models. A panel of experts in AI, copyright, and ethics weighs in on this complex and rapidly evolving issue.

But is it art? The evolving role of generative AI in music and video production

with Mikey Shulman (Suno), Amit Jain (Luma AI), and other speakers to be announced

Generative AI is increasingly capable of making video, music, and other media on demand. But who actually wants it, and why? This panel of AI startups will discuss the growing markets for generative media and the way they’ll serve them without harming or displacing the artists they supposedly empower.

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About TechCrunch Disrupt 2024

TechCrunch Disrupt 2024 is the place to search out innovation at every stage of your startup journey. Whether you’re a first-time founder with a revolutionary idea, a seasoned startup seeking to scale, or an investor searching for the subsequent big thing, TechCrunch Disrupt offers unparalleled resources, connections, and expert insights to propel your enterprise forward. More than 10,000 startup leaders will attend this yr’s event October 28–30 in San Francisco.

We can’t wait to listen to from these AI leaders at this yr’s show. Buy your tickets here

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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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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