Technology
The Movie Gen Meta model provides realistic video with sound, so we can finally have infinite Moo Deng

No one really knows yet what generative video models are good for, but that does not stop firms like Runway, OpenAI, and Meta from investing thousands and thousands of their development. The latest version of Meta is titled Movie Genand true to its name, it turns text prompts into relatively realistic video with sound… but luckily no voice yet. And it’s sensible that they do not post it publicly.
Movie Gen is definitely a set (or “cast” as they call it) of basic models, the most important of which is the text-to-video bit. Meta claims it outperforms the likes of Runway Gen3, the newest LumaLabs release, and Kling 1.5, although as all the time, this type of thing shows more that they are playing the identical game than Movie Gen winning. The specs can be present in Meta’s release article describing all components.
Sound is generated to match the content of the video, adding, for instance, engine sounds corresponding to the movements of the automotive, the sound of a waterfall within the background, or thunder mid-video when required. He’ll even add music if he thinks it is vital.
It was trained on “a combination of licensed and publicly available datasets” that they called “proprietary/commercially sensitive” and provided no further details about it. We can only guess, which means there are various videos on Instagram and Facebook, in addition to some partner materials and rather more, that usually are not properly shielded from scrapers – i.e. “publicly available”.
However, Meta is clearly aiming here not only to say the “state-of-the-art” crown for a month or two, but for a practical, soup-to-nuts approach during which a quite simple material can be changed into a solid end product, a natural language prompt. Things like “imagine me as a baker baking a shiny hippopotamus-shaped cake during a storm.”
For example, one in every of the sticking points with these video generators is how difficult they have an inclination to be to edit. If you request a video of an individual crossing the road and also you realize that you just want the person to walk from right to left, not left to right. There’s a very good probability the entire shot will look different when you repeat the prompt with additional instruction. The meta adds an easy, text-based editing method where you can just say “change the background to a busy intersection” or “change her clothes to a red dress” and she is going to attempt to make that change, nevertheless it’s a change.
Camera movements are also generally understood, and things like “tracking shot” and “panning left” are taken into consideration when generating video. It’s still quite clunky in comparison with actual camera controls, nevertheless it’s significantly better than nothing.
The model limitations are a bit strange. It generates video with a width of 768 pixels, a dimension familiar to most from the famous but outdated 1024×768 resolution, but which can be thrice the width of 256, so it plays well with other HD formats. The Movie Gen system upscales this resolution to 1080p, which is the source of the claim that it produces this resolution. Not entirely true, but we’ll leave them alone because upscaling is surprisingly effective.
Oddly enough, it generates as much as 16 seconds of video… at 16 frames per second, a frame rate that nobody in history has ever wanted or asked for. However, you can also record 10 seconds of video at 24 frames per second. Lead with it!
As for why it doesn’t play the voice… well, there are probably two reasons. First of all, it is extremely difficult. Generating speech is now easy, but matching it to lip movements and lip movements to faces is a rather more complicated proposition. I do not blame them for leaving it until later because it could have been a one-minute fail. Someone might say, “generate a clown delivering the Gettysburg address by riding around on a little bicycle” – nightmare fuel primed for popularity.
The second reason might be political: releasing a deepfake generator a month before the major elections is… not one of the best for optics. A practical preventive step is to barely limit its capabilities so that if malicious actors try to make use of it, it requires real work on their part. You can actually mix this generative model with a speech generator and an open mouth sync generator, but you can’t just generate a candidate making crazy claims.
“Movie Gen is currently purely an AI research concept, and even at this early stage, security is a top priority, as it is with all of our generative AI technologies,” a Meta representative said in response to TechCrunch’s questions.
Unlike, say, Llama’s large language models, Movie Gen is not going to be publicly available. You can replicate these techniques to some extent by following the research paper, however the code is not going to be published apart from the “baseline evaluation prompt dataset,” a record of the prompts used to generate the test videos.
Technology
One of the last AI Google models is worse in terms of safety

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.
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.”
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
Technology
Aurora launches a commercial self -propelled truck service in Texas

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.
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
Technology
Sarah Tavel, the first woman of the Benchmark GP, goes to the Venture partner

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.
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
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