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Audio platform Pocket FM uses AI tools to help it expand its content catalog

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Pocket FM app on 3 smartphones

India based audio platform Pocket FM has over 200,000 hours of content on the web site. However, the corporate’s CEO Rohan Nayak believes that the platform still has room to grow when it comes to creating original content and expanding its library to include multiple genres and sub-genres. The fastest way to achieve that is to use artificial intelligence tools that may help produce audio, write strategies, and tailor these stories to different geographies.

“I still believe that our content catalog is not sufficient for our users. There are so many genres and subgenres that we don’t have in our library. I don’t think we have the depth of content that would fall under the adult entertainment category,” Nayak told TechCrunch over the phone.

The company has already established an excellent partnership with ElevenLabs to transform texts into audio series. This resulted in 5x faster production and 30x lower cost compared to professionally generated audio series.

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“We have already tested how these AI adaptations perform in various markets and have seen encouraging results. We are still refining our models for errors, but we believe the technology is good enough to be used in program production,” Nayak said.

One of the AI ​​tools Pocket FM is trying out allows stories to be adapted across regions. The company says it has trained internal models that do not do easy translation, but handle cultural nuances when transforming stories from one region to one other.

He added that the difficult task is to solve the models’ hallucinations within the context of stories spanning a whole lot of episodes. Pocket FM found that it had to address the restrictions of context windows of open source models, in addition to construct maps of the relationships between different entities within the story to maintain character consistency.

Another tool the corporate offers for writers is to test their work as a creative assistant, helping them create alternative stories or giving them plot ideas. The company also plans to use some insights from historical data within the tool to show authors what’s working on the platform.

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Nayak mentioned that while the tool is in its early stages of development, the corporate wants to open up a author’s room to a solo author who might post an episode on a single day. He noted that a author’s room allows you to brainstorm without having to control your creativity, and that’s the predominant idea of ​​this writing assistant.

Additionally, the corporate is investing in creating a success engine that might be based on insights from the platform about which shows develop into hits.

Pocket FM’s ultimate goal is to scale its catalog, on condition that it produces some content itself and produces programming through its network of writers. But to scale and gain popularity, it needs to create hit shows.

“Blockbusters power every content platform. While we have a good start to the funnel with user-generated content, blockbusters are still hard to come by.”

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Pocket FM achieved encouraging results thanks to the implementation of artificial intelligence. It has over 40,000 series on the platform with the help of artificial intelligence in voice creation. What’s more, the corporate generated $3 million in revenue from them. Overall, the platform earned $127 million in fiscal yr 2024.

The company’s most difficult challenge is finding the appropriate balance between AI helping creators and creating content quickly. There is at all times a risk that individuals will use AI to speed up content production and degrade quality. As a result, the platform becomes stuffed with mediocre content and it becomes difficult for the algorithms to distinguish good programs.

Puneet Sharma, a author and lyricist based in India, identified that in a world where a lot work is formulaic, the onus might be on artists to prove the authenticity of their work.

Sharma added that AI tools can help writers generate ideas and learn different styles. However, because of this learning could also be lost through failure within the means of using these tools.

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Nayak said some authors and creators are already using AI tools. The company’s idea is to provide tools together with the context of the story and a platform.

Pocket FM has raised $197 million in multiple rounds from backers including Lightspeed Ventures, Tencent and Times Internet. The company competes on multiple fronts with other players resembling Audible, Omidyar Network-backed Pratilipi and Google-backed Kuku FM.

This article was originally published on : techcrunch.com
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Anysphere, which makes the cursor supposedly collect USD 900 million with a valuation of USD 9 billion

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AI robot face and programming code on a black background.

Anysphere, producer of coding cursor with AI drive, attracted $ 900 million in the recent financing round by Thrive Capital, Financial Times He informed, citing anonymous sources familiar with the contract.

The report said that Andreessen Horowitz (A16Z) and ACCEL also participate in the round, which values ​​about $ 9 billion.

The cursor collected $ 105 million from Thrive, and A16Z with a valuation of $ 2.5 billion, as TechCrunch said in December. Capital Thrive also led this round and in addition participated in A16Z. According to Crunchbase data, the startup has collected over $ 173 million thus far.

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It is alleged that investors, including index ventures and a reference point, attempt to support the company, but plainly existing investors don’t want to miss the opportunity to support it.

Other coding start-ups powered by artificial intelligence also attract the interest of investors. Techcrunch announced in February that Windsurf, a rival for Aklesphere, talked about collecting funds at a valuation of $ 3 billion. Openai, an investor in Anysphere, was supposedly I’m attempting to get windsurf for about the same value.

(Tagstransate) A16Z

(*9*)This article was originally published on : techcrunch.com

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This is the shipping of products from China to the USA

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Shein and Temu icons are seen displayed on a phone screen in this illustration photo

The Chinese retailer has modified the strategy in the face of American tariffs.

Thanks to the executive ordinance, President Donald Trump ended the so -called de minimis principle, which allowed goods value 800 USD or less entering the country without tariffs. It also increases tariffs to Chinese goods by over 100%, forcing each Chinese firms and Shein, in addition to American giants, similar to Amazon to adapt plans and price increases.

CNBC reports that this was also affected, and American buyers see “import fees” from 130% to 150% added to their accounts. Now, nevertheless, the company is not sending the goods directly from China to the United States. Instead, it only displays the offers of products available in American warehouses, while goods sent from China are listed as outside the warehouse.

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“He actively recruits American sellers to join the platform,” said the spokesman ago. “The transfer is to help local sellers reach more customers and develop their companies.”

(tagstotransate) tariffs

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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