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In the ever-changing artificial intelligence (AI) world, there is a place that is gaining an unrival..

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In the ever-changing artificial intelligence (AI) world, there is a place that is gaining an unrivaled status as an AI-based language-specific service. DeepL started in Germany in 2017 and now has 200,000 companies around the world as customers.

DeepL Chief Revenue Officer David Parry Jones, whom Mail Business recently met via video, is in charge of all customer management and support.

DeepL is focusing on securing customers by introducing a large number of services tailored to their needs, such as launching “Deep L for Enterprise,” a corporate product, and “Deep L Voice,” a voice translation solution, last year.

“We are focusing on translators, which are key products, and DeepL Voice is gaining popularity as it is installed in the Teams environment,” Pari-Jones CRO said. “We are also considering installing it on Zoom, a video conference platform.”

DeepL’s voice translation solution is currently integrated into Microsoft’s Teams. If participants in the meeting using Teams speak their own language, other participants can check subtitles that are translated in real-time. As the global video conference market accounts for nearly 90% of Zoom and MS Teams, if DeepL solutions are introduced through Zoom, the language barrier in video conferences will now disappear.

DeepL solutions are all focused on saving time and resources going into translation and delivering accurate results. “According to a study commissioned by Forrester Research last year, companies’ internal document translation time was reduced by 90% when using DeepL solutions,” Parry Jones CRO said, explaining that it is playing a role in breaking down language barriers and strengthening efficiency.

The Asian market, including Korea, a non-English speaking country, is considered a key market for DeepL. CEO Yarek Kutilovsky also visits Korea almost every year and meets with domestic customers.

“The Asia-Pacific region and Japan are behind DeepL’s rapid growth,” said CRO Pari-Jones. In translation services, the region accounts for 45% of sales, he said. “In particular, Japan is the second largest market, and Korea is closely following it.” He explains that Korea and Japan have similar levels of English proficiency, and there are many large corporations that are active in multiple countries, so there is a high demand for high-quality translations.

In Japan, Daiwa Securities is using DeepL solutions in the process of disclosing performance-related data to the world, and Fujifilm and NEC are also representative customers of DeepL. In Korea, Yanolja, Lotte Innovate, and Lightning Market are using DeepL.

DeepL currently only has branches in Japan among Asian countries, and the Korean branch is also considering establishing it, although the exact timing has not been set.

“DeepL continues to improve translation quality and invest at the same time for growth in Korea,” said CRO Pari-Jones. “We need a local team for growth.” We can’t promise you the exact schedule, but (the Korean branch) will be a natural development,” he said.

Meanwhile, as Generative AI services such as ChatGPT become more common, these services are also not the main function, but they also perform compliance levels of translation, threatening translators.

DeepL also sees them as competitors and competes. “DeepL is a translation company, so the difference is that it strives to provide accuracy or innovative language services,” Pari-Jones CRO said. “When comparing translation quality, the gap has narrowed slightly with ChatGPT.” We will continue to improve quality while testing regularly,” he said.

[Reporter Jeong Hojun]



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Three eastern Iowa students charged in nude AI-generated photos case

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Three Cascade High School students accused of creating fake nude images of other students with artificial intelligence have been charged, according to the Western Dubuque Community School District.

Iowa Public Radio reported back in May, that a group of students allegedly attached the victims’ headshots on other images of nude bodies. School officials say they first were made aware of the images on March 25.

The school district says “any student charged as a creator or distributor of materials like those in question will not be permitted to attend school in person at Cascade Junior/Senior High School.”

The district would not give many more details in the case due to the ongoing investigation and their “legal obligation to maintain student confidentiality.”



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5 Key Takeaways | The Law of the Machine (Learning): Solving Complex AI Challenges | Kilpatrick

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As businesses are under increasing pressure to develop and deploy artificial intelligence (AI) tools, their legal departments are facing new challenges at this intersection of innovation, compliance, and risk. Recently, Kilpatrick’s Mike Breslin, Meghan Farmer, and Greg Silberman joined Rome Perlman, Associate General Counsel, National Student Clearinghouse, to explore some of the more subtle and complex issues in the AI legal landscape and provide practical tips for in-house counsel who need to quickly assess and manage their clients’ use and deployment of advanced AI systems. The discussion, sponsored by the Association of Corporate Counsel (ACC) Capital Region Chapter, addressed these topics through the lenses of risk management, regulatory compliance, data privacy, model governance, contracting considerations, and incident classification and response.

Mike, Meghan, and Greg offer the following takeaways from the discussion:

1. Data Underpins Model Performance, Governance, and Risk Mitigation.

High-quality, well-managed data ensures AI model reliability, drives continuous improvement, and provides meaningful context. Establish data management protocols that address collection, storage, processing, and disposal, embed privacy-by-design and track data provenance. Use robust data controls to enable governance, support compliance, and build trust in AI systems.

2. Responsible AI Requires Accountability, Transparency, and Human Oversight.

Organizations must assess AI systems for impact, identify adverse effects, and design for informed human control. Provide clear disclosures about AI capabilities and limitations, and state when content or interactions are AI-generated. Human oversight and regular policy reviews are vital to maintaining ethical and compliant AI use.

3. Classify and Respond to AI Incidents to Manage Risk Effectively.

AI incidents are not just another type of cybersecurity incident. Systematically classifying by domain, root cause, lifecycle stage, and responsible owner is critical for effective response. This enables prompt containment, accurate evidence preservation, clear accountability, and tailored remediation. Apply consistent classification to support trend analysis and continuous improvement across teams.

4. Adopt Best Practices in AI Contracting.

Define permitted uses, clearly allocate IP ownership and data training rights, mandate data governance and privacy compliance, and set performance and bias standards. Require transparency, audit rights, and termination provisions for compliance failures. Continuously monitor contract performance and regulatory developments to manage evolving risks.

5. Implement Practical Controls and Education for Safe, Fair, and Effective AI Use.

Mitigate AI risks with layered controls, including human oversight, privacy-by-design, secure coding, data provenance tracking, and documented policies. Train employees regularly on AI policies, known limitations (such as hallucinations and data retention), and verification of AI outputs. Regularly review and update policies to address new risks.



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New AI Technique Unravels Quantum Atomic Vibrations in Materials

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New AI Technique Unravels Quantum Atomic Vibrations in Materials<br /> – </p> <p> www.caltech.edu













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