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Article summary:

1. DeepL.com is a superior translation tool compared to Google Translator, offering more accurate translations and alternative phrase options.

2. While DeepL can be used for longer texts, it still requires human editing to ensure the highest quality of translation.

3. DeepL is not considered true artificial intelligence, but rather a machine learning algorithm that relies on data and human input to refine its translations.

Article analysis:

The article titled "Kašlete na Google Translator, přesedlejte na DeepL" provides a comparison between Google Translator and DeepL.com. The author claims that DeepL is a superior translation tool compared to Google Translator. However, the article has several biases and lacks evidence to support its claims.

Firstly, the author claims that DeepL translates ten times better than Google Translator. However, this claim is subjective and lacks any empirical evidence to support it. The author also fails to mention how they arrived at this conclusion or what criteria they used to compare the two tools.

Secondly, the article promotes DeepL as a free translation tool that can be used on mobile devices, browsers, and PC apps. While this may be true for the basic version of DeepL, the author fails to mention that some features are only available in the paid Pro version. For example, the Pro version allows users to translate PDFs, DOCs, and pptx files.

Thirdly, the article highlights some of DeepL's strengths such as offering alternative translations for phrases and sentence structures. However, it fails to mention some of its weaknesses such as its inability to understand context and composition in longer texts. The author also fails to explore counterarguments against using machine translation tools like DeepL instead of human translators.

Fourthly, while the article acknowledges that even the best machine translation tools require human intervention for quality assurance purposes, it downplays this fact by suggesting that users can rely solely on machine translations without any editing or proofreading. This is misleading because machine translations are not always accurate or reliable.

Finally, while the article notes some potential risks associated with using machine translation tools like DeepL (such as losing creativity and stylistic skills), it fails to mention other risks such as privacy concerns related to data collection by these tools.

In conclusion, while there may be some benefits of using machine translation tools like DeepL for short texts or casual communication purposes, relying solely on them for important documents or professional work is not advisable. The article's biased reporting and lack of evidence undermine its credibility and suggest a promotional agenda rather than an objective analysis of both sides of the issue.