It seemed that iOS was unwavering. Until this malware slipped in App Store and started reading screenshots

Talk about iOS (usually) to be synonymous with Talk about security. But there is no infallible operating system. In the case of Android, we are quite accustomed to the fact that occasionally Some type of malware in Play Storebut in Apple’s application store this is not common. For the first time, a malware capable of reading screenshots has been found in App Store. Is, According to Kasperskythe first case detected of an app published in APP Store capable of using technology to extract image text using Google technology. The Antivirus company has explained that this malware is part of a campaign that sought to attack users to find cryptographic keys. The severity of the matter comes from the distribution method: applications infected with both iOS and Android. In the case of Android, these apps exceeded 240,000 downloads. These apps were varied and did not follow a thematic pattern. Some were “Chat AI”, other Delivery apps, others of messaging … Some of these applications had thousands of downloads in the Apple application store. What was its operation? In both cases, the same. Apps executed technology OCR of Googlea Google Cloud solution capable of recognizing text automatically. Once we gave apps gallery permits, they were able to look for text in our images and send it to the server. Thus, the attackers were made with cryptocurrency wallet passwords or with phrases and recovery codes of any app. From Kaspersky they affirm that “they cannot confirm with certainty that the infection has been the result of an attack on the supply chain or a deliberate action of developers.” Similarly, they point out that there may still be apps with this malware available in application stores. As we always indicate from Xataka, it is crucial not to give gallery permits to apps in which we do not trust 100%. Image | Xataka In Xataka | How to detect and eliminate malware with MSRT, the hidden Windows 10 and 11 tool

I started reading ‘Cointelligence’ with a lot of skepticism. Its reasonableness makes it an essential book on AI

If the readings on productivity They are a minefield in which you have to dodge bombs before finding gold, the AI ​​readings are even more so. Most are divided into two large groups: Unbridled techno-optimism. Apocalyptic catastrophism. And that’s if you’re lucky and it’s not a scam to sell you a course. That’s why I celebrate when I find a book like ‘Co-intelligence‘, by Ethan Mollick, who shines for its balance. Cold head. It recognizes the existential risks, but focuses on how to pragmatically leverage AI today. As a Wharton professor specializing in innovation and entrepreneurship, Mollick has been on the front lines of observing and experimenting with AI in education. Its central concept of ‘cointelligence’ –see AI as a co-worker, not as a threat nor as a messianic savior– is quite persuasive. And he gives concrete examples from his classes at Wharton to show how AI can amplify human capabilities instead of replacing them. Perhaps the most valuable is in his ideas about how AI is already transforming education and employment (perhaps in some latitudes more than others). For example, in his analysis of how students already use ChatGPT and how that forces rethink assessments and homework. He also has a very clear vision of how companies should adapt to this panorama: not by banning AI, but by finding ways to integrate it productively. On the B side of the album, the book has some weak points. For example, it tangentially transmits a certain hasteas if it had been written in haste to take advantage of the timing. Some sections, especially those that point to predictions for the future, could have directly been better developed. What I find most problematic is the over-reliance on examples from academia. His experience as a professor is valuable and supports the book, but his case studies focus too much on university professors… and elite students. This greatly limits the applicability of the conclusions to sectors other than academia. and there I missed a somewhat more diverse analysis of use cases in SMEs or other work sectors. It would have greatly strengthened his argument about the universal adaptability of AI. Despite these asterisks, ‘Cointelligence’ is a good contribution to the literature of the early years of generative AI. A good framework to think about AI that does not fall into fear but does not allow itself to be overwhelmed by the train of thought. hype. It is a book that lacks all the answers, but that is not what it intends. Rather it brings us closer to asking ourselves the right questions. It’s already a lot. For anyone looking to understand what position to take in this rise of generative AI, I find this a good read. It is not a perfect book, but at least it offers a calm perspective and nuanced analysis. Surely it’s what we need most at this point in the film. Co-intelligence: Living and working with AI In Xataka | I thought I should always read new books, until rereading showed me what I was missing Featured image | Xataka, Connect

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