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title: Best Ars Technica posts — August 2025 | daily.dev
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og:description: The most upvoted Ars Technica posts from August 2025, curated by the daily.dev community.
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# Best of Ars Technica — August 2025

1. 1  
[](https://daily.dev/posts/adult-sites-are-stashing-exploit-code-inside-racy-svg-files-umcf1drk4 "Adult sites are stashing exploit code inside racy .svg files")  
Article  
![Avatar of arstechnica](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/80883e0e48a34b5ebcf93777016cb3fe)Ars Technica · 1y  
Adult sites are stashing exploit code inside racy .svg files  
Adult websites are exploiting SVG image files to embed malicious JavaScript code that automatically generates Facebook likes when users click on the images. Unlike traditional image formats, SVG files can contain executable code, making them vulnerable to attacks like cross-site scripting and clickjacking. The malicious code is heavily obfuscated using techniques like JSFuck to avoid detection, allowing these sites to artificially boost their social media engagement through unwitting user interactions.  
178  
29
2. 2  
[](https://daily.dev/posts/college-student-s-time-travel-ai-experiment-accidentally-outputs-real-1834-history-zqwqjlx8x "College student’s “time travel” AI experiment accidentally outputs real 1834 history")  
Article  
![Avatar of arstechnica](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/80883e0e48a34b5ebcf93777016cb3fe)Ars Technica · 1y  
College student’s “time travel” AI experiment accidentally outputs real 1834 history  
A computer science student created TimeCapsuleLLM, an AI language model trained exclusively on Victorian-era London texts from 1800-1875\. When prompted with "It was the year of our Lord 1834," the model unexpectedly generated text referencing real historical protests and Lord Palmerston's actions from that exact year. The student discovered through fact-checking that these were actual historical events, demonstrating how AI models trained on period texts can inadvertently capture and reproduce authentic historical information. This project is part of a growing field of Historical Large Language Models (HLLMs) that aim to recreate linguistic patterns and knowledge frameworks from past eras.  
56  
16
3. 3  
[](https://daily.dev/posts/zuckerberg-s-ai-hires-disrupt-meta-with-swift-exits-and-threats-to-leave-421loeeqh "Zuckerberg’s AI hires disrupt Meta with swift exits and threats to leave")  
Article  
![Avatar of arstechnica](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/80883e0e48a34b5ebcf93777016cb3fe)Ars Technica · 1y  
Zuckerberg’s AI hires disrupt Meta with swift exits and threats to leave  
Meta faces internal disruption as newly hired AI executives, including OpenAI's ChatGPT co-creator Shengjia Zhao, threaten to quit shortly after joining. Zuckerberg is conducting Meta's biggest leadership reorganization in 20 years, bringing in high-profile AI talent like former Scale AI CEO Alexandr Wang and former GitHub chief Nat Friedman. However, several new AI hires have already left after brief tenures, highlighting the challenges of integrating external talent into Meta's culture while competing in the AI race.  
22  
5
4. 4  
[](https://daily.dev/posts/is-the-ai-bubble-about-to-pop-sam-altman-is-prepared-either-way--xomxawgns "Is the AI bubble about to pop? Sam Altman is prepared either way.")  
Article  
![Avatar of arstechnica](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/80883e0e48a34b5ebcf93777016cb3fe)Ars Technica · 1y  
Is the AI bubble about to pop? Sam Altman is prepared either way.  
OpenAI CEO Sam Altman warns that investors are overexcited about AI, predicting someone will lose a "phenomenal amount of money" in what he compares to the dot-com bubble. This comes as OpenAI seeks a $500 billion valuation, up from $300 billion months earlier. Meanwhile, new MIT research shows 95% of enterprise AI pilots fail to deliver rapid revenue acceleration, though purchased AI tools succeed 67% of the time compared to internally built systems. The failures are attributed to implementation problems and learning gaps rather than AI model quality itself.  
20  
3
5. 5  
[](https://daily.dev/posts/study-social-media-probably-can-t-be-fixed-cbxzvyxwn "Study: Social media probably can’t be fixed")  
Article  
![Avatar of arstechnica](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/80883e0e48a34b5ebcf93777016cb3fe)Ars Technica · 1y  
Study: Social media probably can’t be fixed  
Researchers from the University of Amsterdam used AI simulations to study social media dysfunction and found that problems like echo chambers, attention inequality, and extreme content amplification are structurally embedded in social media architecture itself. Their study tested six proposed intervention strategies including chronological feeds, diversity boosting, and bridging algorithms, but concluded that none would be effective because the underlying structural dynamics are too robust to resolve with surface-level changes.  
17  
8
6. 6  
[](https://daily.dev/posts/an-inner-speech-decoder-reveals-some-mental-privacy-issues-0hm0lluvw "An inner-speech decoder reveals some mental privacy issues")  
Article  
![Avatar of arstechnica](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/80883e0e48a34b5ebcf93777016cb3fe)Ars Technica · 1y  
An inner-speech decoder reveals some mental privacy issues  
Stanford researchers developed a brain-computer interface that can decode inner speech directly from neural signals, bypassing the need for patients to physically attempt speaking. This breakthrough could help severely paralyzed individuals communicate more easily, but raises significant mental privacy concerns since inner monologues contain private thoughts. The team implemented safeguards to protect patient privacy while working with four paralyzed participants who had electrode arrays implanted in their motor cortex.  
12  
1

[See all Ars Technica archives](/sources/arstechnica/best-of)

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