Lakera Launches API to Protect Large Language Models from Malicious Attacks


In a recent paper, the Seed team at ByteDance revealed that performance fluctuations in large language models when processing ultra-long texts are mainly caused by the phase sensitivity of block-based KV cache compression technology. To reduce memory consumption during long-context reasoning, this technique compresses continuous token windows into fewer entries by using a fixed stride, but it introduces new position coordinates for tokens relative to the compressed window, causing retrieval bias and leading to performance fluctuations.
Glassdoor data shows a significant decline in employee satisfaction with companies introducing AI. Between 2019 and 2026, the proportion of comments involving keywords such as AI and large language models increased by over 240%. However, positive reviews dropped from 81% to 43%, while negative reviews rose to 53%, reflecting a shift in workplace attitudes toward AI implementation towards the negative.
Integrating video generation is easy, but switching models is painful due to inconsistent endpoints, parameters, statuses, polling, and outputs. OpenRouter's unified async video generation API standardizes workflows, simplifying development and reducing integration costs.....
OpenAI disbanded its preparedness team late last month, FT reported Aug 17. The team assessed frontier model risks such as bio/chemical and cyberattacks and devised mitigations; duties were split by risk area into business teams. This follows disbanding of AGI readiness and superalignment teams, showing a shift from safety-oriented public-interest governance.....
A team from the University of York and the University of Calgary analyzed AI programming-related posts on Reddit and found that AI programming agents frequently cause problems due to excessive permissions, including overwriting files, deleting important data, and generating malicious code. The study collected 3801 posts labeled with large models from February 2023 to March 2026, filtered out 446 safety-related posts, and analyzed more than 6000 comments, reflecting the community's ongoing concern about AI programming security issues.