OpenAI Collaborates with US and UK Institutes to Enhance AI Security
OpenAI has partnered with the US Center for AI Standards and Innovation (CAISI) and the UK AI Security Institute (UK AISI) to enhance the security of AI systems, announced on their website. These collaborations focus on identifying and addressing vulnerabilities in AI technologies.
The partnership with CAISI involves evaluating OpenAI's models in areas relevant to national security, such as cybersecurity and chemical-biological domains. This collaboration has led to the identification of novel security vulnerabilities in OpenAI's ChatGPT Agent, which were promptly addressed by OpenAI.
In collaboration with UK AISI, OpenAI has been working on improving safeguards against biological misuse. This ongoing effort includes red-teaming exercises to test and enhance the security measures of AI systems like ChatGPT Agent and GPT-5.
These partnerships highlight the importance of collaboration between AI developers and government bodies to ensure the secure deployment of AI technologies, ultimately benefiting end users by strengthening the security of widely used AI products.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Cybersecurity AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from Cybersecurity
Oct 16 Inlayer, JLINC and Vconic Introduce Human Verification for Calls Oct 16 CTM and Huawei Plan AI Network Security Upgrades in Macao Oct 16 Advantech and DEKRA Partner on Industrial Cybersecurity Compliance Oct 15 Cyfendo Offers AI Code Scanning and Patch Review for Small Businesses Oct 15 Perplexity Open Sources SPACE Agent SandboxCybersecurity AI Weekly
Weekly newsletter about AI in Cybersecurity.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
OpenAI Urges US to Lead Global AI Standards
US Allows Britain to Test American AI Models Before Release
UK AI Minister Warns Cyber Defences Will Likely Be Breached
OpenAI Supports NVIDIA Agent Safety Platform Without Joining It
OpenAI apologizes for access to Australian government systems
Daily AI Brief: the AI news that matters, in your inbox.