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Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Anthropic's Alignment Science team released a study on poisoning attacks on LLM training. The experiments covered a range of model sizes and datasets, and found that only 250 malicious examples in pre-training data were needed to create a "backdoor" vulnerability. Anthropic concludes that these attacks actually become easier as models scale up.
By Anthony Alford
Cloudflare's innovative Merkle Tree Certificates (MTCs) revolutionize WebPKI, enabling a seamless transition to Post-Quantum (PQ) cryptography without performance penalties. By minimizing TLS handshake overhead and integrating Certificate Transparency, MTCs promise enhanced security while addressing latency concerns, paving the way for future-ready internet security.
By Steef-Jan Wiggers
This week's Java roundup for November 3rd, 2025, features news highlighting: a new Jakarta AI specification; the fourteenth milestone release of GlassFish 8.0; second release candidates of Spring Boot 4.0, Spring for GraphQL 2.0 and Spring Batch 6.0; the release of Infinispan 16.0; and the November 2025 edition of Open Liberty.
By Michael Redlich
Researchers from Standford, Princeton, and Cornell have developed a new benchmark to better evaluate coding abilities of large language models (LLMs). Called CodeClash, the new benchmark pits LLMs against each other in multi-round tournaments to assess their capacity to achieve competitive, high-level objectives beyond narrowly defined, task-specific problems.
By Sergio De Simone
Vivek Gupta shares best practices for managing and mentoring ML engineers, from early-career development to senior leadership growth. He breaks down the crucial, distinct skills for Production Machine Learning, including data/model management, building training pipelines, LLM prompt evaluation, privacy/security, and integrating human-in-the-loop processes for reliable, scalable AI systems.
By Vivek Gupta
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