AI News Feed
These are AI-generated summaries I use to keep tabs on daily news.
Daily Tech Newsletter - 2025-12-22
AI Copyright and Legal Implications
The increasing use of copyrighted material to train AI models has brought the issue of AI copyright and fair use into focus. While humans face legal consequences for downloading copyrighted content, the legality of using the same content for training AI models remains debated. A whitepaper commissioned by the FSF supports the legal defensibility of using copyrighted work to train ML models. However, a recent judgment in the Anthropic case differentiated between scenarios where copies are directly used to train LLMs (deemed "fair use") and when downloaded pirated copies are retained in a central library for general purposes (not deemed "fair use"). The key distinction hinges on the notion that copyright grants control over making copies, not an eternal claim on knowledge learned from a copy.
Relevant URLs:
Weaponizing LLMs - AI-Generated Knockoff Books on Amazon
Amazon's Kindle Direct Publishing (KDP) platform is being exploited by AI-generated knockoff books, created using readily available AI tools and online tutorials, leading to copyright concerns, and author frustration. These knockoffs, often of newly released books, frequently reuse titles but are categorized as summaries or workbooks to skirt copyright law. Authors report Amazon's content moderation is insufficient, resulting in the proliferation of poor-quality, fraudulent content that devalues the online bookselling experience. The creation of these fake books is driven by the motive of "passive income" generation, leveraging AI tools to create and publish content quickly and easily.
Relevant URLs:
Accelerating LLM Inference with KV Caching
KV caching is a vital optimization technique for improving the speed of large language model (LLM) inference, particularly as the length of generated sequences increases. Without KV caching, the model redundantly recomputes attention over all previous tokens at each step, leading to quadratic growth in computation. KV caching addresses this by storing previously computed keys (K) and values (V) for earlier tokens, avoiding their re-computation for subsequent tokens. Benchmarks demonstrate a significant speedup: generating 1000 tokens with a gpt2-medium model took about 21.7 seconds with KV caching, compared to over 107 seconds without it. The trade-off is increased memory usage to store the cached keys and values.
Relevant URLs:
Streamlining Code Review with AI and GitHub Diffs
A new workflow allows developers to quickly obtain AI-powered code reviews by appending ".diff" to a GitHub Pull Request (PR) URL, which provides the raw diff to input into an LLM like Claude or ChatGPT. This method enables a rapid first pass to identify potential issues and edge cases before human peer review, promoting cleaner code and potentially shortening development cycles. It eliminates the need for enterprise-level tools and browser extensions, providing accessible automated feedback on code changes.
Relevant URLs:
Anthropic Releases Bloom: An Open-Source Framework for AI Model Evaluation
Anthropic has launched Bloom, an open-source, agentic framework to automate the behavioral evaluation of AI models in order to address the scalability problem in safety and alignment evaluations. Bloom can generate tailored evaluation suites from a single behavior specification, utilizing a four-stage pipeline: Understanding, Ideation, Rollout, and Judgement. Its design supports unified model API access (LiteLLM), experiment tracking, and is validated for alignment-focused behaviors. Anthropic is positioning Bloom as complementary to Petri, with Bloom focused on creating targeted evaluation suites, while Petri offers broader coverage.
Relevant URLs: