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💥 Explore this trending post from Hacker News 📖 📂 **Category**: 📌 **What You’ll Learn**: [Submitted on 15 Jan 2026 (v1), last revised 19 Feb 2026 (this version, v2)] View a PDF of the paper titled Alignment Pretraining: AI Discourse Causes Self-Fulfilling (Mis)alignment, by Cameron Tice and 5 other authors View PDF HTML (experimental) Abstract:Pretraining corpora contain extensive discourse about AI systems, yet the causal influence of this discourse on downstream alignment remains poorly understood. If prevailing descriptions of AI behaviour are predominantly negative, LLMs may internalise corresponding behavioural priors, giving rise to self-fulfilling misalignment. This paper provides the first…

💥 Explore this must-read post from Hacker News 📖 📂 **Category**: 💡 **What You’ll Learn**: Shutterstock Inc. will pay $35 million to settle Federal Trade Commission allegations that the online digital photo and video platform illegally made tens of millions of dollars from a range of unfair and deceptive practices, including charging consumers for products without their informed consent and making it difficult to cancel subscriptions.“Subscription and negative option features can be beneficial for both companies and consumers, making renewal simpler and streamlining payment processes,” said Christopher Mufarrige, Director of the FTC’s Bureau of Consumer Protection. “But these benefits depend…

🔥 Read this trending post from Hacker News 📖 📂 **Category**: 📌 **What You’ll Learn**: Agora-1 learns two distinct functions. First, it learns how the world state evolves over time in response to player interaction. To do this, we train a model directly on the internal state of one or more games—in the case of Agora-1, GoldenEye. This model learns the underlying gameplay dynamics and how state transitions occur from player actions. Second, Agora-1 learns how to render that shared state visually. This is accomplished using a DiT-based world model conditioned directly on the shared game state, rather than prompts,…

✨ Check out this trending post from Hacker News 📖 📂 **Category**: 💡 **What You’ll Learn**: We are in the age of inference. Billion- to trillion-parameter neural networks are run on specialized accelerators at quadrillions of operations per second to generate media, author software, and fold proteins at massive scale. Inference workloads are more variable and less predictable than the training workloads that previously dominated. That makes them a natural fit for serverless computing, where applications are defined at a level above the (virtual) machine so that they can be more readily scaled up and down to handle variable load.…