AI (Artificial Intelligence)

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At turn of year, Musk’s ‘spicy’ AI feature triggers sour response from Indian regulators

Concerns about AI-generated explicit content arise from Grok’s recent feature, leading to government scrutiny in India. The Centre is calling for stricter regulations on social media platforms like X, emphasizing the need for accountability in light of rising complaints.

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Trump Super PAC Raised More Than $100 Million in Recent Months

The haul highlights how the president’s team has continued aggressive fund-raising from donors with interests before the administration.

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No, Grok can’t really “apologize” for posting non-consensual sexual images

Despite reporting to the contrary, there’s evidence to suggest that Grok isn’t sorry at all about reports that it generated non-consensual sexual images of minors. In a post Thursday night (archived), the large language model’s social media account proudly wrote the following blunt dismissal of its haters: “Dear Community, Some folks got upset over an

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OpenAI reorganizes some teams to build audio-based AI hardware products

OpenAI, the company that developed the models and products associated with ChatGPT, plans to announce a new audio language model in the first quarter of 2026, and that model will be an intentional step along the way to an audio-based physical hardware device, according to a report in The Information. Citing a variety of sources

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Recursive Language Models (RLMs): From MIT’s Blueprint to Prime Intellect’s RLMEnv for Long Horizon LLM Agents

Recursive Language Models aim to break the usual trade off between context length, accuracy and cost in large language models. Instead of forcing a model to read a giant prompt in one pass, RLMs treat the prompt as an external environment and let the model decide how to inspect it with code, then recursively call

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A Coding Implementation to Build a Self-Testing Agentic AI System Using Strands to Red-Team Tool-Using Agents and Enforce Safety at Runtime

In this tutorial, we build an advanced red-team evaluation harness using Strands Agents to stress-test a tool-using AI system against prompt-injection and tool-misuse attacks. We treat agent safety as a first-class engineering problem by orchestrating multiple agents that generate adversarial prompts, execute them against a guarded target agent, and judge the responses with structured evaluation

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