The Cognitive Impact of LLMs: What AI Is Doing to Learning, Memory, and Brain Activity Quick answer (featured-snippet ready) LLMs can reduce immediate cognitive effort and change neural engagement patterns, which correlates with lower recall and more homogeneous outputs — but evidence is early and limited. Key takeaway: LLMs are powerful for augmentation, but unchecked […]
Sora deepfake safety: What OpenAI’s Sora launch teaches us about protecting AI-generated likenesses Short answer (featured snippet): Sora deepfake safety refers to the combination of user consent controls, content guardrails, provenance signals, and moderation systems that OpenAI has applied to its Sora app to limit misuse of AI-generated faces and short videos. Key elements are […]
Caste bias in LLMs: Why GPT-5 and Sora reproduce Indian caste stereotypes and what to do about it What is caste bias in LLMs? — A quick featured-snippet answer Caste bias in LLMs is when large language and multimodal models reproduce, amplify, or normalize harmful stereotypes and dehumanizing representations tied to India’s caste system. These […]
AI Last Mile: Turning Generative AI Pilots into Everyday Operational Value 1. Intro — Quick answer (featured-snippet friendly) TL;DR: The AI last mile is the operational gap between promising generative AI pilots and measurable P&L outcomes. The solution is AI operational excellence — rigorous process documentation for AI, collaboration tooling, and AI change management that […]
Vision-LLM typographic attacks: what they are, why they matter, and how to harden multimodal products Vision-LLM typographic attacks are adversarial typographic attacks that exploit how vision-enabled LLMs parse text in images and follow instructional directives to produce incorrect or harmful outputs. Quick snippet: Vision-LLM typographic attacks are adversarial inputs that misuse text in images (signage, […]
Neural Fields Dynamic CT: How Continuous Neural Representations and PDE Motion Models are Rewriting Dynamic CT Quick answer (featured-snippet friendly): Neural fields dynamic CT uses continuous neural-field representations combined with PDE motion models and end-to-end learning (E2E-DEcomp) to reconstruct time-resolved CT volumes more accurately and with fewer artifacts than traditional grid-based dynamic inverse imaging methods. […]
Honey ChatGPT integration: What It Means for Conversational Shopping, AI Shopping Assistants, and Affiliate Deal Aggregation Featured snippet (one sentence): The Honey ChatGPT integration surfaces Honey’s product links, real‑time pricing, merchant options and exclusive offers inside AI chat responses—enabling conversational shopping, faster price comparison, and affiliate and deal aggregation within AI shopping assistants. Intro — […]
Anthropic opt out: How to stop Claude chats being used for training Intro — TL;DR and quick answer Quick answer: To opt out of having your Claude conversations used as training data, sign in to Claude, go to Account > Privacy Settings, and turn off the toggle labeled “Help improve Claude.” New users are asked […]
Alexa+ devices: What the Amazon Fall Hardware Event 2025 Means for Smart Home Edge AI TL;DR — Quick summary Alexa+ devices are Amazon’s new class of Echo and Ring/Blink hardware designed to run the Alexa+ chatbot and perform on-device Edge AI for smarter, faster, and more private home experiences. Announced at the Amazon fall hardware […]
Model Context Protocol (MCP): How Delinea’s MCP Server Secures Agent Credential Access Intro — Quick answer Model Context Protocol (MCP) is a standard for secure, constrained interactions between AI agents and external systems. The Delinea MCP server acts as a proxy that enables agent credential access without exposing long‑lived secrets by issuing short‑lived tokens, evaluating […]
