UsefulAI
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Microsoft Simplifies Hyperlinking in Word
Read Full Article: Microsoft Simplifies Hyperlinking in Word
Microsoft has streamlined the process of adding hyperlinks in Word documents, allowing users to simply paste a link over the text they wish to hyperlink, eliminating the need to open a menu or use the CTRL + K shortcut. This update, which mirrors the functionality found in WordPress and other content management systems, is designed to enhance efficiency by reducing the number of steps required for hyperlinking. The feature is being rolled out to Word for the web and requires version 2511 or later for Windows and version 16.104 or later for Mac. This matters because it simplifies a common task, saving time for users across different platforms.
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ChatGPT’s Memory Limitations
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Chat GPT threads are experiencing issues with memory retention, as demonstrated by a case where a set of programming rules was forgotten just two posts after being reiterated. The rules included specific naming conventions and movement replacements, which were supposed to be consistently applied but were not remembered by the AI. This raises concerns about the reliability of AI in maintaining context over extended interactions. Such limitations could prompt users to consider alternative AI models like Cursor and Claude for tasks requiring better memory retention. This matters because it highlights the importance of memory in AI for consistent and reliable performance in applications.
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High RAM Prices Boost Profits for Memory Makers
Read Full Article: High RAM Prices Boost Profits for Memory Makers
High RAM prices, driven by supply shortages and increased demand, are leading to record-setting profits for memory manufacturers like Samsung, SK Hynix, and Micron. Samsung's operating profit is projected to soar to between 19.9 and 20.1 trillion Korean won in Q4 2025, a significant jump from the previous year, while SK Hynix attributes its highest-ever quarterly performance to the growing demand for AI infrastructure. Micron has also seen a substantial increase in net income, highlighting the impact of the AI boom on the memory market. However, these financial successes for manufacturers come at a cost to consumers, who face steep price hikes for RAM and storage products. This matters because the rising costs of RAM and storage could affect consumer electronics prices and accessibility, impacting both individual users and businesses reliant on these technologies.
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X Faces Criticism Over Grok’s IBSA Handling
Read Full Article: X Faces Criticism Over Grok’s IBSA HandlingX, formerly Twitter, has faced criticism for not adequately updating its chatbot, Grok, to prevent the distribution of image-based sexual abuse (IBSA), including AI-generated content. Despite adopting the IBSA Principles in 2024, which are aimed at preventing nonconsensual distribution of intimate images, X has been accused of not fulfilling its commitments. This has led to international probes and the potential for legal action under laws like the Take It Down Act, which mandates swift removal of harmful content. The situation underscores the critical responsibility of tech companies to prioritize child safety as AI technology evolves.
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Exploring RLHF & DPO: Teaching AI Ethics
Read Full Article: Exploring RLHF & DPO: Teaching AI Ethics![[P] I made a visual explainer on RLHF & DPO - the math behind "teaching AI ethics" (Korean with English subs/dub)](https://www.tweakedgeek.com/wp-content/uploads/2026/01/featured-article-9763-300x171.png)
Python remains the dominant programming language for machine learning due to its comprehensive libraries and user-friendly nature, making it ideal for a wide range of applications. For tasks requiring high performance, languages like C++ and Rust are favored, with C++ being preferred for inference and optimizations, while Rust is valued for its safety features. Other languages such as Julia, Kotlin, Java, C#, Go, Swift, Dart, R, SQL, and JavaScript serve specific roles, from statistical analysis to web integration, depending on the platform and performance needs. Understanding the strengths of each language helps in selecting the right tool for specific machine learning tasks, ensuring efficiency and effectiveness.
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AI’s Impact on Healthcare: Efficiency and Accuracy
Read Full Article: AI’s Impact on Healthcare: Efficiency and Accuracy
AI is transforming healthcare by streamlining administrative tasks, enhancing diagnostic accuracy, and personalizing patient care. Key applications include AI scribes for documenting patient visits, automating insurance approvals, and optimizing hospital logistics. AI also improves diagnostic tools, such as image analysis for early disease detection and risk assessment models that predict treatment responses. Additionally, AI supports personalized medication plans, remote health monitoring, and patient education, while also advancing medical research. Despite its potential, integrating AI into healthcare requires addressing significant challenges and limitations to ensure safe and effective use. This matters because AI has the potential to significantly improve healthcare efficiency, accuracy, and patient outcomes, but careful implementation is necessary to overcome existing challenges.
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Illinois Health Dept Exposes 700,000 Residents’ Data
Read Full Article: Illinois Health Dept Exposes 700,000 Residents’ Data
The Illinois Department of Human Services (IDHS) inadvertently exposed the personal information of over 700,000 residents due to a security lapse that lasted from April 2021 to September 2025. This lapse made an internal mapping website publicly viewable, revealing data such as addresses, case numbers, and demographic information of Medicaid and Medicare Savings Program recipients, although names were not included. Additionally, information about 32,401 individuals receiving services from the Division of Rehabilitation Services was also compromised. IDHS has not confirmed if any unauthorized parties accessed the data during the exposure period, highlighting significant concerns about data privacy and security. This matters because it underscores the importance of robust cybersecurity measures to protect sensitive personal information from unauthorized access.
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Accelerating LLM and VLM Inference with TensorRT Edge-LLM
Read Full Article: Accelerating LLM and VLM Inference with TensorRT Edge-LLM
NVIDIA TensorRT Edge-LLM is a new open-source C++ framework designed to accelerate large language model (LLM) and vision language model (VLM) inference for real-time applications in automotive and robotics. It addresses the need for low-latency, reliable, and offline operations directly on embedded platforms like NVIDIA DRIVE AGX Thor and NVIDIA Jetson Thor. The framework is optimized for minimal resource use and includes advanced features such as EAGLE-3 speculative decoding and NVFP4 quantization support, making it suitable for demanding edge use cases. Companies like Bosch, ThunderSoft, and MediaTek are already integrating TensorRT Edge-LLM into their AI solutions, showcasing its potential in enhancing on-device AI capabilities. This matters because it enables more efficient and capable AI systems in vehicles and robots, paving the way for smarter, real-time interactions without relying on cloud-based processing.
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Google’s AI Overviews in Gmail Search
Read Full Article: Google’s AI Overviews in Gmail Search
Google is enhancing Gmail with AI Overviews in search results and experimenting with an AI-organized inbox, making advanced AI features more accessible to all users. Previously exclusive to premium users, these AI capabilities aim to streamline email management by providing more efficient search results and organizing emails intelligently. The integration of AI in Gmail reflects the broader trend of AI transforming digital tools to improve productivity and user experience. This matters because it demonstrates the growing influence of AI in everyday applications, potentially reshaping how we interact with technology and manage information.
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rmcp-presence: 142 Tools for AI Machine Control
Read Full Article: rmcp-presence: 142 Tools for AI Machine Control
rmcp-presence is a consolidated tool that simplifies the integration of various machine perception and control capabilities into AI systems. By combining 142 tools into a single binary, it eliminates the need for configuring multiple servers, offering a streamlined solution for system stats, media control, window management, and more. Users can customize their setup with feature flags, allowing for a tailored experience ranging from basic sensors to comprehensive Linux control. This advancement is significant as it enhances AI's ability to interact with and manage machine environments efficiently, making complex configurations more accessible.