Learning Triton One Kernel At a Time: Vector AdditionTowards Data Scienceon September 27, 2025 at 4:00 pm The basics of GPU programming, optimisation, and your first Triton kernel
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The basics of GPU programming, optimisation, and your first Triton kernel
The post Learning Triton One Kernel At a Time: Vector Addition appeared first on Towards Data Science. Read More
How to Build an Intelligent AI Desktop Automation Agent with Natural Language Commands and Interactive Simulation?MarkTechPoston September 27, 2025 at 6:40 am In this tutorial, we walk through the process of building an advanced AI desktop automation agent that runs seamlessly in Google Colab. We design it to interpret natural language commands, simulate desktop tasks such as file operations, browser actions, and workflows, and provide interactive feedback through a virtual environment. By combining NLP, task execution, and
The post How to Build an Intelligent AI Desktop Automation Agent with Natural Language Commands and Interactive Simulation? appeared first on MarkTechPost.
In this tutorial, we walk through the process of building an advanced AI desktop automation agent that runs seamlessly in Google Colab. We design it to interpret natural language commands, simulate desktop tasks such as file operations, browser actions, and workflows, and provide interactive feedback through a virtual environment. By combining NLP, task execution, and
The post How to Build an Intelligent AI Desktop Automation Agent with Natural Language Commands and Interactive Simulation? appeared first on MarkTechPost. Read More
CAMIA privacy attack reveals what AI models memoriseAI Newson September 26, 2025 at 5:17 pm Researchers have developed a new attack that reveals privacy vulnerabilities by determining whether your data was used to train AI models. The method, named CAMIA (Context-Aware Membership Inference Attack), was developed by researchers from Brave and the National University of Singapore and is far more effective than previous attempts at probing the ‘memory’ of AI
The post CAMIA privacy attack reveals what AI models memorise appeared first on AI News.
Researchers have developed a new attack that reveals privacy vulnerabilities by determining whether your data was used to train AI models. The method, named CAMIA (Context-Aware Membership Inference Attack), was developed by researchers from Brave and the National University of Singapore and is far more effective than previous attempts at probing the ‘memory’ of AI
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Building health care agents using Amazon Bedrock AgentCoreArtificial Intelligenceon September 26, 2025 at 4:03 pm In this solution, we demonstrate how the user (a parent) can interact with a Strands or LangGraph agent in conversational style and get information about the immunization history and schedule of their child, inquire about the available slots, and book appointments. With some changes, AI agents can be made event-driven so that they can automatically send reminders, book appointments, and so on.
In this solution, we demonstrate how the user (a parent) can interact with a Strands or LangGraph agent in conversational style and get information about the immunization history and schedule of their child, inquire about the available slots, and book appointments. With some changes, AI agents can be made event-driven so that they can automatically send reminders, book appointments, and so on. Read More
Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in MindTowards Data Scienceon September 26, 2025 at 2:00 pm Why the original MissForest algorithm cannot be directly applied for predictive modeling, and how MissForestPredict solves this problem
The post Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in Mind appeared first on Towards Data Science.
Why the original MissForest algorithm cannot be directly applied for predictive modeling, and how MissForestPredict solves this problem
The post Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in Mind appeared first on Towards Data Science. Read More
US investigators are using AI to detect child abuse images made by AIMIT Technology Reviewon September 26, 2025 at 7:03 pm Generative AI has enabled the production of child sexual abuse images to skyrocket. Now the leading investigator of child exploitation in the US is experimenting with using AI to distinguish AI-generated images from material depicting real victims, according to a new government filing. The Department of Homeland Security’s Cyber Crimes Center, which investigates child exploitation…
Generative AI has enabled the production of child sexual abuse images to skyrocket. Now the leading investigator of child exploitation in the US is experimenting with using AI to distinguish AI-generated images from material depicting real victims, according to a new government filing. The Department of Homeland Security’s Cyber Crimes Center, which investigates child exploitation… Read More
Hugging Face Releases Smol2Operator: A Fully Open-Source Pipeline to Train a 2.2B VLM into an Agentic GUI CoderMarkTechPoston September 26, 2025 at 8:51 pm Hugging Face (HF) has released Smol2Operator, a reproducible, end-to-end recipe that turns a small vision-language model (VLM) with no prior UI grounding into a GUI-operating, tool-using agent. The release covers data transformation utilities, training scripts, transformed datasets, and the resulting 2.2B-parameter model checkpoint—positioned as a complete blueprint for building GUI agents from scratch rather than
The post Hugging Face Releases Smol2Operator: A Fully Open-Source Pipeline to Train a 2.2B VLM into an Agentic GUI Coder appeared first on MarkTechPost.
Hugging Face (HF) has released Smol2Operator, a reproducible, end-to-end recipe that turns a small vision-language model (VLM) with no prior UI grounding into a GUI-operating, tool-using agent. The release covers data transformation utilities, training scripts, transformed datasets, and the resulting 2.2B-parameter model checkpoint—positioned as a complete blueprint for building GUI agents from scratch rather than
The post Hugging Face Releases Smol2Operator: A Fully Open-Source Pipeline to Train a 2.2B VLM into an Agentic GUI Coder appeared first on MarkTechPost. Read More
AI News September 26 2025: Robots, AI Videos & $30M Funding Executive Summary AI News Roundup: Robots Get Smarter, Meta Pushes AI Videos, and Recruiting Goes LLM The AI world took a breather yesterday. No mega-rounds. No AGI announcements. Just three developments worth your attention. Google’s Robots Can Now Think Ahead (And Google Things) Yesterday […]
CLIPin: A Non-contrastive Plug-in to CLIP for Multimodal Semantic Alignmentcs.AI updates on arXiv.orgon September 26, 2025 at 4:00 am arXiv:2508.06434v2 Announce Type: replace-cross
Abstract: Large-scale natural image-text datasets, especially those automatically collected from the web, often suffer from loose semantic alignment due to weak supervision, while medical datasets tend to have high cross-modal correlation but low content diversity. These properties pose a common challenge for contrastive language-image pretraining (CLIP): they hinder the model’s ability to learn robust and generalizable representations. In this work, we propose CLIPin, a unified non-contrastive plug-in that can be seamlessly integrated into CLIP-style architectures to improve multimodal semantic alignment, providing stronger supervision and enhancing alignment robustness. Furthermore, two shared pre-projectors are designed for image and text modalities respectively to facilitate the integration of contrastive and non-contrastive learning in a parameter-compromise manner. Extensive experiments on diverse downstream tasks demonstrate the effectiveness and generality of CLIPin as a plug-and-play component compatible with various contrastive frameworks. Code is available at https://github.com/T6Yang/CLIPin.
arXiv:2508.06434v2 Announce Type: replace-cross
Abstract: Large-scale natural image-text datasets, especially those automatically collected from the web, often suffer from loose semantic alignment due to weak supervision, while medical datasets tend to have high cross-modal correlation but low content diversity. These properties pose a common challenge for contrastive language-image pretraining (CLIP): they hinder the model’s ability to learn robust and generalizable representations. In this work, we propose CLIPin, a unified non-contrastive plug-in that can be seamlessly integrated into CLIP-style architectures to improve multimodal semantic alignment, providing stronger supervision and enhancing alignment robustness. Furthermore, two shared pre-projectors are designed for image and text modalities respectively to facilitate the integration of contrastive and non-contrastive learning in a parameter-compromise manner. Extensive experiments on diverse downstream tasks demonstrate the effectiveness and generality of CLIPin as a plug-and-play component compatible with various contrastive frameworks. Code is available at https://github.com/T6Yang/CLIPin. Read More
Sakana AI Released ShinkaEvolve: An Open-Source Framework that Evolves Programs for Scientific Discovery with Unprecedented Sample-EfficiencyMarkTechPoston September 26, 2025 at 9:15 am Sakana AI has released ShinkaEvolve, an open-sourced framework that uses large language models (LLMs) as mutation operators in an evolutionary loop to evolve programs for scientific and engineering problems—while drastically cutting the number of evaluations needed to reach strong solutions. On the canonical circle-packing benchmark (n=26 in a unit square), ShinkaEvolve reports a new SOTA
The post Sakana AI Released ShinkaEvolve: An Open-Source Framework that Evolves Programs for Scientific Discovery with Unprecedented Sample-Efficiency appeared first on MarkTechPost.
Sakana AI has released ShinkaEvolve, an open-sourced framework that uses large language models (LLMs) as mutation operators in an evolutionary loop to evolve programs for scientific and engineering problems—while drastically cutting the number of evaluations needed to reach strong solutions. On the canonical circle-packing benchmark (n=26 in a unit square), ShinkaEvolve reports a new SOTA
The post Sakana AI Released ShinkaEvolve: An Open-Source Framework that Evolves Programs for Scientific Discovery with Unprecedented Sample-Efficiency appeared first on MarkTechPost. Read More