createLiveAI

Business

📄 MarkTechPost

Sep 21, 2025

IBM and ETH Zrich Researchers Unveil Analog Foundation Models to Tackle Noise in In-Memory AI Hardware

IBM researchers in collaboration with ETH Zrich have developed a new class of Analog Foundation Models (AFMs) that aim to integrate large language models (LLMs) with Analog In-Memory Computing (AIMC) hardware, addressing the longstanding challenge of noise-induced errors in AIMC systems. AIMC offers significant efficiency advantages by performing matrix-vector multiplications directly within dense non-volatile memory (NVM) arrays, eliminating the von Neumann bottleneck and enabling high throughput and low power consumption, which is crucial for deploying AI models on edge and embedded devices. The primary obstacle for AIMC adoption has been

A Coding Guide to End-to-End Robotics Learning with LeRobot: Training, Evaluating, and Visualizing Behavior Cloning Policies on PushT - AI news coverage from MarkTechPost in Research

Research

📄 MarkTechPost

Sep 20, 2025

A Coding Guide to End-to-End Robotics Learning with LeRobot: Training, Evaluating, and Visualizing Behavior Cloning Policies on PushT

The article highlights the use of Hugging Faces LeRobot library to facilitate end-to-end robotics learning through behavior cloning on the PushT dataset. By leveraging LeRobots unified API within Google Colab, researchers can efficiently load datasets, design compact visuomotor policiescombining convolutional neural networks with small MLP headsand train models that map visual and state observations directly to robot actions. This approach emphasizes reproducibility and rapid experimentation, enabling users to develop dataset-driven robot control policies with minimal setup. The key innovation lies in LeRobots streamlined pipeline, which simplifies the process of training, evaluating

Google AI Robotics

Building LLM Apps That Can See, Think, and Integrate: Using o3 with Multimodal Input and Structured Output - AI news coverage from Towards Data Science in Research

Research

📄 Towards Data Science

Sep 20, 2025

Building LLM Apps That Can See, Think, and Integrate: Using o3 with Multimodal Input and Structured Output

The article demonstrates how to develop a time-series anomaly detection system leveraging large language models (LLMs) through visualization and prompting techniques, emphasizing a hands-on, interactive approach. By utilizing the o3 framework with multimodal input capabilities and structured output, it showcases how LLMs can be integrated to analyze complex data patterns, enabling more intuitive and adaptable AI applications without extensive coding.

General

📄 MarkTechPost

Sep 20, 2025

Run MATLAB-Style Code Inside Python by Connecting Octave with the oct2py Library

The article highlights a method for integrating MATLAB-style coding within Python environments by leveraging the oct2py library to connect Python with GNU Octave. This approach enables seamless data exchange between NumPy and Octave, allowing users to execute .m files, visualize plots generated in Octave directly within Python, and work with MATLAB-specific data structures such as toolboxes, structs, and .mat files, all within a Google Colab setup. This development offers significant flexibility for researchers and developers by combining Pythons extensive ecosystem with the numerical and scripting capabilities of MATLAB/Octave, facilitating complex workflows without switching between

Google AI

The Hacker News

📄 The Hacker News

Sep 20, 2025

Researchers Uncover GPT-4-Powered MalTerminal Malware Creating Ransomware, Reverse Shell

Cybersecurity researchers from SentinelOne SentinelLABS have identified MalTerminal, the earliest known malware integrated with Large Language Model (LLM) capabilities, highlighting a new frontier in malicious AI applications. Presented at LABScon 2025, this development demonstrates how LLMs are being embedded into malware to enhance its sophistication, potentially enabling more advanced social engineering, code generation, or evasive tactics. The integration of LLMs into malware signifies a significant escalation in cyber threats, emphasizing the need for robust detection and mitigation strategies as malicious actors leverage AI to improve their attack vectors.

GPT

The Hacker News

📄 The Hacker News

Sep 20, 2025

ShadowLeak Zero-Click Flaw Leaks Gmail Data via OpenAI ChatGPT Deep Research Agent

Cybersecurity researchers from Radware have identified a zero-click vulnerability in OpenAI's ChatGPT Deep Research agent, dubbed ShadowLeak, which enables attackers to extract sensitive Gmail inbox data through a single malicious email without any user interaction. This critical flaw highlights the risks associated with AI-powered research tools and email integration, prompting OpenAI to respond swiftly by patching the vulnerability in early August 2025 after responsible disclosure in June.

GPT

Ethics

📄 AI News

Sep 19, 2025

TechEx Europe 2025: Practical learnings for AI leaders

TechEx Europe 2025, scheduled for September 24-25 at the RAI in Amsterdam, will serve as a pivotal platform for AI leaders to explore the transition from pilot projects to large-scale enterprise deployment, emphasizing agentic AI systems, governance, and trust. The event will feature over 250 speakers across five co-located expos, providing insights into infrastructure, operational strategies, and the broader integration of AI within digital transformation, cloud, IoT, and data ecosystems. A key focus will be on operationalising AI in enterprise settings, with sessions highlighting regulatory compliance, trust, and scaling lessons

📄 Towards Data Science

Sep 19, 2025

An Interactive Guide to 4 Fundamental Computer Vision Tasks Using Transformers

This article introduces an interactive Streamlit application that enables users to compare the performance of transformer-based modelsViT, DETR, BLIP, and ViLTacross four fundamental computer vision tasks: image classification, image segmentation, image captioning, and visual question answering. By providing a practical implementation guide, it highlights how these models leverage transformer architectures to address diverse visual understanding challenges, emphasizing their technical distinctions and capabilities. The development underscores the growing importance of transformer models in computer vision, offering a hands-on tool for researchers and practitioners to evaluate and understand their performance in real-world scenarios. This approach

Computer Vision Transformers

📄 Towards Data Science

Sep 19, 2025

How to Select the 5 Most Relevant Documents for AI Search

The article discusses advancements in enhancing the document retrieval process within Retrieval-Augmented Generation (RAG) pipelines by focusing on selecting the five most relevant documents for AI search tasks. It emphasizes techniques such as optimized ranking algorithms and relevance scoring methods to improve the accuracy and efficiency of retrieving pertinent information, thereby strengthening the overall performance of AI-driven search systems.

📄 Towards Data Science

Sep 19, 2025

TDS Newsletter: How to Make Smarter Business Decisions with AI

The article discusses how advanced AI tools, such as research agents and budget planners, are transforming business decision-making by providing more accurate insights and automation capabilities. These AI-driven solutions enable organizations to optimize resource allocation, enhance strategic planning, and improve overall operational efficiency through intelligent data analysis and automation.