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IBM Security’s research reveals the threat of AI voice clones being used to infiltrate live conversations undetected. With evolving voice cloning technology, scammers can mimic individuals’ voices for fraudulent calls. The researchers demonstrated a sophisticated attack…

“Puncc, a Python library, integrates conformal prediction algorithms to address the crucial need for uncertainty quantification in machine learning. It transforms point predictions into interval predictions, ensuring rigorous uncertainty estimations and coverage probabilities. With comprehensive documentation…

This study addresses the problem of text-to-image generative models’ inability to consistently generate images. They propose a novel approach to generating consistent portrayals of characters in different circumstances based on a text prompt. The researchers use…

Graph Self-supervised Pre-training (GSP) Techniques In graph analysis, labeled data poses a challenge for traditional supervised learning methods. Graph Self-supervised Pre-training (GSP) techniques have emerged to overcome this limitation by extracting meaningful representations from graph data…

Protecting User Data with Privacy-First Solutions Challenge: Organizations need to analyze data for advanced analytics and machine learning without compromising user privacy. Current solutions often fail to balance security and functionality, hindering innovation and collaboration. Need…

The text describes the concept and process of building stacked ensembles in machine learning using H2O.ai and Optuna. The author outlines the steps involved in training a stacked ensemble, including the training of base models such…

Artificial intelligence is revolutionizing video generation, with Google AI introducing VideoPoet. This large language model integrates various video generation tasks, such as text-to-video, image-to-video, and video stylization, using tokenizers for processing. Its unique approach offers the…

The Self-Contrast approach from the Zhejiang University and OPPO Research Institute addresses the challenge of enhancing Large Language Models’ reflective and self-corrective abilities. It introduces diverse solving perspectives, a detailed checklist generation, and demonstrates significant improvements…

Building a Semantic Search Engine Building a Semantic Search Engine: A Practical Guide Understanding Semantic Search Semantic search enhances traditional keyword matching by grasping the contextual meaning of search queries. Unlike conventional systems that rely solely…

This text provides a hands-on guide to building a language model for masked language modeling (MLM) tasks using Python and the Transformers library. It discusses the importance of large language models (LLMs) in the machine learning…

Meet Lytix: An AI Platform for Your LLM Stack Product insights & monitoring, testing, end-to-end analytics, and errors are four of the most difficult LLMs to monitor and test. Teams mostly waste weeks of dev time…

Challenges with Language Models Large Language Models (LLMs) perform well in many tasks, but they struggle with multi-step reasoning, especially in complex scenarios like: Mathematical problem-solving Controlling embodied agents Web navigation Current methods, such as Proximal…

In data science and AI, embedding entities into vector spaces enables numerical representation, but a study by Netflix Inc. and Cornell University challenges the reliability of cosine similarity, revealing its potential for arbitrary and misleading results.…

Multimodal Attributed Graphs (MMAGs) Overview: MMAGs are powerful tools for generating images by representing relationships between different entities in a graph format. Each node in these graphs contains both image and text information, allowing for more…

A new study proposes a three-step system to evaluate artificial intelligence’s ability to reason like a human, acknowledging the limitations of the Turing test due to AI’s capacity to imitate human responses.

Advancements in Large Language Models (LLMs) Recent developments in large language models (LLMs) such as DeepSeek-R1, Kimi-K1.5, and OpenAI-o1 have demonstrated remarkable reasoning capabilities. However, the lack of transparency regarding training code and datasets, particularly with…

Researchers from Peking University, Peng Cheng Laboratory, Peking University Shenzhen Graduate School, and Sun Yat-sen University have introduced Video-LLaVA, a Large Vision-Language Model (LVLM) approach that unifies visual representation into the language feature space. Video-LLaVA surpasses…

Intersection of AI and arts, particularly music, is a significant study due to its impact on human creativity, with researchers focusing on creating music through language models. Skywork AI and Hong Kong University developed ChatMusician, outperforming…

AWS’s suite of low-code and no-code ML tools, such as Amazon SageMaker Canvas, enables rapid, cost-effective machine learning model development without requiring coding expertise. Deloitte uses these tools to expedite project delivery and take on more…