​[[{“value”:” With the increasing growth of artificial intelligence—introduction of large language models (LLMs) and generative AI—there has been a growing demand for more efficient graphics processing units (GPUs). GPUs are specialized hardware extensively used for high computing tasks and capable of executing computations in parallel.… Read More »Mirage: A Multi-Level Tensor Algebra Super-Optimizer that Automates GPU Kernel Generation for PyTorch Applications Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Liquid AI has released its first series of Liquid Foundation Models (LFMs), ushering in a new generation of generative AI models. These models are positioned as a new benchmark for performance and efficiency at multiple scales, namely the 1B, 3B, and 40B parameter configurations.… Read More »Liquid AI Introduces Liquid Foundation Models (LFMs): A 1B, 3B, and 40B Series of Generative AI Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post is co-written with Dean Steel and Simon Gatie from Aviva. With a presence in 16 countries and serving over 33 million customers, Aviva is a leading insurance company headquartered in London, UK. With a history dating back to 1696, Aviva is one… Read More »How Aviva built a scalable, secure, and reliable MLOps platform using Amazon SageMaker Dean Steel AWS Machine Learning Blog

​[[{“value”:” This post is co-written with Ike Bennion from Visier. Visier’s mission is rooted in the belief that people are the most valuable asset of every organization and that optimizing their potential requires a nuanced understanding of workforce dynamics. Paycor is an example of the… Read More »Visier’s data science team boosts their model output 10 times by migrating to Amazon SageMaker Kinman Lam AWS Machine Learning Blog

​[[{“value”:” Generative AI models can produce information on a wide range of topics, but their application brings new challenges. These include maintaining relevance, avoiding toxic content, protecting sensitive information like personally identifiable information (PII), and mitigating hallucinations. Although foundation models (FMs) on Amazon Bedrock offer… Read More »Implement model-independent safety measures with Amazon Bedrock Guardrails Michael Cho AWS Machine Learning Blog

​[[{“value”:” Microsoft unveiled VoiceRAG, a voice-based retrieval-augmented generation (RAG) system that utilizes the new Azure OpenAI gpt-4o-realtime-preview model to combine audio input and output with powerful data retrieval capabilities. This innovative system represents a significant leap in natural language processing by enabling seamless interaction with… Read More »Microsoft Released VoiceRAG: An Advanced Voice Interface Using GPT-4 and Azure AI Search for Real-Time Conversational Applications Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Traffic forecasting is a fundamental aspect of smart city management, essential for improving transportation planning and resource allocation. With the rapid advancement of deep learning, complex spatiotemporal patterns in traffic data can now be effectively modeled. However, real-world applications present unique challenges due to… Read More »STGformer: A Spatiotemporal Graph Transformer Achieving Unmatched Computational Efficiency and Performance in Large-Scale Traffic Forecasting Applications Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Transformer-based Models in Segmentation tasks have initiated a new transformation in the Computer Vision realm. Meta’s Segment Anything Model has proven to be a benchmark due to its robust and exquisite performance. SAM has proven highly successful as supervised segmentation continues to gain popularity… Read More »Researchers from UC Berkeley Present UnSAM in Computer Vision: A New Paradigm for Segmentation with Minimal Data, Achieving State-of-the-Art Results Without Human Annotation Adeeba Alam Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have gained widespread popularity, but their token generation process is computationally expensive due to the self-attention mechanism. This mechanism requires attending to all previous tokens, leading to substantial computational costs. Although caching key-value (KV) states across layers during autoregressive decoding… Read More »Block Transformer: Enhancing Inference Efficiency in Large Language Models Through Hierarchical Global-to-Local Modeling Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have gained immense capabilities due to their training on vast internet-based datasets. However, this broad exposure has inadvertently incorporated harmful content, enabling LLMs to generate toxic, illicit, biased, and privacy-infringing material. As these models become more advanced, the embedded hazardous… Read More »Evaluating the Vulnerabilities of Unlearning Techniques in Large Language Models: A Comprehensive White-Box Analysis Mohammad Asjad Artificial Intelligence Category – MarkTechPost