​[[{“value”:” In the world of advanced AI, a common challenge developers face is the security and privacy of data, especially when using external services. Many businesses and individuals have strict rules about where their sensitive information can be stored and processed. The existing solutions often… Read More »Meet Dify.AI: An LLM Application Development Platform that Integrates BaaS and LLMOps Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) like GPT-4 require substantial computational power and memory, posing challenges for their efficient deployment. While sparsification methods have been developed to mitigate these resource demands, they often introduce new complexities. For example, these techniques may require extra data structures to… Read More »Researchers from ETH Zurich and Microsoft Introduce SliceGPT for Efficient Compression of Large Language Models through Sparsification Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A groundbreaking development is emerging in artificial intelligence and machine learning: intelligent agents that can seamlessly adapt and evolve by integrating past experiences into new and diverse tasks. These agents, central to advancing AI technology, are being engineered to perform tasks efficiently and learn… Read More »This AI Paper Introduces Investigate-Consolidate-Exploit (ICE): A Novel AI Strategy to Facilitate the Agent’s Inter-Task Self-Evolution Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” With its structured format, Tabular data dominates the data analysis landscape across various sectors such as industry, healthcare, and academia. Despite the surge in the use of images and texts for machine learning, tabular data’s inherent simplicity and interpretability have kept it at the… Read More »Researchers from the University of Kentucky Propose MambaTab: A New Machine Learning Method based on Mamba for Handling Tabular Data Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” With the rise of Large Language Models (LLMs) in recent years, generative AI has made significant strides in the field of language processing, showcasing impressive abilities in a wide array of tasks. Given their potential in solving complex tasks, researchers have made quite a… Read More »Meet DrugAssist: An Interactive Molecule Optimization Model that can Interact with Humans in Real-Time Using Natural Language Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:”Posted by Rajat Sen and Yichen Zhou, Google Research Time-series forecasting is ubiquitous in various domains, such as retail, finance, manufacturing, healthcare and natural sciences. In retail use cases, for example, it has been observed that improving demand forecasting accuracy can meaningfully reduce inventory costs… Read More »A decoder-only foundation model for time-series forecasting Google AI Google AI Blog

​[[{“value”:”Posted by Rishabh Tiwari, Pre-doctoral Researcher, and Pradeep Shenoy, Research Scientist, Google Research Machine learning models in the real world are often trained on limited data that may contain unintended statistical biases. For example, in the CELEBA celebrity image dataset, a disproportionate number of female… Read More »Intervening on early readouts for mitigating spurious features and simplicity bias Google AI Google AI Blog

​[[{“value”:” One of the most useful application patterns for generative AI workloads is Retrieval Augmented Generation (RAG). In the RAG pattern, we find pieces of reference content related to an input prompt by performing similarity searches on embeddings. Embeddings capture the information content in bodies… Read More »Monitor embedding drift for LLMs deployed from Amazon SageMaker JumpStart Abdullahi Olaoye AWS Machine Learning Blog

​[[{“value”:” In computational linguistics and artificial intelligence, researchers continually strive to optimize the performance of large language models (LLMs). These models, renowned for their capacity to process a vast array of language-related tasks, face significant challenges due to their expansive size. For instance, models like… Read More »Seeking Faster, More Efficient AI? Meet FP6-LLM: the Breakthrough in GPU-Based Quantization for Large Language Models Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” For LLMs, auto-regressive decoding is now considered the gold standard. Because LLMs generate output tokens individually, the procedure is time-consuming and expensive. Methods based on speculative sampling provide an answer to this problem. In the first, called the “draft” phase, LLMs are hypothesized at… Read More »Seeking Speed without Loss in Large Language Models? Meet EAGLE: A Machine Learning Framework Setting New Standards for Lossless Acceleration Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost