​[[{“value”:” AI applications that translate textual instructions into 2D images or 3D models have expanded creative possibilities, yet the challenge persists in obtaining precise outputs. Existing tools often yield unexpected or “hallucinatory” results, lacking fidelity to input prompts. Stable Diffusion models faced issues with combining… Read More »L3GO: Unveiling Language Agents with Chain-of-3D-Thoughts for Precision in Object Generation Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Very large language models (LLMs) continue to face major computational cost barriers, which prevents their broad deployment, even with inference optimization approaches that have advanced significantly. Sequentially producing tokens throughout the autoregressive generation process is a major cause of the high inference latency. Because… Read More »Google DeepMind Introduces Tandem Transformers for Inference Efficient Large Language Models LLMs Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In machine learning, the effectiveness of tree ensembles, such as random forests, has long been acknowledged. These ensembles, which pool the predictive power of multiple decision trees, stand out for their remarkable accuracy across various applications. This work, from researchers at the University of… Read More »Why Random Forests Dominate: Insights from the University of Cambridge’s Groundbreaking Machine Learning Research! Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The growth of Artificial Intelligence (AI), with Transformers leading the charge, ranges from applications in conversational AI to image and video generation. Yet, traditional symbolic planners have held the upper hand in complex decision-making and planning tasks due to their structured, rule-based approach.  The… Read More »Meta AI Introduces Searchformer for Improving Planning Efficiency: A Transformer Model for Complex Decision-Making Tasks Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The advent of transformer architectures has marked a significant milestone, particularly in their application to in-context learning. These models can make predictions based solely on the information presented within the input sequence without explicit parameter updates. This ability to adapt and learn from the… Read More »Google and Duke University’s New Machine Learning Breakthrough Unveils Advanced Optimization by Linear Transformers Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The emergence of Large Language Models (LLMs) has notably enhanced the domain of computational linguistics, particularly in multi-agent systems. Despite the significant advancements, developing multi-agent applications remains a complex endeavor. This complexity arises from the challenge of effectively coordinating multiple agents’ actions and navigating… Read More »Alibaba AI Group Propose AgentScope: A Developer-Centric Multi-Agent Platform with Message Exchange as its Core Communication Mechanism Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Recent advancements in (self) supervised learning models have been driven by empirical scaling laws, where a model’s performance scales with its size. However, such scaling laws have been challenging to establish in reinforcement learning (RL). Unlike supervised learning, increasing the parameter count of an… Read More »Google DeepMind’s Latest Machine Learning Breakthrough Revolutionizes Reinforcement Learning with Mixture-of-Experts for Superior Model Scalability and Performance Janhavi Lande Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have significantly evolved in recent times, especially in the areas of text understanding and generation. However, there have been certain difficulties in optimizing LLMs for more effective human instruction delivery. While LLMs have shown progress in tasks involving token prediction… Read More »Microsoft AI Research Introduces Generalized Instruction Tuning (called GLAN): A General and Scalable Artificial Intelligence Method for Instruction Tuning of Large Language Models (LLMs) Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the evolving landscape of psycholinguistics, language models (LMs) have carved out a pivotal role, serving as both the subject and tool of study. These models, leveraging vast datasets, attempt to mimic human language processing capabilities, offering invaluable insights into the cognitive mechanisms that… Read More »From Black Box to Open Book: How Stanford’s CausalGym is Decoding the Mysteries of Artificial Intelligence AI Language Processing! Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The ability to predict outcomes from a myriad of parameters has traditionally been anchored in specific, narrowly focused regression methods. While effective within its domain, this specialized approach often needs to be revised when confronted with the complexity and diversity inherent in real-world experiments.… Read More »Meet OmniPred: A Machine Learning Framework to Transform Experimental Design with Universal Regression Models Adnan Hassan Artificial Intelligence Category – MarkTechPost