​[[{“value”:” A critical aspect of AI research involves fine-tuning large language models (LLMs) to align their outputs with human preferences. This fine-tuning ensures that AI systems generate useful, relevant, and aligned responses with user expectations. The current paradigm in AI emphasizes learning from human preference… Read More »HyPO: A Hybrid Reinforcement Learning Algorithm that Uses Offline Data for Contrastive-based Preference Optimization and Online Unlabeled Data for KL Regularization Sana Hassan Artificial Intelligence Category – MarkTechPost

​ On April 2, the World Health Organization launched a chatbot named SARAH to raise health awareness about things like how to eat well, quit smoking, and more. But like any other chatbot, SARAH started giving incorrect answers. Leading to a lot of internet trolls and… Read More »Why does AI hallucinate? CuriosityDeck Becoming Human: Artificial Intelligence Magazine – Medium

​[[{“value”:” In the digital age, personalized experiences have become essential. Whether in customer support, healthcare diagnostics, or content recommendations, people expect interactions with technology to be tailored to their specific needs and preferences. However, creating a truly personalized experience can be challenging. Traditional AI systems… Read More »Meet Mem0: The Memory Layer for Personalized AI that Provides an Intelligent, Adaptive Memory Layer for Large Language Models (LLMs) Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The Sparse Autoencoder (SAE) is a type of neural network designed to efficiently learn sparse representations of data. The Sparse Autoencoder (SAE) neural network efficiently learns sparse data representations. Sparse Autoencoders (SAEs) enforce sparsity to capture only the most important data characteristics for fast… Read More »Google Deepmind Researchers Introduce Jumprelu Sparse Autoencoders: Achieving State-of-the-Art Reconstruction Fidelity Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Recent advances in immune sequencing and experimental methods generate extensive T cell receptor (TCR) repertoire data, enabling models to predict TCR binding specificity. T cells play a role in the adaptive immune system, orchestrating targeted immune responses through TCRs that recognize non-self antigens from… Read More »Advances and Challenges in Predicting TCR Specificity: From Clustering to Protein Language Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The LMSys Chatbot Arena has recently released scores for GPT-4o Mini, sparking a topic of discussion among AI researchers. GPT-4o Mini outperformed Claude 3.5 Sonnet, which is frequently praised as the most intelligent Large Language Model (LLM) on the market, according to the results.… Read More »Why GPT-4o Mini Outperforms Claude 3.5 Sonnet on LMSys? Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” TensorOpera has announced the launch of its groundbreaking small language model, Fox-1, through an official press release. This innovative model represents a significant step forward in small language models (SLMs), setting new benchmarks for scalability and performance in generative AI, particularly for cloud and… Read More »TensorOpera Unveils Fox Foundation Model: A Unique Step in Small Language Models Enhancing Scalability and Efficiency for Cloud and Edge Computing Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the past decade, the data-driven method utilizing deep neural networks has driven artificial intelligence success in various challenging applications across different fields. These advancements address multiple issues; however, existing methodologies face the challenge in data science applications, especially in fields such as biology,… Read More »LAMBDA: A New Open-Source, Code-Free Multi-Agent Data Analysis System to Bridge the Gap Between Domain Experts and Advanced AI Models Sajjad Ansari Artificial Intelligence Category – MarkTechPost