Skip to content

This AI Paper Introduces a Unified Perspective on the Relationship between Latent Space and Generative Models Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

  • by

​[[{“value”:” In recent years, there have been drastic changes in the field of image generation, mainly due to the development of latent-based generative models, such as Latent Diffusion Models (LDMs) and Mask Image Models (MIMs). Reconstructive autoencoders, like VQGAN and VAE, can reduce images into… Read More »This AI Paper Introduces a Unified Perspective on the Relationship between Latent Space and Generative Models Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

15 Fundamental Mathematics Theories Needed to Understand AI Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

  • by

​[[{“value”:” Mathematics is the cornerstone of artificial intelligence. These theories provide the framework for developing intelligent systems capable of learning, reasoning, and making decisions. From the statistical foundations of machine learning to the complex algorithms powering neural networks, mathematics plays a pivotal role in shaping… Read More »15 Fundamental Mathematics Theories Needed to Understand AI Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

Multi-Scale Neural Audio Codec (SNAC): An Wxtension of Residual Vector Quantization that Uses Quantizers Operating at Multiple Temporal Resolutions Mohammad Asjad Artificial Intelligence Category – MarkTechPost

  • by

​[[{“value”:” Neural audio compression has emerged as a critical challenge in digital signal processing, particularly in achieving efficient audio representation while preserving quality. Traditional audio codecs, despite their widespread use, face limitations in achieving lower bitrates without compromising audio fidelity. While recent neural compression methods… Read More »Multi-Scale Neural Audio Codec (SNAC): An Wxtension of Residual Vector Quantization that Uses Quantizers Operating at Multiple Temporal Resolutions Mohammad Asjad Artificial Intelligence Category – MarkTechPost

Anthropic AI Introduces a New Claude 3.5 Sonnet with Computer Use Feature, and Claude 3.5 Haiku Asif Razzaq Artificial Intelligence Category – MarkTechPost

  • by

​[[{“value”:” The advancement of artificial intelligence often reveals new ways for machines to augment human capabilities. Anthropic AI’s latest innovation introduces features designed to overcome critical limitations in AI-human interactions. Specifically, Anthropic AI is tackling the challenges of improving AI’s understanding of nuanced prompts, enabling… Read More »Anthropic AI Introduces a New Claude 3.5 Sonnet with Computer Use Feature, and Claude 3.5 Haiku Asif Razzaq Artificial Intelligence Category – MarkTechPost

Cohere Releases Multimodal Embed 3: A State-of-the-Art Multimodal AI Search Model Unlocking Real Business Value for Image Data Asif Razzaq Artificial Intelligence Category – MarkTechPost

  • by

​[[{“value”:” In an increasingly interconnected world, understanding and making sense of different types of information simultaneously is crucial for the next wave of AI development. Traditional AI models often struggle with integrating information across multiple data modalities—primarily text and images—to create a unified representation that… Read More »Cohere Releases Multimodal Embed 3: A State-of-the-Art Multimodal AI Search Model Unlocking Real Business Value for Image Data Asif Razzaq Artificial Intelligence Category – MarkTechPost

Generative Reward Models (GenRM): A Hybrid Approach to Reinforcement Learning from Human and AI Feedback, Solving Task Generalization and Feedback Collection Challenges Sana Hassan Artificial Intelligence Category – MarkTechPost

  • by

​[[{“value”:” Reinforcement learning (RL) has been pivotal in advancing artificial intelligence by enabling models to learn from their interactions with the environment. Traditionally, reinforcement learning relies on rewards for positive actions and penalties for negative ones. A recent approach, Reinforcement Learning from Human Feedback (RLHF),… Read More »Generative Reward Models (GenRM): A Hybrid Approach to Reinforcement Learning from Human and AI Feedback, Solving Task Generalization and Feedback Collection Challenges Sana Hassan Artificial Intelligence Category – MarkTechPost

Towards Data-Centric RLHF: Simple Metrics for Preference Dataset Comparison Apple Machine Learning Research

  • by

​The goal of aligning language models to human preferences requires data that reveal these preferences. Ideally, time and money can be spent carefully collecting and tailoring bespoke preference data to each downstream application. However, in practice, a select few publicly available preference datasets are often… Read More »Towards Data-Centric RLHF: Simple Metrics for Preference Dataset Comparison Apple Machine Learning Research

MUSCLE: A Model Update Strategy for Compatible LLM Evolution Apple Machine Learning Research

  • by

​Large Language Models (LLMs) are regularly updated to enhance performance, typically through changes in data or architecture. Within the update process, developers often prioritize improving overall performance metrics, paying less attention to maintaining compatibility with earlier model versions. Instance-level degradation (instance regression) of performance from… Read More »MUSCLE: A Model Update Strategy for Compatible LLM Evolution Apple Machine Learning Research

CtrlSynth: Controllable Image-Text Synthesis for Data-Efficient Multimodal Learning Apple Machine Learning Research

  • by

​Pretraining robust vision or multimodal foundation models (e.g., CLIP) relies on large-scale datasets that may be noisy, potentially misaligned, and have long-tail distributions. Previous works have shown promising results in augmenting datasets by generating synthetic samples. However, they only support domain-specific ad hoc use cases… Read More »CtrlSynth: Controllable Image-Text Synthesis for Data-Efficient Multimodal Learning Apple Machine Learning Research