Sam Altman returns as CEO, OpenAI has a new initial board
Mira Murati as CTO, Greg Brockman returns as President. Read messages from CEO Sam Altman and board chair Bret Taylor.
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Manifold learning, rooted in the manifold assumption, reveals low-dimensional structures within input data, positing that the data exists on a low-dimensional manifold within a high-dimensional ambient space. Deep Manifold Learning (DML), facilitated by deep neural networks, extends to graph data applications. For instance, MGAE leverages auto-encoders in the graph domain to embed node features and…
This AI Paper from Apple Unveils AlignInstruct: Pioneering Solutions for Unseen Languages and Low-Resource Challenges in Machine Translation
ByWeb Dev
Machine translation, an integral branch of Natural Language Processing, is continually evolving to bridge language gaps across the globe. One persistent challenge is the translation of low-resource languages, which often need more substantial data for training robust models. Traditional translation models, primarily based on large language models (LLMs), perform well with languages abundant in data…
UC Berkeley and NYU AI Research Explores the Gap Between the Visual Embedding Space of Clip and Vision-only Self-Supervised Learning
MLLMs, or multimodal large language models, have been advancing lately. By incorporating images into large language models (LLMs) and harnessing the capabilities of LLMs, MLLMs demonstrate exceptional skill in tasks including visual question answering, instruction following, and image understanding. Studies have seen a significant flaw in these models despite their improvements; they still have some…
Google AI Research Proposes SpatialVLM: A Data Synthesis and Pre-Training Mechanism to Enhance Vision-Language Model VLM Spatial Reasoning Capabilities
Vision-language models (VLMs) are increasingly prevalent, offering substantial advancements in AI-driven tasks. However, one of the most significant limitations of these advanced models, including prominent ones like GPT-4V, is their constrained spatial reasoning capabilities. Spatial reasoning involves understanding objects’ positions in three-dimensional space and their spatial relationships with one another. This limitation is particularly pronounced…
Researchers from the University of Wisconsin–Madison Unveil ‘SAMPLE’: An Artificial Intelligence Platform for Fully Autonomous Protein Engineering
Protein engineering, a field with wide-ranging applications in chemistry, energy, and medicine, has multiple intricate challenges. Existing methods of engineering new proteins with improved or novel functions are slow, labor-intensive, and inefficient. This inefficiency in protein engineering hampers the ability to exploit its potential in various scientific and medical fields. Protein engineering involves a discovery-driven…
‘Weak-to-Strong JailBreaking Attack’: An Efficient AI Method to Attack Aligned LLMs to Produce Harmful Text
Well-known Large Language Models (LLMs) like ChatGPT and Llama have recently advanced and shown incredible performance in a number of Artificial Intelligence (AI) applications. Though these models have demonstrated capabilities in tasks like content generation, question answering, text summarization, etc, there are concerns regarding possible abuse, such as disseminating false information and assistance for illegal…
