*=Equal Contributors Preserving training dynamics across batch sizes is an important tool for practical machine learning as it enables the trade-off between batch size and wall-clock time. This trade-off is typically enabled by a scaling rule; for example, in stochastic gradient descent, one should scale… Read More »How to Scale Your EMA Apple Machine Learning Research
Behavioral testing in NLP allows fine-grained evaluation of systems by examining their linguistic capabilities through the analysis of input-output behavior. Unfortunately, existing work on behavioral testing in Machine Translation (MT) is currently restricted to largely handcrafted tests covering a limited range of capabilities and languages.… Read More »Automating Behavioral Testing in Machine Translation Apple Machine Learning Research
Large Language Models (LLMs) with billions of parameters have drastically transformed AI applications. However, their demanding computation during inference has raised significant challenges for deployment on resource-constrained devices. Despite recent trends favoring alternative activation functions such as GELU or SiLU, known for increased computation, this… Read More »ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models Apple Machine Learning Research
This paper was accepted at the Machine Learning for Audio Workshop at NeurIPS 2023. Over the past several years, the synchronization between audio and visual signals has been leveraged to learn richer audio-visual representations. Aided by the large availability of unlabeled videos, many unsupervised training… Read More »Diffusion Models as Masked Audio-Video Learners Apple Machine Learning Research
Spotting user-defined flexible keyword in real-time is challenging because the keyword is represented in text. In this work, we propose a novel architecture to efficiently detect the flexible keywords based on the following ideas. We contsruct the representative acousting embeding of a keyword using graphene-to-phone… Read More »Flexible Keyword Spotting based on Homogeneous Audio-Text Embedding Apple Machine Learning Research
A team of researchers from Shanghai Artificial Intelligence Laboratory, GigaAI, East China Normal University, The Chinese University of Hong Kong, WeRide.ai evaluates the applicability of GPT-4V(ision), a Visual Language Model, in autonomous driving scenarios. GPT-4V demonstrates superior performance in scene understanding and causal reasoning,… Read More »This AI Research from China Provides an Exhaustive Evaluation of the Latest SOTA Visual Language Model GPT-4V(ision) and Its Application in Autonomous Driving Scenarios Adnan Hassan Artificial Intelligence Category – MarkTechPost
Large Language Models (LLMs) have shown remarkable capabilities in tasks like language understanding and reasoning, marking a paradigm shift in how we interact with AI systems. To augment the proficiency of LLMs, researchers generally employ the chain of thought prompting technique, which involves intermediate… Read More »Can Language Models Reason Beyond Words? Exploring Implicit Reasoning in Multi-Layer Hidden States for Complex Tasks Arham Islam Artificial Intelligence Category – MarkTechPost
AutoML allows you to derive rapid, general insights from your data right at the beginning of a machine learning (ML) project lifecycle. Understanding up front which preprocessing techniques and algorithm types provide best results reduces the time to develop, train, and deploy the right… Read More »Implement a custom AutoML job using pre-selected algorithms in Amazon SageMaker Automatic Model Tuning Konrad Semsch AWS Machine Learning Blog
Llama 2 stands at the forefront of AI innovation, embodying an advanced auto-regressive language model developed on a sophisticated transformer foundation. It’s tailored to address a multitude of applications in both the commercial and research domains with English as the primary linguistic concentration. Its… Read More »Best prompting practices for using the Llama 2 Chat LLM through Amazon SageMaker JumpStart Jin Tan Ruan AWS Machine Learning Blog
An established financial services firm with over 140 years in business, Principal is a global investment management leader and serves more than 62 million customers around the world. Principal is conducting enterprise-scale near-real-time analytics to deliver a seamless and hyper-personalized omnichannel customer experience on… Read More »Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights Chris Lott AWS Machine Learning Blog