When do you want to see my Articles?

Over the past few months, I have published a lot of high quality content on AI, LLMs, RAG, Knowledge Bases and on the experiments we are running. Even though this content is AI focused, there is an inherently Philosophical and Psychological connection as we get into biases, semantics, perception and interpretation. In the past week, I …

Corpus Synthesis for Zero-shot ASR Domain Adaptation using Large Language Models

While Automatic Speech Recognition (ASR) systems are widely used in many real-world applications, they often do not generalize well to new domains and need to be finetuned on data from these domains. However, target-domain data is usually not readily available in many scenarios. In this paper, we propose a new strategy for adapting ASR models …

The future of 5G: What to expect from this transformational technology

Since its rollout in 2019, 5G wireless networks have been growing in both availability and use cases. Apple was one of the first manufacturers to test the appetite for 5G in 2020 by offering its newest iPhone with 5G compatibility. From there, the floodgates opened, and today as much as 62% of smartphones are built …

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Cappy: Outperforming and boosting large multi-task language models with a small scorer

Posted by Yun Zhu and Lijuan Liu, Software Engineers, Google Research Large language model (LLM) advancements have led to a new paradigm that unifies various natural language processing (NLP) tasks within an instruction-following framework. This paradigm is exemplified by recent multi-task LLMs, such as T0, FLAN, and OPT-IML. First, multi-task data is gathered with each …

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The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

This is a guest post co-written with Scott Gutterman from the PGA TOUR. Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval. Given the data sources, LLMs provided tools …

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Dive deeper into Gemini with BigQuery and Vertex AI

Traditional barriers between data and AI teams can hinder innovation. Often, these disciplines operate separately and use disparate tools, leading to data silos, redundant data copies, data governance overhead and cost challenges. From an AI implementation perspective, this increases security risks and leads to failed ML deployments and a lower rate of ML models reaching …