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In: Artificial Intelligence

Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval. In this post, we showcase how to fine-tune a sentence transformerContinue Reading

In: Artificial Intelligence

Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. Evaluation,Continue Reading

In: Artificial Intelligence

Professionals in a wide variety of industries have adopted digital video conferencing tools as part of their regular meetings with suppliers, colleagues, and customers. These meetings often involve exchanging information and discussing actions that one or more parties must take after the session. The traditional way to make sure informationContinue Reading

In: Artificial Intelligence

Enterprises in industries like manufacturing, finance, and healthcare are inundated with a constant flow of documents—from financial reports and contracts to patient records and supply chain documents. Historically, processing and extracting insights from these unstructured data sources has been a manual, time-consuming, and error-prone task. However, the rise of intelligentContinue Reading

In: Artificial Intelligence

In the modern, cloud-centric business landscape, data is often scattered across numerous clouds and on-site systems. This fragmentation can complicate efforts by organizations to consolidate and analyze data for their machine learning (ML) initiatives. This post presents an architectural approach to extract data from different cloud environments, such as GoogleContinue Reading

In: Artificial Intelligence

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. Examples include financial systems processing transaction data streams, recommendation engines processing user activity data, and computer vision models processing video frames. In these scenarios, customized model monitoring for nearContinue Reading

In: Artificial Intelligence

This post is co-written with Lee Rehwinkel from Planview. Businesses today face numerous challenges in managing intricate projects and programs, deriving valuable insights from massive data volumes, and making timely decisions. These hurdles frequently lead to productivity bottlenecks for program managers and executives, hindering their ability to drive organizational successContinue Reading

In: Artificial Intelligence

Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. LLMs are incredibly flexible. One model can perform completely different tasks such as answering questions, summarizing documents, translating languages, and completing sentences. LLMs have the potential to revolutionize content creation and the wayContinue Reading