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ML

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  • 5 min

Sentiment Analysis With BigQuery ML

Introduction We recently announced BigQuery support for sparse features which help users to store and process the sparse features efficiently while working with them. That functionality enables users to represent sparse tensors and train machine learning models directly in the BigQuery environment. Being able to represent sparse tensors is a useful feature because sparse tensors are used extensively in encoding schemes like TF-IDF as part of data pre-processing in NLP applications and for pre-processing images with a lot of dark pixels in computer vision applications. There are numerous applications of sparse features such as text generation and sentiment analysis. In…
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  • 4 min

Vertex AI Example-Based Explanations Improve ML Via Explainability

Artificial intelligence (AI) can automatically learn patterns that humans can’t detect, making it a powerful tool for getting more value out of data. A high-performing model starts with high-quality data, but in many cases, datasets have issues such as incorrect labels or unclear examples that contribute to poor model performance. Data quality is a constant challenge for enterprises—even some datasets used as machine learning (ML) benchmarks suffer from label errors. ML models are thus often notoriously difficult to debug and troubleshoot. Without special tools, it’s difficult to connect model failures to root causes and even harder to know the next…
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  • 3 min

Ready To Solve For The future? Data Cloud Summit ’22 Is Coming April 6

At Google Cloud, we’ve helped tens of thousands of companies build data clouds that leverage the full power of data, from databases and analytics that support decision making, to AI and ML that predict and automate the future. Organizations across all industries have gravitated to Google’s tools for building data clouds because of our proven speed, scale and security, as well as our long-standing leadership in AI. If anyone has seen firsthand how data can modernize businesses and revolutionize industries, it’s our customers and partners. And next month, so can you. Get the perspective and insight you need to turn…
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  • 3 min

Integration Of Cloudian Object Storage And WekaFS™ Enables Rapid Processing Of Analytical Workloads And Saves 1/3 In Costs Over Traditional Storage Systems

Cloudian® today announced the integration of its HyperStore® object storage with the WEKA Data Platform for AI, providing high-performance, exabyte-scalable private cloud storage for processing iterative analytical workloads. The combined solution unifies and simplifies the data pipeline for performance-intensive workloads and accelerated DataOps, all easily managed under a single namespace. In addition, the new solution reduces the storage TCO associated with data analytics by a third, compared to traditional storage systems.   Advanced Analytics Workloads Create Data Storage Challenges Organizations are consuming and creating more data than ever before, and many are applying AI, machine learning (ML) and other advanced analytics on these…
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  • 3 min

Cohere And Google Cloud Announce Multi-Year Technology Partnership

Cohere, a provider of cutting-edge natural language processing (NLP) services, and Google Cloud today announced a multi-year partnership in which Google Cloud’s advanced artificial intelligence (AI) and machine learning (ML) infrastructure will power Cohere’s platform. Many of Cohere’s products will be developed and deployed on Cloud TPUs, Google’s supercomputers that are optimized for large-scale ML, enabling Cohere to broaden access to advanced large language models (LLMs) and NLP to more small businesses and large enterprises alike. Today, organizations in every industry generate massive quantities of unstructured, text-heavy data such as web pages, business documents, invoices, and customer support records. NLP…
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  • 3 min

4 Agile Testing Trends That Will Continue in 2022

Since their inception in 2001, agile practices have radically evolved. It was first about shifting from the waterfall model of software development to focusing on iterative development using Scrum, XP, and other methodologies, thereby removing many bottlenecks organizations had with faster software delivery. Agile is now about optimizing operations within the development process, using different practices and tools, and making the entire process more efficient. It is about starting the testing process right from the beginning of the development lifecycle to catch defects early and distilling insights from the data collected from each stage of the development process. Agile continues…
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