Global Big Data Conference

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For years, the sheer messiness of data slowed efforts to launch artificial intelligence (A.I.) and machine learning projects. Companies weren't willing to wait a year or two while data analysts cleaned up a massive dataset, and executives sometimes had a hard time trusting the outputs of a platform or tool built on messy data. Data pre-processing is a well-established art, and there are many tech pros out there who specialize in tweaking datasets for maximum validity, accuracy, and completeness. It's a tough job, and someone has to do it (usually with the assistance of tools, as well as specialized libraries such as Pandas). But now IBM is trying to apply A.I. to this issue, via new data prep tools within AutoAI, itself a tool within the cloud-based Watson Studio.


Apple details Overton AI development tool, whose models have processed 'billions' of queries

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Building, monitoring, and improving machine learning systems is no walk in the park, no matter the circumstances. Data scientists and engineers have to monitor fine-grained quality and diagnose errors in sophisticated apps, not to mention field contradictory or incomplete corpora. To ease the development burden somewhat, Apple developed Overton, a framework intended to automate AI system lifecycles by providing a set of novel high-level abstractions. Given the query "How tall is the president of the United States," for example, Overton generates a model capable of supplying an answer. Apple researchers say that Overton has been used in production to support "multiple applications" in both near-real-time and back-of-house processing, and in that time, Overton-based apps have answered "billions" of queries in multiple languages and processed "trillions" of records.


IBM Wants To Make Artificial Intelligence Fair And Transparent With AI OpenScale

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IBM has announced AI OpenScale, a service that aims to bring visibility and explainability of AI models for enterprises. When it comes to adopting AI for business use, there are multiple concerns among enterprise customers. Lack of visibility of the model, unwanted bias, interoperability among tools and frameworks, compliance in building and consuming AI models are some of the critical issues with AI. IBM AI OpenScale provides explanations into how AI models are making decisions, and automatically detect and mitigate bias to produce fair, trusted outcomes. It attempts to bring confidence to enterprises by addressing the challenges involved in adopting artificial intelligence.


IBM Wants To Make Artificial Intelligence Fair And Transparent With AI OpenScale

#artificialintelligence

IBM has announced AI OpenScale, a service that aims to bring visibility and explainability of AI models for enterprises. When it comes to adopting AI for business use, there are multiple concerns among enterprise customers. Lack of visibility of the model, unwanted bias, interoperability among tools and frameworks, compliance in building and consuming AI models are some of the critical issues with AI. IBM AI OpenScale provides explanations into how AI models are making decisions, and automatically detects and mitigates bias to produce fair, trusted outcomes. It attempts to bring confidence to enterprises by addressing the challenges involved in adopting artificial intelligence.


IBM Wants To Make Artificial Intelligence Fair And Transparent With AI OpenScale

#artificialintelligence

IBM has announced AI OpenScale, a service that aims to bring visibility and explainability of AI models for enterprises. When it comes to adopting AI for business use, there are multiple concerns among enterprise customers. Lack of visibility of the model, unwanted bias, interoperability among tools and frameworks, compliance in building and consuming AI models are some of the critical issues with AI. IBM AI OpenScale provides explanations into how AI models are making decisions, and automatically detects and mitigates bias to produce fair, trusted outcomes. It attempts to bring confidence to enterprises by addressing the challenges involved in adopting artificial intelligence.