Today, MLCommons®, an open engineering consortium, released new results from MLPerf™ Training v2.0, which measures the performance of training machine learning models. Training models empowers researchers to unlock new capabilities faster such as diagnosing tumors, automatic speech recognition or improving movie recommendations. The latest MLPerf Training results demonstrate broad industry participation and up to 1.8X greater performance ultimately paving the way for more capable intelligent systems to benefit society at large.
Jacqueline Berger – Drilling Engineer & Data scientist (In view – 2023)
As a drilling engineer with so many years and interesting internationalexperiences, Jacqueline is one who seeks a new adventure in data science.Her transition into informatics and data science came after her maternityleave while working at Schlumberger. Trying to fit the experience into her “new”the world did not come easy and in search for an alternative led her to informaticsand data science.In her experience of working in the oil and gas sector, a field dominated by men,she mentioned that while it was a male-dominated field, she never felt suppressed ina negative way that made her feel she was not enough. She also said that the use ofpieces of machinery meant that many of the muscle works were automated and easier.About how she got attracted to data science. Jacqueline believes her interest indata science has the common denominator with her previous job as a drilling engineer, which was the use of data for analysis and description.
What Is Data Reliability Engineering?
In this contributed article, Kyle Kirwan, CEO and co-founder of Bigeye, discusses Data Reliability Engineering (DRE), the work done to keep data pipelines delivering fresh and high-quality input data to the users and applications that depend on them. The goal of DRE is to allow for iteration on data infrastructure, the logical data model, etc. as quickly as possible, while—and this is the key part! —still guaranteeing that the data is usable for the applications that depend on it.
Survey Results Identifying the Benefits and Challenges of RPA
Robocorp, a top provider of Gen2 robotic process automation (RPA), announced the results of their State of RPA survey, which was designed to understand the challenges users face with current RPA solutions. The results will help usher in the next generation of enterprise automation – Gen2 RPA.
How is IoT Changing the Future of Cruising?
In this special guest feature, Ian Richardson, CEO & Co-Founder, theICEway, discusses how as the world continues to open for travel, cruise industry leaders are looking to leverage the next wave of travel technology to improve the passenger experience.
More Than You Know: The Enterprise Worth of Natural Language Generation
In this contributed article, editorial consultant Jelani Harper highlights how Natural Language Generation (NLG) is arguably the nexus point of natural language technologies. It utilizes Natural Language Processing (NLP), is a prerequisite for conversational AI, and largely requires Natural Language Understanding (NLU) for meaningful responses to interrogatives or commands.
Domino Data Lab Announces Hybrid MLOps Architecture to Future-Proof Model-Driven Business at Scale
Domino Data Lab, a leading Enterprise MLOps platform trusted by over 20 percent of the Fortune 100, announced its new Nexus hybrid Enterprise MLOps architecture that will allow companies to rapidly scale, control and orchestrate data science work across different compute clusters — in different geographic regions, on premises, and even across multiple clouds.
Dataiku 11 Unveils Enhanced Toolset to Scale AI
Dataiku announced Dataiku 11, a pivotal update of the company’s data science and AI platform that helps organizations to deliver on the promise of Everyday AI. This packed release provides new capabilities for expert teams to deliver more value at scale, enables tech-savvy workers to take on more expansive challenges, helps non-technical workers more easily engage with AI, and provides strengthened AI Governance to ensure projects are robust, transparent, and ready for success at scale.
Making a Case for the First Open Source Platform for Synthetic Data
In this special guest feature, Yashar Behzadi, Ph.D., CEO and Founder of Synthesis AI, discusses on the importance of a community like OpenSynthetics in developing more capable AI models.
OpenSynthetics, an open community for creating and using synthetic data in AI/ML and computer vision, is open to practitioners, researchers, academics, and the wider industry.
Streamlining Data Evolution in a Rapidly Changing World
In this contributed by Adam Glaser from Appian believes that in a fast-changing, digital-driven world, having access to the right data at the right time is crucial. That is why, as data evolves, it must be brought together in a reliable and efficient way that creates a powerful asset, not a compliance challenge.