Topic: machine learning

TensorFlow Lite gets machine learning model maker

Google has announced the TensorFlow Lite Model Maker. TensorFlow Lite is an open-source deep learning framework for on-device inference. The new tool is designed to adapt machine learning models to datasets with transfer learning.  “It wraps the complex machine learning concepts with an intuitive API, so that everyone can get started without any machine learning … continue reading

SD Times news digest: AWS DeepComposer, React Native 0.62, and Nim programming language 1.2

Amazon announced AWS DeepComposer is now generally available. The company first announced the machine learning solution at AWS re:Invent last year. AWS DeepComposer includes in-console training that enables users to train generative models without having to write any machine learning code. In addition, the composer is powered by  Generative Adversarial Networks (GANs) and allows users … continue reading

8 top open-source community and data tools

As organizations wake up to the multitude of ways advanced technologies can augment their businesses, developers with relevant skills are becoming ever more valuable. Data is the key to a whole kingdom of opportunity, and when combined with AI and machine learning tools, the bounds of this kingdom are practically limitless.  Even for those without … continue reading

premium Software 3.0: Enterprise AI systems and the brave new economy

Machine learning (ML) and other artificial intelligence (AI) technologies are powerful tools with the potential to transform a wide range of processes for both consumers and companies.  Though many of these technologies are still commercially nascent, a number of startups have emerged that provide ML-based software solutions to enterprises. We believe that these “enterprise AI … continue reading

A role in identity verification

Previous methods of identity verification aren’t as efficient today when there is so much more data in circulation. Augmented intelligence has entered the arena to provide much more accurate solutions for ID verification.  Previous methods just required basic information of where someone lives and the applications would then just check a database. One company called … continue reading

Augmented intelligence will help, not replace, human workers

Augmented intelligence is growing as an approach to artificial intelligence, in a way that helps humans complete tasks faster, rather than being replaced by machines entirely.  In an IBM report called “AI in 2020: From Experimentation to Adoption,” 45% of respondents from large companies said they have adopted AI, while 29% of small and medium-sized … continue reading

SD Times news digest: ArrangoML Pipeline Cloud, Hyperledger Fabric 2.0, and Pandas 1.0

ArangoDB has announced a new machine learning offering. The ArangoML Pipeline Cloud is a fully-hosted, fully-managed common metadata layer for production-grade data science and ML platforms that runs on ArangoDB Oasis.  “ArangoML Pipeline Cloud meets the needs of both data scientists, who are concerned with the quality of the data, feature training, and model results, … continue reading

SD Times Open-Source Project of the Week: Manifold

Manifold is a visual debugging tool for machine learning developed by Uber. Machine learning is widely used across the Uber platform to support decision making and forecasting for features such as ETA prediction and fraud detection, the company explained. The tool aims to help engineers and scientists identify performance issues across ML data slices and … continue reading

Amazon aims to democratize deep learning with new library AutoGluon

Amazon has launched a new open-source library that will make it easier for developers to deploy machine learning models. With AutoGluon, Amazon aims to help developers deploy their models using just a few lines of code.  “We developed AutoGluon to truly democratize machine learning, and make the power of deep learning available to all developers,” … continue reading

Continuous Deployment for ML: The new software development life cycle

The new software development life cycle means working out ways to adapt the SDLC for your machine learning workflow and teams. With data scientists currently spending large chunks of their time on infrastructure and process instead of building models, finding ways to enable the SDLC to work effectively with machine learning is critical for not … continue reading

SD Times Open-Source Project of the Week: Ray

Ray is an open-source distributed framework that makes it easy to scale applications and to leverage machine learning libraries. The project was developed by the distributed programming platform company Anyscale. Ray includes three libraries for accelerating machine learning workloads: Tune, RLlib and Distributed Training. According to the company, the machine learning libraries give developers the ability … continue reading

Implications and practical applications for AI and ML in embedded systems

“Civilization advances by extending the number of important operations we can perform without thinking about them.” —Alfred North Whitehead, British mathematician, 1919 Hailed as a truly transformational technology, artificial intelligence (AI) is positioned to disrupt businesses either by enabling new approaches to solving complex problems, or threatening the status quo for whole business sectors or … continue reading

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