NXP Semiconductors has launched a new machine learning toolkit. Called "eIQ", it's a software development platform that supports popular neural network frameworks including Caffe2 and TensorFlow Lite. The platform is aimed particularly at the development of machine learning software for edge devices with limited energy consumption and other resource constraints, with NXP Semiconductors highlighting automotive, industrial, and Internet of Things applications. In announcing the new platform, the company noted that eIQ and its other processor solutions can be used to support a range of machine learning applications including facial recognition, wake word and voice control systems, and computer vision technologies including traffic sign recognition and even food recognition. NXP Semiconductors announced the eIQ platform at this week's IoT World Congress in Barcelona, where the company is demoing examples of real-world applications of its machine learning technology.

Making sense of data can involve a wide variety of tools, and IBM is hoping to make data scientists' lives easier by putting them all in one place. The company on Tuesday released what it calls Data Science Experience, a new development environment in the cloud for real-time, high-performance analytics. Based on data-processing framework Apache Spark, Data Science Experience is designed to speed and simplify the process of embedding data and machine learning into cloud applications. Included in the new offering are tools such as RStudio and Jupyter Notebooks. Developers can tap Python, R and Scala; they can also view sample notebooks and watch tutorials while they code.

Making sense of data can involve a wide variety of tools, and IBM is hoping to make data scientists' lives easier by putting them all in one place. The company on Tuesday released what it calls Data Science Experience, a new development environment in the cloud for real-time, high-performance analytics. Based on data-processing framework Apache Spark, Data Science Experience is designed to speed and simplify the process of embedding data and machine learning into cloud applications. Included in the new offering are tools such as RStudio and Jupyter Notebooks. Developers can tap Python, R and Scala; they can also view sample notebooks and watch tutorials while they code. Additional tools focus on data preparation and cleaning, visualization, prescriptive analytics, data connections, and scheduling jobs.