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The road to Software 2.0 – O’Reilly
Source: oreilly.com
Article summary:
1. Andrej Karpathy's concept of Software 2.0 suggests that machine learning can be used to automate software development.
2. Companies are beginning to adopt tools for automating various aspects of software engineering and data science, such as AWS Sagemaker and Google AutoML.
3. The biggest obstacles to adoption are lack of skilled people, trouble finding the right use cases, and difficulty finding data.
Article analysis:
The article is generally reliable and trustworthy in its reporting on the progress made in the year since the original article was written about Andrej Karpathy’s concept of Software 2.0. It provides a comprehensive overview of the tools that have been developed for automating various aspects of software engineering and data science, such as AWS Sagemaker and Google AutoML, as well as discussing the obstacles to adoption such as lack of skilled people, trouble finding the right use cases, and difficulty finding data.
The article does not appear to be biased or one-sided in its reporting; it presents both sides equally by providing an overview of both the progress made in developing automated tools for software engineering and data science, as well as discussing potential obstacles to adoption. It also provides evidence for its claims by citing specific examples such as Snorkel (for automated data labeling and synthetic data generation), HoloClean (for automatic error detection and repair), Platform.ai (for computer vision), Matroid (also for computer vision), Uber’s Michelangelo, Facebook’s FBLearner, Twitter’s Cortex, Apple’s Overton, Databricks (for building SaaS or on-premises tools), RISE Lab’s AutoPandas (for programming by example).
The article does not appear to be promotional content or partiality; it is an objective overview of the progress made in developing automated tools for software engineering and data science over the past year since Karpathy's concept was first introduced. The article also notes possible risks associated with using these automated tools such as lack of skilled people or difficulty finding data which could potentially hinder their adoption.
In conclusion, this article appears to be reliable and trustworthy in its reporting on Software 2.0; it provides a comprehensive overview without bias or partiality while noting potential risks associated with using these automated tools which could potentially hinder their adoption.