In an interview with Wired, Facebook's head of AI, Jerome Pesenti, theorized that the development of artificial intelligence and machine learning is …

"Every pharma company I know of is using some sort of machine learning or AI to create better pharmaceuticals," Matchette said. "The result is we're …

Bio-IT World: When the term machine learning or artificial intelligent (AI) is brought up, the first word that comes to mind is "Watson" from IBM. Are you …

The incredibly large, Nazca Lines of Peru has always been a mysterious wonder, a sight best viewed from the air. Located near Lima, these impressive geometric figures are etched on a coastal desert. Recently, a team of Japenese researchers have found 143 new figures using satellite photography, 3D imaging and artificial intelligence. They portray animal and human figures like camels, llamas, cats and snakes, while some are more abstract, appearing as geometric shapes. Already, images of a monkey, hummingbird, and spider are quite famous.

This is a project that I have been working on to automate testing my experiments in data science projects. It also involves some automated experiments. However, there is still a lot of work to be done. I will be writing unit tests and making some parts simpler. It can work with tensorflow and lgbm, but some work needs to be done before that.

The field of machine learning underwent massive changes in the 2010's. At the beginning, the field saw diverse approaches applied to a variety of topics and data structures. Then Alexnet blew away the competition for the Imagenet challenge with his CNN, and the field was forever changed. However, there was a warming up phase. Caffe's first release was in 2013.

Netflix's data-science team has open-sourced its Metaflow Python library, a key part of the'human-centered' machine-learning infrastructure it uses for building and deploying data-science workflows. The video-streaming giant uses machine learning across all aspects of its business, from screenplay analysis, to optimizing production schedules, predicting churn, pricing, translation, and optimizing its giant content distribution network. According to Netflix software engineers, Metaflow was built to help boost the productivity of its data scientists who like to express business logic through Python code but don't want to spend too much time thinking about engineering issues, such as object hierarchies, packaging issues, or dealing with obscure APIs unrelated to their work. The idea behind Metaflow was to give Netflix data scientists the ability to see early on whether a prototyped model would fail in production, allowing them to fix whatever the issue was and ideally speed up deployment times. Netflix in February revealed that Metaflow had helped reduce median deployment times from four months to just seven days.

Abstract: In this report, we introduce Procgen Benchmark, a suite of 16 procedurally generated game-like environments designed to benchmark both sample efficiency and generalization in reinforcement learning. We believe that the community will benefit from increased access to high quality training environments, and we provide detailed experimental protocols for using this benchmark. We empirically demonstrate that diverse environment distributions are essential to adequately train and evaluate RL agents, thereby motivating the extensive use of procedural content generation. We then use this benchmark to investigate the effects of scaling model size, finding that larger models significantly improve both sample efficiency and generalization.

Many retailers already use Artificial Intelligence (AI) in their recruiting systems for hiring the best and brightest seasonal help.