Google goes for More AI Automation

More indications to the automation of the design and delivery of AI.   See the quite technical paper referenced below.The trend most likely to continue.

Google’s TF-Coder tool automates machine learning model design
Kyle Wiggers in VentureBeat    @Kyle_L_Wiggers

Researchers at Google Brain, one of Google’s AI research divisions, developed an automated tool  https://arxiv.org/pdf/2003.09040.pdf  for programming in machine learning frameworks like TensorFlow. They say it achieves better-than-human performance on some challenging development tasks, taking seconds to solve problems that take human programmers minutes to hours.

Emerging AI techniques have resulted in breakthroughs across computer vision, audio processing, natural language processing, and robotics. Playing an important role are machine learning frameworks like TensorFlow, Facebook’s PyTorch, and MXNet, which enable researchers to develop and refine new models. But while these frameworks have eased the iterating and training of AI models, they have a steep learning curve because the paradigm of computing over tensors is quite different from traditional programming. (Tensors are algebraic objects that describe relationships between sets of things related to a vector space, and they’re a convenient data format in machine learning.) Most models require various tensor manipulations for data processing or cleaning, custom loss functions, and accuracy metrics that must implemented within the constraints of a framework.  ..... "