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Skinner, who was responsible for bringing the whole subject into popular view, acknowledged Pressey's work in his 1958 paper on teaching machines. [15] [16] Sidney was displeased by the “crass commercialization” of teaching machines. He objected to this use of teaching machines feeling they had a lack of questioning about basic theory.
The concept of intelligent machines for instructional use date back as early as 1924, when Sidney Pressey of Ohio State University created a mechanical teaching machine to instruct students without a human teacher. [5] [6] His machine resembled closely a typewriter with several keys and a window that provided the learner with questions. The ...
The ideas of teaching machines and programmed learning provided the basis for later ideas such as open learning and computer-assisted instruction. Illustrations of early teaching machines can be found in the 1960 sourcebook, Teaching Machines and Programmed Learning. [12] An "Autotutor" was demonstrated at the 1964 World's Fair. [13]
OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
The Google Brain team contributed to the Google Translate project by employing a new deep learning system that combines artificial neural networks with vast databases of multilingual texts. [21] In September 2016, Google Neural Machine Translation (GNMT) was launched, an end-to-end learning framework, able to learn from a large number of ...
In 2017, Google announced, in association with Pluralsight, 100,000 scholarships to help developers gain access to advanced learning curriculum in emerging technologies, including mobile and web development, machine learning, artificial intelligence, and cloud platforms in India.
In May 2016, Google announced its Tensor processing unit (TPU), an application-specific integrated circuit (ASIC, a hardware chip) built specifically for machine learning and tailored for TensorFlow. A TPU is a programmable AI accelerator designed to provide high throughput of low-precision arithmetic (e.g., 8-bit ), and oriented toward using ...