TensorFlow: Why Google&#8217;s Artificial Intelligence Engine is a Gamechanger
In May 2006, Larry page, one of Google’s co-founders had said “The ultimate search engine would understand everything in the world. It would understand everything that you asked it and give you back the exact right thing instantly. You could ask ‘what should I ask Larry?’ and it would tell you.” Come 2016, it seems at least part of his vision has been achieved through the release of Tensorflow, Google’s Artificial engine platform. Tensorflow is a deep learning software developed by Google as a successor to its DistBelief software, which also focused on deep learning. Deep learning is a concept where activity of neurons in the brain is emulated. The basic idea is to mimic the activity of neurons in the brain in the context of machines and software, through the development of an artificial neural network. This network could help machines and software to perform an array of tasks ranging from speech recognition, image recognition etc. Tensorflow is software built around these principles. The software was built to reason and think like humans and this was made possible by feeding it a vast amount of data and then training it to recognize objects and patterns from the data. For example, image search of eggs and fruit juices could throw up images of a full breakfast. Development in Google: Given Google’s focus on automated machines which operate with the least amount of human interaction, shown from its development of driverless cars and artificial intelligence platforms, Tensorflow is a step forward for Google in achieving its goals. Currently Tensorflow is used in a variety of Google applications like Google photos, Google translate, Gmail etc. Tensorflow helps in removing glitches in the speech recognition process and improving search results. Tensorflow is written in C++ and python, with the latter being more popular with software developers. Google has made Tensorflow open-source, similar to its other software like its android mobile operating system, enabling third parties and software professionals to work on the software. While Google has only made part of the code open-source, it is nevertheless a significant step taken by Google considering the importance of Tensorflow to Google’s overall strategy. Future scope: The concept of Artificial intelligence and Machine learning has been there for decades. Several challenges like the collection and processing of vast amounts of data and the absence of advanced hardware infrastructure derailed their development, leading to artificial intelligence and machine learning being relegated to the domain of science fiction. However recent developments in data analytics combined with improved infrastructure such as availability of GPU’s-Hardware used to parallel process data in small bits- has led to a renewed interest in machine learning and artificial intelligence. Indeed, Artificial intelligence has become the core of some company’s philosophy, with Larry page stating in 2002 “Google will fulfill its mission only when its search engine is AI-complete. You guys know what that means? That’s artificial intelligence.” Along with Google, companies like Facebook, Twitter and Microsoft are also working on developing its AI software to bolster their search capabilities and improve other functions. Companies have recognized that it is necessary to develop unique capabilities and software in order to stay ahead in the market. Indeed, Google’s accession to the top can be mainly attributed to their success in developing unique products. With Tensorflow, Google has come up with a product which could help define its place in the industry for a long time to come.
In May 2006, Larry page, one of Google’s co-founders had said “The ultimate search engine would understand everything in the world. It would understand everything that you asked it and give you back the exact right thing instantly. You could ask ‘what should I ask Larry?’ and it would tell you.” Come 2016, it seems […]
In May 2006, Larry page, one of Google’s co-founders had said “The ultimate search engine would understand everything in the world. It would understand
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["machine learning", "artificial intelligence", "AI", "neural network", "image recognition", "Python", "Ray", "deep learning", "analytics", "TensorFlow"]
["AI", "artificial intelligence", "machine learning", "deep learning", "neural network", "analytics", "Ray", "TensorFlow", "image recognition", "Python"]
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