Our 10 biggest AI moments so far


2006: Google Translate launches

Five years later, we launched Google Translate, which used machine learning to automatically translate languages. We started with Arabic to English and English to Arabic translations, but today Google Translate supports 133 languages spoken by millions of people around the world. This technology can translate text, images or even a conversation in real time, breaking down language barriers across the global community, helping people communicate and expanding access to information like never before.

2015: TensorFlow democratizes AI

The introduction of TensorFlow, a new open source machine learning framework, made AI more accessible, scalable and efficient. It also helped accelerate the pace of AI research and development around the world. TensorFlow is now one of the most popular machine learning frameworks, and has been used to develop a wide range of AI applications, from image recognition to natural language processing to machine translation.

2016: AlphaGo defeats world champion Go player

As part of the Google DeepMind Challenge Match, more than 200 million people watched online as AlphaGo became the first AI program to defeat a human world champion in Go, a complex board game previously considered out of reach for machines. This milestone victory demonstrated deep learning’s potential to solve complex problems once thought impossible for computers. AlphaGo’s victory over Lee Sedol, one of the world’s best Go players, sparked a global conversation about AI’s future and showed that AI systems could now learn to master complex games requiring strategic thinking and creativity.

2016: TPUs enable faster, more efficient AI deployment

Tensor Processing Units, or TPUs, are custom-designed silicon chips we specifically invented for machine learning and optimized for TensorFlow. They can train and run AI models much faster than traditional chips, which makes them ideal for large-scale AI applications. Version v5e, announced in August, is the most cost-efficient, versatile, and scalable Cloud TPU to date.

Original Source: https://blog.google/technology/ai/google-ai-ml-timeline/

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