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Apple is Working on a new Predictive Keyboard AI for Better Word Accuracy

AI technology is already being used to some degree in smartphone keyboards, but Apple is now testing a new predictive keyboard that taps AI to read whole documents. Based on the challenge of teaching a machine to use all of a document's content, this new predictive keyboard aims to be incredibly accurate when suggesting what words someone will type next.

While current predictive text AIs use a combination of narrow and local context, this new predictive keyboard AI relies on "global semantic context." This leads to better results when predicting words to use and takes in semantics, context, and style into its suggestions. The program is still under development, as Apple needs to continue to teach its AI, but it is making progress. The ultimate goal is to further the capabilities of AI in understanding how to read and assess text.
Trend Themes
1. Global Semantic Context AI - Developing AI predictive keyboard that uses global semantic context leads to better prediction and accuracy in suggesting what words someone will type next.
2. AI-assisted Document Reading - Teaching AI predictive keyboard to read and understand whole documents presents an opportunity to improve productivity and accuracy in content creation.
3. Improving AI Capabilities - Continuing to develop AI technology to read and assess text has the potential to revolutionize the way technology aids in communication and information sharing.
Industry Implications
1. Technology - The technology industry has the opportunity to develop and integrate AI predictive keyboard technology into devices and software, with a focus on improving productivity and ease of use for users.
2. Communication - Integrating AI predictive keyboards in communication software, such as messaging and email platforms, has the potential to revolutionize the way people communicate and make it easier to convey information accurately and efficiently.
3. Content Creation - AI-assisted document reading and writing has the potential to improve the efficiency and accuracy of content creation in industries such as journalism, publishing, and academia, amongst others.

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