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People learn through trial and error, for both good and bad. Same thing will happen with A.I.
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'How societies decide to weigh caution against the speed of innovation, accuracy against explainability, and privacy against performance will determine what kind of relationships human beings develop with intelligent machines.'
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Even the smartest person in history couldn't have done everything he did without a lot of help from other smart people.
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Google Cloud made a significant announcement today, revealing a plethora of fresh AI-powered functionalities for its productivity tools. However, the company's latest release of APIs and tools for developers is equally intriguing - and arguably, even more compelling.
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At this year's Mobile World Congress, discussions around power consumption and sustainability took center stage as the industry grapples with the escalating energy costs and unprecedented data usage.
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The 2022 Global Market Study of Data Science and Machine-Learning Platforms provides a comprehensive analysis of the industry's performance, competitive landscape, and global market trends.
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Machine learning (ML) is an indispensable aspect of a data scientist's role, with valuable and highly sought-after skills that extend beyond the realm of data science.
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The global market size for Machine Learning as a Service was USD 7.1 billion in 2022, and it is projected to reach USD 173.5 billion with a compound annual growth rate (CAGR) of 37.9% by 2032.
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According to the Machine Learning Industry Data Book, 2023 - 2030 published by Grand View Research, the machine learning industry is set to experience significant growth due to the increasing use of AI and IoT devices.
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NLP involves the analysis and processing of natural language data, including text and speech, for the purpose of executing specific tasks such as language translation, sentiment analysis, and chatbot interaction