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It’s been a huge decade for big data and artificial intelligence (AI), two of the biggest tech trends we’ve seen this century. From data-driven manufacturing to self-driving cars, we’ve witnessed dozens of jaw-dropping, previously unimaginable feats, all thanks to advances in big data analytics and AI.
Not so long ago, businesses across industries often sat on tons of useful, game-changing data, unsure about the many ways they could put it to use to gain competitive advantage. But as methods in machine learning, deep learning, and natural language processing became more advanced while computing power went up, seemingly useless data suddenly began to make sense.
For instance, businesses could use customer data to analyze demographic profiles, shopping habits, and other behaviors, which helped improve marketing campaigns and overall customer experience.
Still, despite all the good that comes with AI, its growth presents a myriad of challenges for big data, especially when you consider how data-hungry AI systems can be.
These challenges represent the biggest roadblock that must be addressed before we can fully realize the potential of AI and big data.
1. Data Privacy and Security
AI systems, even the most basic forms, are usually very complex, with tons of algorithms obscuring what the system is …
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