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20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% billion by the end of 2025. billion by the end of 2025.

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20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% billion by the end of 2025. billion by the end of 2025.

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Slack’s former head of machine learning wants to put AI in reach of every company

TechCrunch

Adam Oliner, co-founder and CEO of Graft used to run machine learning at Slack, where he helped build the company’s internal artificial intelligence infrastructure. With a small team, he could only build what he called a “miniature” solution in comparison to the web scale counterparts.

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Build a strong data foundation for AI-driven business growth

CIO

In the quest to reach the full potential of artificial intelligence (AI) and machine learning (ML), there’s no substitute for readily accessible, high-quality data. If the data volume is insufficient, it’s impossible to build robust ML algorithms. If the data quality is poor, the generated outcomes will be useless.

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Dulling the impact of AI-fueled cyber threats with AI

CIO

Artificial Intelligence: A turning point in cybersecurity The cyber risks introduced by AI, however, are more than just GenAI-based. And while the cyber risks introduced by AI can be countered by incorporating AI within security tools, doing so can be resource-intensive.

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Building a vision for real-time artificial intelligence

CIO

Data is a key component when it comes to making accurate and timely recommendations and decisions in real time, particularly when organizations try to implement real-time artificial intelligence. The underpinning architecture needs to include event-streaming technology, high-performing databases, and machine learning feature stores.

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Accelerating AI at scale without sacrificing security

CIO

Failing to invest in data governance and security practices risks not only regulatory lapses and internal governance violations, but also bad outputs from AI that can stunt growth, lead to biased outcomes and inaccurate insights, and waste an organization’s resources. are creating additional layers of accountability.