Manufactured Data

Organizations committed to data driven decision making often share common concerns about privacy, data integrity, and a lack of sufficient data. Synthetic data allows companies to share data and create algorithms more easily. This interesting information came to us from MIT’s Sloan School of Management in their article, “What is synthetic data — and how…

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Understanding the Impact and Potential of AI

Artificial intelligence (AI) can be transformative for businesses, but the increased use of the technology inevitably leads to a higher rate of AI system failures. The World Economic Forum brought this interesting information to our attention in their article, “Scaling AI: Here’s why you should first invest in responsible AI.” AI has reshaped industries and…

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Getting Personal with AI

Artificial intelligence (AI) brings with it a promise of genuine human-to-machine interaction. When machines become intelligent, they can understand requests, connect data points, and draw conclusions. They can observe, reason, and plan. It’s very common to hear the terms “machine learning” and “AI” thrown around in the wrong context, but they are not the same.…

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Governing AI

Artificial intelligence (AI) governance is the idea that there should be a legal framework for ensuring that machine learning technologies are well researched and developed with the goal of helping humanity navigate the adoption of AI systems fairly. This interesting information came to us from Fortune in their article, “Investors are pouring billions into artificial intelligence. It’s time for a…

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Learning from the Data

When it comes to machine learning algorithms, your predictions are only as good as your data. And if you aren’t using the right data, you aren’t setting your models up for success. This interesting topic came to us from KD Nuggets in their article, “The Difference Between Training and Testing Data in Machine Learning.” When…

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Understanding the Difference

Data science, data analytics, and machine learning are terms that are often used interchangeably when talking about making sense of big data. But this is wrong. Data science is a field that studies data and how to extract meaning from it, whereas machine learning is a field devoted to understanding and building methods that utilize data to improve…

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Emerging Technologies Now and Tomorrow

Even with the evolution of emerging technologies, memory remains one of the most critical technologies for enabling continued advances in artificial intelligence (AI) and machine learning processing. Fierce Electronics brought this interesting information to us in their article, “Memory is key to future AI and ML performance.” The future will demand that AI and machine…

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Learning More About Emerging Tech

When it comes to machine learning algorithms, your predictions are only as good as your data. And if you aren’t using the right data, you aren’t setting your models up for success. This interesting topic came to us from KD Nuggets in their article, “The Difference Between Training and Testing Data in Machine Learning.” When…

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Quality and AI

Data quality has never been more important. It is at the heart of the success of enterprise artificial intelligence (AI) and other emerging technologies. It remains the main source of challenges for companies that want to apply machine learning in their applications and operations. Venture Beat brought this interesting information to our attention in their article, “Why data…

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Emerging Tech, Healthcare and COVID-19

Emerging technologies like machine learning and artificial intelligence (AI) are impacting various types of business and some in powerful ways. Researchers from the University of California at Berkeley have developed machine learning software that uses entries in electronic health records (EHRs) to shed light on post-COVID-19 syndrome, commonly referred to as long COVID. Health IT Analytics brought…

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