Remove Cybersecurity Remove Data Requirement Remove Healthcare
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Must-Have AI Features for Your App

Sisense

Whether it’s core to the product, as with a stock market forecasting algorithm in Quants, or a peripheral component, such as a healthcare domain chatbot that diagnoses diseases via dialog with a patient, building reliable AI components into products is now part of the learning curve that product teams have to manage. .

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Understanding Data Loss Prevention (DLP)

GAVS Technology

Human Error: Mistakes such as accidental data sharing or configuration errors that unintentionally expose data, requiring corrective actions to mitigate impacts. Data Theft: Unauthorized acquisition of sensitive information through physical theft (e.g., She enjoys exploring new cybersecurity technologies.

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Moving to the cloud? Choose cloud service providers wisely

Analysts Corner

Among the downsides of a public cloud are limited customization and a higher risk of a data breach since public clouds are available to anyone. So when choosing a public cloud services provider, it’s worth paying much attention to the cybersecurity measures it has in place. When to use?

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Ethical Concerns With AI/ML – Some Myths vs. Facts

GAVS Technology

Following actions are taken to minimize privacy challenges: Better Data Hygiene: Only the data required for the use case is captured/stored Use of Accurate Datasets: Quality of AI models is enhanced by training with accurate datasets User Control: Users are informed of their data being used and asked for consent.