Governments rush to regulate AI

With artificial intelligence being in widespread use, the concern for how AI makes decisions have increased. Governments are worried about its risks and are grappling with controlling its ability to do harm– before it actually does so.As AI regulations kick in, industry fears it’ll hurt innovation. But everyone has an interest in AI research being conducted carefully, with proper oversight and transparency.

The AI Chatbot Report Card

AI chatbots – the confluence of artificial intelligence and chat programs – are revolutionary. They use machine learning algorithms to mimic human-like conversation, bridging the gap between human users and digital interfaces. They understand inputs, process them using natural language processing capabilities, and generate appropriate responses. But their vision for the future may be short-sighted.

MLOps in Action

Machine Learning Operations (MLOps) brings together machine learning, DevOps, and data engineering to streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps have become increasingly crucial for businesses to remain competitive in today’s AI-driven landscape.Leading edtech platform Brainlyleverages MLOps to create a cutting-edge visual search pipeline, optimising user experience and driving innovation in the EdTech space.

Generative AI finds a likely answer to the riddle of the Productivity Paradox

A series of research papers revealed that General-purpose technologies (GPTs) can affect entire economies, usually on a national or global level. GPTs have strong impact on pre-existing economic and social structures.Hence, they can drastically alter societies and also has the potential to address some of the riddles posed by the ProductivityParadox.

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