Meta faces dual celebrity AI crises: unauthorized bots impersonating Swift and others while licensed celebrity voices engaged inappropriately with minors. Both expose how engagement incentives override safety guardrails.
Despite massive AI hype, 95% of enterprise projects deliver no real returns. The gap between promises and reality reveals hidden costs, workflow mismatches, and why human oversight remains surprisingly essential.
Meta's $14B AI talent blitz hits turbulence as ChatGPT co-creator Shengjia Zhao threatened to quit days after joining. The company hastily named him Chief Scientist to prevent defection, but at least three other marquee hires have already left.
Category: Fundamentals
Category: Fundamentals
Data science extracts insights from data using statistics, programming, and domain knowledge to solve business problems.
Data scientists collect, clean, and analyze data to find patterns and make predictions. They use tools like Python, R, and SQL along with machine learning techniques.
The work combines technical skills with business understanding to turn data into actionable insights.
Data science drives decision-making in modern organizations. It helps companies understand customers, optimize operations, and predict trends.
Many AI applications start with data science work to understand what's possible with available data.
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