NEWS IN BRIEF: AI/ML FRESH UPDATES

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OpenAI's Record-Breaking $110bn Funding Round

OpenAI is raising $110bn in funding, valuing ChatGPT maker at $840bn, with backing from Nvidia and Amazon, showcasing the rapid AI investment pace. Last year, the company raised $40bn in the largest private tech deal, now doubling its investment amount.

AI-proof stocks fuel market surge

Goldman Sachs notes investors favoring 'Halo trade' for AI-proof companies with tangible assets like energy and transport infrastructure. Investors seek 'heavy-asset, low-obsolescence' firms to weather AI disruption.

COBOL Modernization: Real World Insights

AI is accelerating COBOL modernization, but success requires complete context and platform-aware input for forward engineering. Mainframe modernization hinges on reverse engineering and a traceable foundation for AI coding assistants.

ChatGPT Health: A Deadly Oversight

Study: ChatGPT Health fails to recommend hospital visits when necessary, risking harm. OpenAI's AI platform overlooks urgent care and suicidal ideation, potentially endangering users' lives.

Building Decision Tree Regression in C#

Learn about Decision Tree Regression implemented from scratch using C# without pointers or recursion in Visual Studio Magazine. Decision trees offer interpretability and can be used alone or in ensembles for regression tasks.

Training AI: The Future of Work

Workers express feeling devalued by AI technology, fearing a decline in work quality. IMF analysis predicts AI impact on 40% of global jobs, likening it to a labor market tsunami.

Protecting Original Journalism from AI

UK media companies, including BBC and Financial Times, seek global frameworks to protect journalism from unauthorized use by AI firms. Guardian-led coalition aims to ensure fair compensation for original content to ensure industry sustainability.

Teaching AI: Fine-tuning Amazon Nova with Feedback

Foundation models excel at general tasks, but customizing models with business knowledge is crucial. Amazon introduces reinforcement fine-tuning for Nova models, shifting from imitation to evaluation learning paradigm, offering tailored solutions for code generation and math reasoning.