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AI & Bed Bugs in Paris

"A recent wave of bed bug sightings has erupted across various hotspots in Paris, from Charles de Gaulle airport to the metro, high-speed trains, and even movie theaters. These infestations have alarmed authorities just nine months ahead of the 2024 Paris Olympics."


"A recent wave of bed bug sightings has erupted across various hotspots in Paris, from Charles de Gaulle airport to the metro, high-speed trains, and even movie theaters. These infestations have alarmed authorities just nine months ahead of the 2024 Paris Olympics."

 

 

Exploring AI Capabilities: A Comparison of ChatGPT4 Advanced Data Analysis and Default ChatGPT-4

 

I recently set out to evaluate the new ChatGPT4 Advanced Data Analysis by pitting it against the default ChatGPT-4 platform. My test involved creating two articles, each focusing on the recent bed bug problem in Paris.

 

I then asked both - each- platform to critique, organize, and produce a document comparing the two articles in a two-column format.

Both platforms performed admirably, yet neither fulfilled the final task exactly as I had instructed.

This led me to utilize Claude2, which expertly produced the comparison table I needed.

In the wise words of Alex Karp, CEO of Palantir, "AI is reliable, but it demands multiple layers of verification. It is somewhat akin to the Weather Channel—usually accurate, but occasionally full of surprises, be it rain or shine."

A Cautionary Note on AI Use in Office Settings

If you're planning on using AI tools in the office, ensure that your work is thorough and complete, well critiqued. Don't bring me proposals generated by outdated tools like ChatGPT 3.5; that would be equivalent to gauging the weather by wetting your finger and sticking it in the air.

 

 

Key Observations: ChatGPT4 Advanced Data Analysis vs. Default ChatGPT-4

I did notice some critical distinctions between the articles. ChatGPT4 Advanced Data Analysis version appears to be heavily influenced by a data-driven approach: (let me add, I did not enjoy BING at all before, 3 months ago when I first tried it!!)

 

• Actionable Recommendations: The conclusion specifically emphasizes practical, evidence-based strategies, highlighting health impacts.

• Quantifiable Health Impacts: It provides comprehensive details on health outcomes like skin infections and psychological distress, indicating a focus on measurable metrics.

• Demographic Considerations: There is a thoughtful discussion about how population density affects the spread of bed bugs, underlining the platform's attention to demographic data.

• Data-Driven Measures: Recommendations such as regular monitoring and inspections suggest a strategy based on collecting and analyzing data to identify high-risk areas.

 

Overall, the ChatGPT4 Advanced Data Analysis version adopts a more data-driven approach. It focuses heavily on health statistics, population data, and employs actionable strategies based on quantifiable metrics.

 

This sharply contrasts with the default ChatGPT4, which relies more on a qualitative analysis of economic impacts and factors like neighbor-to-neighbor spread.

 

Below, you will find a table that highlights the key differences between the two articles on the bed bug crisis in Parisa table I created using Claude2.

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Infinity AI

A subsidiary of Powerstorm Holdings, Inc (PSTO), is on a transformative journey, utilizing AI to provide advanced solutions with AI Automation partners, by offering value-added AI services to its longstanding telecom operator clients.

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