Exploring the Truth About A.I. and Its Implications
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Chapter 1 Understanding A.I. and Gartner's Spaghetti Graph
This week, we have a special guest who will help clarify the complexities surrounding Gartner's spaghetti graph. Make sure to subscribe to the Analytically Yours YouTube channel for the latest insights.
Section 1.1 Effective Marketing Through Data
Spotlighting Masumi Nakamura, Mercari's VP of Engineering, we delve into the company's remarkable journey. Achieving effective marketing means aligning the right offer with the right audience at the right moment, all while minimizing customer churn. While this concept may seem straightforward, its execution is anything but simple.
Previously, Mercari needed months to transition from data acquisition to campaign launch. Now, they've streamlined this process to just days. Here's a closer look at their approach:
- Customer 360: Integrating diverse data sources into a unified view within BigQuery, subsequently linking them to marketing and sales channels.
- Scalable Predictions: Writing predictions back to BigQuery for precise targeting and exporting triggers to various destination channels.
- Performance Analysis: Utilizing Flywheel's performance visualization tools for a comprehensive review of metrics from revenue to retention, while creating tailored data visualizations using Looker Studio.
- Audience Management: Launching and synchronizing audiences along with their personalization attributes across major platforms like Braze, Google Ads, and others.
Subsection 1.1.1 The Essential Elements for Scaling A.I.
Section 1.2 Key Considerations for A.I. Growth
During the recent EVERYDAY AI event, I was asked how to effectively scale A.I. My response? "Make the 'I' larger than the 'A'." To truly scale A.I. within enterprises, three fundamental conditions are necessary:
- Trust: This is the cornerstone of sound decision-making. True trust encompasses attributes like traceability, data completeness, and governance.
- Interaction: For A.I. to function efficiently at scale, it must support multimodal and contextual inputs and outputs. This means combining audio, images, and text across web, mobile, and app environments, while also retaining context.
- Action: Timely information and actionable insights must be integrated within specific domains. Rapid information dissemination and seamless transaction capabilities within applications enhance usability.
What are your thoughts? What aspects do you believe are missing? Join the discussion here.
Chapter 2 Public Sentiment on A.I.
In this chapter, we explore how people feel about A.I. and the evolving perceptions surrounding it. Participate in the conversation and see what others think.
The first video titled "The Truth Behind Artificial Intelligence" by Andrew Zeitler at TEDxStMaryCSSchool, dives deep into the realities of A.I. and its implications for our lives.
The second video, "The Truth About A.I. and Why You Should Learn It" from Computerphile, explains the significance of understanding A.I. in today's technological landscape.
Chapter 3 The Future of Generative A.I.
Generative A.I. has sparked discussions about both its potential and its concerns. Notably, reimagining a world free from violence and bias represents a transformative application of this technology. Insights from Jason Carmel at WPP's Wunderman Thompson shed light on this perspective. More details can be found here.