Here's what caught my eye in the world of AI this week:

1. Guidelines for AI and Shared Prosperity

   A chock full of Goodness site - rich in “Bringing diverse voices together across global sectors, disciplines, and demographics so developments in AI advance positive outcomes for people and society.”

Check out their informative and detailed guide - Guidelines for AI and Shared Prosperity - Tools for improving AI’s impact on jobs.

Quote of the week

2. I'd frame Marc Benioff's insight this way:

In the AI revolution, data isn't just the new oil - it's the very air our digital ecosystems breathe. While flashy UI and cutting-edge models grab headlines, savvy leaders recognize that the true competitive edge lies in the depth and quality of their data assets.

This isn't just about hoarding information. It's about curating a rich, nuanced dataset that captures the essence of your business, your customers, and your market. Think of it as creating a digital twin of your entire operation, one that AI can learn from and utilize to drive unprecedented insights and efficiencies.

Yes, synthetic data has its place, especially for privacy-sensitive applications or to augment sparse datasets. But there's no substitute for the complexity and authenticity of real-world, organically collected data. It's this data that allows AI to truly understand the subtleties of your business context.

The companies that will thrive in the AI age aren't necessarily those with the biggest tech budgets, but those who become masters of their own data domains. They'll be the ones who can seamlessly integrate data collection into every facet of their operations, turning each customer interaction, each product cycle, and each market shift into valuable fuel for their AI engines.

In essence, Benioff is urging us to shift our focus. Don't just chase after the latest AI model - build the data infrastructure that will allow any AI to perform at its peak within your unique business ecosystem. That's where the real, lasting value in AI will be found.

“The future's fortune lies in our data” - Shakespeare, if he were living in the 21st century.

3. How should you monetize your AI features? 

Lenny's newsletter - Guest author Palle Broe delivers an absolute masterclass on AI monetization strategies - it's practically an MBA course condensed into a single article.

Fair warning: there's a paywall, but the content is so valuable that you might find yourself reaching for your wallet. For anyone serious about capitalizing on AI's potential, this piece is nothing short of essential reading.

The insights shared here could be the difference between merely dabbling in AI and building a robust, profitable AI-driven business model. If you're looking to turn AI capabilities into real revenue, this article provides a roadmap that's worth its weight in gold.

4. There's a new magic 8 ball, and it’s powered by GPT-4o 🎱

Very cool explainer video from Allie K. Miller:

The Center for AI Safety released a new forecast bot called FiveThirtyNine, and the creators allege it outperforms even experienced human forecasters. The bot has a multi-step process: query > research > fact extraction > arguments and strength scoring > estimation and reasoning > reflection > final prediction.

5. AI is confusing — here’s your cheat sheet

   
   Artificial intelligence is a rapidly evolving field filled with complex jargon, making it difficult to keep track of key concepts like AGI, machine learning, and LLMs. This article provides a simplified glossary to help readers navigate the most common AI terms and their significance in the tech landscape.

Author - Jay Peters

6. Friday Funnies 🤣 .

Data has known the deal for a long time!

7. Is your Use of AI Violating the Law? An Overview of the Current Legal Landscape

Whether you're developing, licensing, or using AI, staying informed on the evolving legal landscape is key to avoiding pitfalls. 🤓 This article, "Is Your Use of AI Violating the Law? An Overview of the Current Legal Landscape," published in NYU's Journal of Legislation and Public Policy, offers a detailed guide to help you navigate the current regulatory landscape and ensure your AI strategy is legally sound in the U.S. and globally.

1. Is your Use of AI Violating the Law? An Overview of the Current Legal Landscape

2. AI and the law: what you need to know

Thank you, Irene Liu, for introducing me to Equal AI through your insightful post. This organization's mission to promote responsible AI development and address bias in AI systems is crucial in today's rapidly evolving technological landscape.

Transforming an organization - hard, Implementing AI in the organization - Harder. Doing both IMPOSSIBLE. Until now! AI Quick Bytes will help you navigate through it all. The key is adaptability.

Step 1 - Take Action In Your Career!

Dream of being a Strategic AI Leader? Will outline the roadmap for your success. You will learn about the different stages of the AI maturity model, the AI success life cycle, and the AI business roadmap. Join us for our upcoming FREE virtual workshop, “Exclusive AI Leadership Insights - Creating a Roadmap For AI Success,” on September 27th from 8 AM to 9 AM PST.

What’s stopping you?

8. Salesforce’s New AI Strategy Acknowledges That AI Will Take Jobs

Salesforce's bold move into outcome-based AI pricing signals a seismic shift in the SaaS landscape. By charging $2 per AI-driven conversation, they're not just monetizing features - they're selling tangible results. This model aligns perfectly with what businesses truly seek: measurable returns on their AI investments. However, the real challenge lies in maintaining simplicity and transparency as these AI-driven outcomes grow increasingly complex. The key to widespread adoption will be striking a delicate balance between sophisticated AI capabilities and straightforward, verifiable success metrics.

Executive Summary 

Salesforce is shifting its AI strategy by introducing fully autonomous AI tools, aiming to replace human labor in tasks like customer service. The new pricing model charges per AI-driven interaction, helping Salesforce adapt to potential job losses and changing workforce dynamics due to AI adoption.

Key Takeaways 

1. AI-Driven Automation: 

- Salesforce’s new AI tools, called "agents," can operate without human supervision, handling complex tasks like customer service and scheduling.

- This shift moves beyond earlier AI models like copilots that required human assistance for execution.

2. Outcome-Based Pricing Model: 

- Salesforce will charge $2 per AI-driven conversation, insulating itself from potential revenue losses as companies downsize due to AI replacing human workers.

- This approach reflects a broader shift from traditional per-user subscription models.

3. Impact on Workforce Efficiency: 

- Salesforce acknowledges that its AI tools will reduce the need for human workers, allowing businesses to manage peak demand without hiring additional staff.

- The company expects a long-term reduction in human labor needs, particularly in sectors like customer service.

Until next time, take it one bit at a time!

Rob

P.S. - In the Bay Area on 10/9? Join us:

The Future of AI in the Enterprise - Project, Governance and Beyond

Unlock the Potential of AI: Join Us - Complimentary Admission, Food and Drinks!

• Discover the Future: Engage with AI innovators as they share their journey, unveiling breakthroughs and practical wisdom.

• Build Connections: Make friendships and forge new business relationships in a community passionate about technology's potential.

  Join us for an unforgettable night of learning, networking, and reconnection. Your presence will contribute to a vibrant community eager to explore the endless possibilities of AI.