Good morning, aspiring leaders of the next-gen! ☀️

🚀 Here’s what’s going on today in the AI space…

High school friends Christopher Fitzgerald and Nicholas Van Landschoot, fresh graduates, launched APIGen, an AI-driven startup that automates the creation of custom APIs from natural language prompts. They secured a $500K seed investment from Varana Capital. While Fitzgerald plans to attend Penn State, Van Landschoot will delay college to focus on their startup full-time. Their venture aims to simplify complex API development, targeting a diverse range of applications from web services to IoT devices. Their efforts caught the eye of investors after impressing with a prototype and a compelling pitch.

Apple and Meta are in discussions to collaborate on AI technology, possibly integrating Meta's AI capabilities into Apple's systems. These talks are not yet finalized and could still not proceed. This partnership could help Apple diversify its AI strategy beyond its current collaboration with OpenAI for Siri enhancements, aiming to implement AI-driven features like writing aids and custom emojis into its products. Apple plans to ensure user privacy by seeking permissions before sharing data with its AI partners. Additionally, due to EU regulations, Apple will restrict some features in European markets.

Hitachi is expanding its AI business by integrating Microsoft cloud services into its Lumada platform. This three-year partnership aims to meet the increasing demand for generative AI among corporations, offering enhanced capabilities through Microsoft's cloud solutions.

📔 #1 Insights Today on AI. Click the Links to Read

Kai-Fu Lee is chairman and CEO of Beijing-based Sinovation Ventures, a venture capital firm that manages $3 billion in Chinese high-tech assets.

⬆️ ️ Trends: How Businesses Implement AI

Handling angry customers is a significant challenge for contact centers, exacerbated by issues like short staffing and long wait times. Recent studies show a rise in customer frustration, with 43% of US customers admitting to yelling during serious issues in 2023, up from 35% in 2015.

AI-Powered Solutions To address this, contact centers are turning to AI-powered voice filters. These technologies modify the tone of customers' voices, transforming irate tones into calmer audio, thereby reducing stress for service agents.

Case Study: SoftBank Corp SoftBank Corp, a Japanese telecom giant, is testing AI software to soften the tone of angry customers. This initiative aims to lower stress levels for agents and improve customer retention. The technology blends voice processing and AI-enabled emotion recognition, fostering better communication and ensuring worker well-being. SoftBank plans to commercialize the solution if tests are successful.

Broader Adoption Many contact centers have adopted similar technologies over the past two years. AI applications that modify accents to neutral American English have been used to reduce bias and improve customer interactions. Companies using such technologies have seen agent turnover rates drop by as much as 50%.

Conclusion AI voice filters offer a promising solution to improve the work environment for contact center agents and enhance customer interactions. As voice remains the primary contact channel, these AI applications provide a significant advantage in managing customer service effectively.

🛸 Let’s Teleport in The Future

Kolmogorov–Arnold Networks (KAN) Are About To Change The AI World Forever

In AI, the Multi-Layer Perceptron (MLP) stands as the bedrock, its neural architecture shaping the landscape of countless applications. Yet, Kolmogorov–Arnold Networks (KAN) seek to disrupt this foundation by reimagining the very essence of the neurons working in neural networks.

Introduction:

In the ever-evolving landscape of machine learning, a recent research paper titled “KAN: Kolmogorov–Arnold Network” has sparked a wave of excitement among enthusiasts. This innovative approach challenges the conventional wisdom of Multi-Layer Perceptron (MLPs), offering a fresh perspective on neural network architectures.

What are Kolmogorov–Arnold Networks (KAN’s):

At the heart of this groundbreaking concept lies the Kolmogorov-Arnold representation theorem, a mathematical theory developed by Vladimir Arnold and Andrey Kolmogorov. This theorem asserts that complex multivariate functions can be decomposed into simpler one-dimensional functions, laying the foundation for KANs’ unique structure.

KANs diverge from traditional MLPs by replacing fixed activation functions with learnable functions (B-Splines), along the edges of the network.

This adaptive architecture allows KANs to effectively model complex functions while maintaining interpretability and reducing the number of parameters needed.

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⚡ ChatGPT Prompting

In reality, it’s super simple to become a ChatGPT maestro and learn how to use it properly.

And the best part? You don’t need to buy any overpriced course to do so, all you need is one prompt.

I will be sure to share this prompt with you in just a minute.

ChatGPT’s full potential without buying a course

The secret behind this technique is a prompt, and it’s a simple one.

Create a curated list of use cases for ChatGPT, each thoughtfully designed to align with my occupation. This list will serve as my personalized guide, enabling me to leverage ChatGPT’s capabilities in various aspects of my occupation. Organize this list into 10 distinct sections sorted by their relevance to my occupation. In each section, construct a table with columns for “Use Case” and “Example Request”. Each section will contain 5 use cases examples. The “Example Request” will be written in the form of a direct request to ChatGPT. Begin by asking me about my occupation, and based on it fill in the interests, goals, challenges I’m facing. It’s imperative that you follow the request for 10 sections and 5 use case examples in each section.

⚡ Hands-on: Supercharge With AI Tools

Work smarter, not harder!

Otter.ai

Otter AI introduces Meeting GenAI, a revolutionary AI meeting assistant that automates the process of taking meeting notes, generating summaries, and tracking action items. This tool is designed to enhance productivity by allowing team members to focus on the discussion without worrying about note-taking.

Steps to Use Otter AI:

1. Sign Up:

   • Visit the Otter AI website and sign up to start using the service for free.

2. Integrate with Your Meetings:

   • Connect Otter AI with your preferred meeting platforms like Zoom, Google Meet, or Microsoft Teams.

3. Use OtterPilot for Automated Notes:

   • Enable OtterPilot to join your meetings automatically and take detailed notes.

4. Review Meeting Summaries:

   • After the meeting, use Otter AI to access a condensed summary of the discussions.

5. Manage Action Items:

   • Check the action items that Otter AI has automatically captured and assigned from the meeting.

6. Interact with Otter AI Chat:

   • Use Otter AI Chat to ask questions and get answers based on your meeting content, or to generate related content such as emails and status updates.

7. Integrate with Workflow Tools:

   • Set up integrations with other tools like Slack, Salesforce, and HubSpot to automatically share notes and updates.

Otter AI's capabilities allow teams to streamline their meeting processes, ensuring that no critical information is missed and enhancing overall team coordination and productivity.

Visit otter.ai → https://otter.ai/

I hope you find these resources helpful. Let me know if you have any questions, if there's anything else I can do to assist you, or what you would like to learn more about in AI.

Have an amazing day!

No more playing catch-up. It's time to GET AHEAD!!! 🚀🚀🚀

🙌🏼

Elena

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