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AI_Distilled #31: Evolving Boundaries and Opportunities

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  • 840 min read
  • 2024-01-08 11:33:05

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Dive deeper into the world of AI innovation and stay ahead of the AI curve! Subscribe to our AI_Distilled newsletter for the latest insights. Don't miss out – sign up today!

👋 Hello ,

🎉 Joyous 2024! Wishing you a year as delightful as your dreams!  

Dive into the new year with our outstanding edition, filled with essential features to boost your AI practice. 

“The speed at which people will be able to come up with an idea, to test the idea, to make something, it’s going to be so accelerated…You don’t need to have a degree in computer science to do that.” Google Plans Potential Layoffs Amidst AI Integration in Ad Sales 

Generative AI's Impact on Mental Health Counseling 

AI in Finance: 

AI-SaaS Integration Revolutionizes E-commerce Analytics 

Here are some handpicked GPT and LLM resources, tutorials, and secret knowledge that’ll come in handy for your next project: 

Creating an Open Source LLM Recommender System: Mastering Prompt Iteration and Optimization 

Looking for hands-on tips and strategies straight from the developer community? We’ve got you covered: 

Unlocking Your MacBook's AI Potential: Running 70B LLM Models Without Quantization 

Check out our curated list of smoking hot GitHub repositories: 

ml-explore/mlx 

 

📥 Feedback on the Weekly Edition

Q: How can we foster effective collaboration between humans and AI systems, ensuring that AI complements human skills and enhances productivity without causing job displacement or widening societal gaps?

Share your valued opinions discreetly! Your insights could shine in our next issue for the 39K-strong AI community. Join the conversation! 🗨️✨ 

As a big thanks, get our bestselling "Vidhu Jain for their valuable contribution to this week’s newsletter content!  

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Cheers,  

Merlyn Shelley  

Editor-in-Chief, Packt 

 

official blog here

here

AI in Healthcare: 

here. 

AI Safeguards Supply Chains Amidst Holiday Challenges: Businesses face unique challenges in managing complex supply chains amid the holiday season, from counterfeit airplane parts to recalls affecting festive foods. The reliance on suppliers underscores the need for transparency and visibility to prevent disruptions caused by supplier misconduct. Leveraging AI in contracts offers a solution, allowing businesses to streamline due diligence, enhance visibility, conduct predictive analytics, and align with environmental, social, and governance (ESG) regulations. AI-powered contracts emerge as vital tools to proactively address supply chain challenges and ensure customer trust during the holiday season and beyond. 

Architectural Patterns and Techniques for Developing IoT Solutions written by Read through the Chapter 1 unlocked here... 

 

🌟 Secret Knowledge: AI/LLM Resources

Creating an Open Source LLM Recommender System: Mastering Prompt Iteration and Optimization: Open Recommender is an open-source YouTube video recommendation system adept at tailoring content to your interests based on Twitter feed analysis. Discover its data pipeline, utilizing GPT-4, and the transition towards cost-effective open-source models using OpenPipe. Explore the challenges faced during prompt iteration, with a focus on better prompt engineering tools, including the introduction of a TypeScript library, Prompt Iteration Assistant.  

 

 

🔛 Masterclass: AI/LLM Tutorials

Unlocking Your MacBook's AI Potential: Running 70B LLM Models Without Quantization: Discover how to unleash the hidden AI power of your 8GB MacBook as this post explores the latest 2.8 version of AirLLM. Without the need for quantization or model compression, an ordinary MacBook can now efficiently run top-tier 70 billion parameter models. Explore the MacBook's AI capabilities, understanding Apple's role in AI evolution through its M1, M2, and M3 series GPUs, which offer competitive performance in the era of generative AI. Gain insights into GPU capabilities, memory advantages, and the open-source MLX platform.

 

🚀 HackHub: Trending AI Tools

ml-explore/mlx: Array framework for machine learning on Apple silicon by Apple's ML research, offering familiar Python and C++ APIs closely aligned with NumPy and PyTorch. 

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