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Who’s winning the AI Patents race

🍏 Apple’s Open Source On-Device Models OpenELM

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AI PATENTS

🌐 AI Patent Trends: A Global Overview
Insights from Visual Capitalist

The latest findings from the Center for Security and Emerging Technology (CSET), highlighted in Stanford University's 2024 AI Index Report, detail significant trends in AI-related patent grants globally from 2010 to 2022.

Global AI Patent Trends:

  1. Dominance in China: Since 2013, China has led annually in the number of AI patents granted, surpassing the United States. By 2022, China had more AI patents than all other countries combined, showcasing a substantial increase in its AI research and development.


  2. Distribution and Sector Focus:

  • China: AI patenting in China is diverse, involving not just major tech companies like Tencent but also universities and government bodies. The country notably focuses on computer vision technologies, which are crucial for enabling computers to interpret visual information.

  • United States: In contrast, the U.S. AI patent landscape is primarily dominated by large tech corporations such as IBM, Microsoft, and Google, with a more evenly distributed focus across various AI research areas.

  1. Nature of AI Patents: AI patents typically encompass abstract concepts, including mathematical relationships and algorithms. This abstraction leads to varying interpretations and standards across different jurisdictions, affecting the landscape of global AI patenting.

This overview highlights the dynamic nature of AI patents, indicating shifting centers of technological leadership and innovation. 

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MICROSOFT PHI-3

🚀 Use Microsoft's Phi-3 Mini locally
Insights from Paul Couvert 

Microsoft has taken the lead in small AI models with the release of Phi-3 Mini, surpassing the Llama-3 8B model in nearly every benchmark. The Phi-3 Mini is not only more powerful but also accessible for local use as it's open-source.

How to Get Started with Phi-3 Mini:

  • Download LM Studio: Start by downloading LM Studio, a free, open-source software that facilitates the running of open-source AI models on your device. Visit LM Studio's website to download and install the version compatible with your operating system.

  • Acquire Phi-3 Mini: Once you have LM Studio, search for "Phi-3" on the homepage. Select the model named "Microsoft/Phi-3-mini-4k-instruct-gguf" and download the Q4 version, which is optimized for lighter and faster operation, albeit with a slight increase in loss compared to the "fp16" version.

  • Initiate Phi-3 Mini: To start using Phi-3 Mini, navigate to the chat tab in LM Studio, click on "New Chat," and ensure Phi-3 Mini is selected. You can then enter your prompts and begin interacting with the model.

Benefits of Using Phi-3 Mini:

  • Privacy and Security: Phi-3 Mini runs entirely offline on your local machine, ensuring that your data remains private and secure.

  • Cost-Effectiveness: Being open-source and free, it provides a cost-effective solution for those looking to utilize advanced AI capabilities without incurring high costs.

  • Ease of Use: The integration with LM Studio makes it straightforward to set up and start using, making advanced AI accessible to a broader audience.

This release marks a significant milestone in AI development, offering both enhanced performance and user-friendly access, making Phi-3 Mini a formidable tool for developers and AI enthusiasts alike.

ADVANCE AI

🍏 Apple Advances AI with Open Source On-Device Models: OpenELM
Insights from MacRumors

Apple has taken a significant step in the AI arena by introducing OpenELM, a suite of open-source large language models (LLMs) that operate directly on devices rather than relying on cloud processing. These models are now accessible through the Hugging Face Hub.

Key Highlights of OpenELM:

  1. Model Diversity and Efficiency:

  • OpenELM includes eight models, with half based on the CoreNet library for pre-training and the others instruction-tuned for specific tasks.

  • These models use a layer-wise scaling strategy that optimizes parameter allocation, achieving 2.36% higher accuracy than previous models like OLMo while requiring half the pre-training tokens.

  1. Open Source Accessibility: In an unusual move for the industry, Apple has released not only the model weights and inference code but also the complete training and evaluation frameworks. This unprecedented level of transparency is designed to support more robust and reliable AI research.

  1. Implications for the AI Community:

  • The availability of these resources allows for quicker, more verifiable advancements in natural language processing.

  • The open-source nature permits a broader analysis of data biases and ethical considerations, promoting the development of responsible AI.

  • By sharing these models publicly, Apple fosters innovation and attracts top talent, supporting its strategy to integrate advanced, privacy-centric AI features into future iOS updates. This strategy leverages on-device processing to enhance user privacy.

Apple's launch of OpenELM is poised to set new standards in the AI sector by improving accessibility, transparency, and collaboration, thereby significantly advancing on-device AI capabilities.

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HOT NEWS

🌨️ Snowflake Launches Flagship Generative AI Model

Source - Joan Cros/NurPhoto / Getty Images

Snowflake unveiled Arctic LLM, an enterprise-focused generative AI model, free under Apache 2.0 and optimized for tasks like SQL generation. Featuring a Mixture of Experts architecture with 480 billion parameters, it boasts high efficiency and cost-effective training. Initially available on Snowflake's Cortex platform, Arctic LLM will also be hosted on services like Hugging Face and Microsoft Azure. 

🤖 AI Can Predict Political Views from Facial Analysis  

A Stanford University study in American Psychologist reveals that AI and facial recognition can determine political orientation from expressionless faces, especially when incorporating demographic data. Distinct facial features correlated with political beliefs hint at deeper social and psychological impacts, raising concerns about biometric surveillance's role in political targeting.  

🤖 Zuckerberg says it will take Meta years to make money from generative AI

CEO Mark Zuckerberg discussed the widespread rollout of their AI assistant, used by tens of millions, against the backdrop of a $12 billion net income on $36.5 billion in revenue. He noted this AI initiative as a long-term project likely to take years, with plans to monetize through ads and premium services. Zuckerberg emphasized, "Building the leading AI will also be a larger undertaking than the other experiences we’ve added to our apps." 

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