SLM

OpenAI and Retro Biosciences have unveiled GPT-4b micro, an AI model designed to engineer proteins for longevity science. This partnership focuses on re-engineering Yamanaka factors, which hold the potential to slow aging, regenerate organs, and add 10 healthy years to human life.
The article discusses the potential of Small, Specialized, and Symbolic Learning Machines (SLMs) in Behavioral Intelligence (BI) Artificial Intelligence (AI) decision engines. Unlike traditional machine learning models, SLMs use symbolic reasoning to make decisions and provide clear explanations for their predictions. This transparency is crucial in sensitive areas where decision-making explanations are essential. The article explores various applications of SLMs in BI AI decision engines and concludes that SLMs offer a promising pathway towards more energy-efficient and sustainable AI, reducing computational demands and enabling edge deployment while providing comparable performance for specific tasks.
SLMs present an exciting opportunity for creating a more energy-efficient and sustainable approach to AI. They lower computational requirements, facilitate edge deployment, and maintain similar performance levels for certain tasks, which can help lessen the environmental footprint of AI while still providing essential advantages. Additionally, prioritizing data privacy and responsible data management can greatly reduce energy use in data centers. By encouraging ethical data practices, empowering users, and promoting energy efficiency through SLMs, we can pave the way for a greener and more privacy-aware digital landscape.

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Explore the collaboration between Purdue Research Foundation, Purdue University, Ericsson, and Saab at the Aviation Innovation Hub. Discover how private 5G networks, real-time analytics, and sustainable innovations are shaping the "Airport of the Future" for a smarter, safer, and greener aviation industry....
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Explore how Generative AI is transforming telecom infrastructure by solving critical industry challenges like massive data management, network optimization, and personalized customer experiences. This whitepaper offers in-depth insights into AI and Gen AI's role in boosting operational efficiency while ensuring security and regulatory compliance. Telecom operators can harness these AI-driven...
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This article explores the deployment of 5G NR Transparent Non-Terrestrial Networks (NTNs), detailing the architecture's advantages and challenges. It highlights how this "bent-pipe" NTN approach integrates ground-based gNodeB components with NGSO satellite constellations to expand global connectivity. Key challenges like moving beam management, interference mitigation, and latency are discussed, underscoring...

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