In this category, we'll explore the vast and fascinating world of Artificial Intelligence (AI). From understanding the fundamentals of AI to discussing cutting-edge research and ethical considerations, this is your go-to place for engaging conversations, learning resources, and insightful discussions about all things AI. What you can expect: 🧠 AI Fundamentals: Dive into the basics of AI, its history, and key concepts. 🌐 Latest Trends: Stay updated on the most recent developments and breakthroughs in AI. 💬 Ethical Considerations: Discuss the ethical implications and societal impacts of AI. 🛠️ Tools and Technologies: Explore AI tools, platforms, and technologies shaping the future. 👥 Collaboration: Connect with fellow AI enthusiasts, share projects, and seek advice. Example Post Ideas: AI Fundamentals: "What are the key differences between Artificial Intelligence, Machine Learning, and Deep Learning?" Latest Trends: "Discussing the Impact of Large Language Models on AI Research and Applications." Ethical Considerations: "Exploring the Ethics of AI in Decision-Making Systems." Tools and Technologies: "Hands-On with TensorFlow: A Beginner's Guide to Building AI Models." Collaboration: "Seeking Collaborators for an AI-Driven Healthcare Diagnostics Project." Industry Insights: "How AI is Revolutionizing the Finance Industry: Use Cases and Challenges." Join us as we navigate the exciting and ever-evolving landscape of Artificial Intelligence. Together, we can learn, innovate, and shape the future of AI! 🚀

FPGAs are the bridge between ML developers and hardware-based AI chip deployment. Intel’s offerings like the OpenVINO™ Toolkit and Intel FPGA AI Suite are tools that abstract complexities, making FPGAs accessible to beginners and flexible enough for tenured engineers. You can find my latest assessment and peer-reviewed findings of this emerging trend we should all get uniquely acquainted with sooner than later. The world's economy propensity is heading in a very specific direction and the level of human abstraction we call our employment landscape is soon to change. Stay in the know and follow my newsletter at Hashnode @Omie: Mean To Epsilon

BLOG - Mean to Epsilon Welcome to Mean to Epsilon—where understanding the humble average quietly unlocks the door to machine learning, artificial intelligence, and beyond. Every remarkable journey in data science begins with the simplest of concepts. At first glance, the 'average' might seem too ordinary to lead anywhere groundbreaking. Yet, beneath this simplicity lies the foundational essence of algorithms that power today's intelligent systems. Sign-up for the newsletter to stay abreast of this ever-changing landscape.

TL;DR A RAND Corporation study of industry AI teams reported that rigid Scrum routines can be a “poor fit for AI projects,” since machine learning work often requires an initial research or data exploration phase of unpredictable length. Forcing exploratory AI development into uniform sprint boxes causes inefficiency. This mismatch can lead to frustration and Agile ceremonies that feel like overhead in AI initiatives. The key issue is that AI development involves iterative data tuning and model experimentation that don’t always deliver tangible increments every sprint. Without adaptation, traditional Agile metrics (like velocity or burndown) may fail to capture progress, and teams risk stakeholder misalignment. You can deep-dive into this emerging trend as we seek to adapt and iterate over this rapidly changing employment landscape in my newly created blog where I keep things candid, clear, accurate and without salesmanship. Enjoy! Mean to Epsilon

-- The Intersection of Machine Learning and Herbal Medicine -- Herbal medicines (HMs) have long been associated with holistic healing, sleep enhancement, and inflammation reduction. Claims that aloe vera hydrates better than water or that certain herbal teas induce sleep are widely popular—but how do we separate scientific fact from myth? With advancements in machine learning (ML) and Convolutional Neural Networks (and respective Deep Neural Networks such as MLPs, RNNs, etc.) and mass spectrometry imaging (MSI), we can now analyze herbal medicines at a molecular level, mapping their active compounds and pharmacological effects. In this blog (don't worry, we are not here to make you feel guilty for drinking coffee), we’ll explore how modern technology is revolutionizing herbal medicine, examining how scientific methods like MSI, SIMS, MALDI, and DESI are used to validate traditional remedies. Herbal medicine has been practiced for centuries, often supported by anecdotal evidence; however, elucidating the mechanisms underlying its efficacy remains challenging. Unlike synthetic pharmaceuticals, in which active ingredients are isolated and systematically analyzed, herbal medicines consist of complex mixtures of bioactive compounds that may exhibit synergistic effects or potential interactions. MSI allows scientists to map the chemical composition of herbal medicines without destroying their structure, offering insights into the spatial distribution of bioactive metabolites (Zhang et al., 2024). For example, if a herbal tea is claimed to help with sleep, we can reveal whether its compounds interact with neurotransmitters like GABA or serotonin, which regulate sleep cycles and hormone efficacy. These MSI techniques use different ionization methods to analyze herbal compounds. ⛔ Hold on now, do not put away your Melatonin pills just yet 💊. Up next we break down the three most common experimental methods used in herbal medicine research: A. Secondary Ion Mass Spectrometry (SIMS)