Blockchain App Factory’s Post

Building a single, hardcoded AI pipeline? That’s a recipe for failure. After a decade in AI/ML development, I’ve seen countless examples of teams struggling to adapt because they rely on one rigid pipeline. In my latest article, I dive into why this approach holds teams back—and how to overcome it with a paradigm shift: 100s of pipelines, all powered by configuration functions with Hypster. This approach transforms your codebase into a flexible, dynamic system where large-scale experimentation and optimization become seamless. The result? Iteration speeds that are orders of magnitude faster, and your AI pipelines are built to evolve with your business needs and technological advances. Curious? Check out the article: https://lnkd.in/dn-9BAxk

🚀 Simplifying AI Model Customization with MultiLoRA on ONNX Runtime 🎯 AI practitioners, are you looking to fine-tune multiple tasks on a single model while optimizing performance and reducing resource consumption? The latest update on ONNX Runtime introduces MultiLoRA (Low-Rank Adapters)—an innovative feature designed to streamline model customization across diverse applications. 🔑 Key highlights from the blog: 💡 Enable simultaneous fine-tuning for multiple tasks on the same base model. ⚡ Benefit from optimized inference performance and minimized memory overhead. 🌍 Empower customization for various industries, from healthcare to customer service. MultiLoRA is a game-changer for developers and researchers leveraging ONNX Runtime, making it easier to adapt models to specific needs without the heavy lifting of traditional fine-tuning. 👉 Dive into the details and let MultiLoRA with ORT transform your AI workflows: https://lnkd.in/gpUSyyBS Let’s shape the future of efficient AI customization, together! 💻✨ #AI #ONNXRuntime #MachineLearning #MultiLoRA #DeepLearning #ModelOptimization #LoraAdapters

Why prompt engineering is one of the most valuable skills today - VentureBeat: Prompt engineering is shaping how we interact with and benefit from AI. Here's how to get prompt engineering right.

🚀🌟 Exciting News for AI Developers! Introducing Claude Evaluate! 🌟🚀 If you're into AI development, automating prompt engineering just got easier and more efficient! Anthropic's Claude has unveiled new features that could revolutionize your AI applications. 🔍 What’s New? Claude has now included a feature called Claude Evaluate. This new tool allows developers to: 🔹 Generate, Test, and Refine Prompts: The playground provides quick feedback, significantly speeding up the process of developing effective AI prompts. 🔹 Automate Prompt Engineering: It offers tools to automatically improve AI application development, saving time and enhancing efficiency. 🔹 Personalized Recommendations: Tailors suggestions, making your prompts more effective and contextually accurate. 🔹 Enhanced Collaboration: Facilitates better teamwork, allowing multiple developers to work on prompt engineering simultaneously and share insights effortlessly. 💡 Why It Matters Prompt engineering can be a cumbersome task, often involving lots of trial and error. With Claude’s new capabilities, you can streamline this process, making it more efficient and cost-effective. 🌟 Real-World Impact These features can be particularly powerful for teams working on complex AI applications that require highly optimized and effective prompt input. From enhancing customer service bots to fine-tuning large language models, the possibilities are vast! 📈 Getting Started: To explore these new functionalities, visit the official announcement on TechCrunch: https://lnkd.in/ecC35P7r. #AI #PromptEngineering #Innovation #Anthropic #ClaudeAI #TechNews #AICommunity #ArtificialIntelligence #DeveloperTools #AIApplications

Forbes article by Paul Smith-Goodson for Moor Insights & Strategy "InstructLAB brings a unique set of advantages to developer- and community-driven, open-source LLM development..making future methods far more accessible, allowing models to evolve faster and solve a broader range of problems, which benefits everyone in the AI ecosystem." Red Hat and IBM Research helping solve real world problems, using affordable and sustainable IT resources, outperforming models which cost many millions of dollars more. https://lnkd.in/d93EpcBy

🚀 Delving Deep into Prompt Engineering! 🧠 In this comprehensive exploration, we'll unravel the intricacies of this pivotal AI discipline. From understanding its diverse types to uncovering real-world examples and implementing best practices. We'll equip ourselves with the tools to unlock AI's full potential. Join the conversation and discover how Prompt Engineering is shaping the future of AI innovation! #PromptEngineering #AI #Innovation #BestPractices https://lnkd.in/df8zHWFD

Inspired by nature and applied in AI and Automation a not completely new padigram but technology has never been closer to realize this vision. https://lnkd.in/eyMaM4xp

Productivity software tends to buttonify AI into small, discrete tasks because most models are currently incapable of building and following complex plans as independent agents. Project builders are forced to bind models to tasks that are small and easily definable because they aren't able to handle knowledge-labor workflows in their totality. Simply replacing small portions of a workflow with a button isn't enough to meaningfully change the work itself. The buttonification of AI is a reminder that we are still in the 'training wheels' phase of the supposed AI revolution. #ai #technology https://lnkd.in/gBym9xwH

🚀 🚀 𝗠𝗮𝘀𝘁𝗲𝗿 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗢𝘂𝗿 𝗟𝗮𝘁𝗲𝘀𝘁 𝗕𝗹𝗼𝗴! 🌟 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴? Explore the fundamentals and importance. 𝗪𝗵𝘆 𝗜𝘁’𝘀 𝗖𝗿𝘂𝗰𝗶𝗮𝗹: Understand its role in effective AI interactions. 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 & 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀: Learn key strategies and techniques. 𝗣𝗿𝗼𝘃𝗲𝗻 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀: Get hands-on with actionable tips. 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗘𝘅𝗮𝗺𝗽𝗹𝗲𝘀: See real-world applications in action. 🖇️https://lnkd.in/gz6Bws6p #PromptEngineering #AI #GenerativeAI #TechTrends #BlogPost #MachineLearning #anishs #cricketai

Very insightful study from McKinsey. It compiled the impact of generative AI on various industries, going into detail and listing each business function. It explains how the automation of work activities and augmentation of human capabilities can contribute to economic benefits. Here are a few pointers on how it benefits software development: - Significantly shorter development cycles through code generation and enhanced pair programming & collaboration. This includes generating code from natural language, which reduces the time needed to write boilerplate code. - Reduced costs in refactoring and handling technical debt. Considerable investments have been made in transforming legacy systems, so AI could significantly reduce the costs associated with managing tech debt. - Developers will save time and most importantly cognitive effort in finding the right information from knowledge bases or extensive technical documentation, and in understanding complex code bases. Very much looking forward to more exciting tools and ideas around generative AI that can be integrated into the development workflows.