IBM Developer

Are you ready to make a real impact with your tech skills? Dive into Environmental Intelligence video playlist—your go-to resource for building applications that predict, respond to, and mitigate environmental risks. From extreme weather forecasting to sustainability insights, these APIs unlock the power to create solutions that matter. Check it out here: https://lnkd.in/dcWJ-RDJ Let’s code for a more sustainable future. #TechForGood #EnvironmentalIntelligence #Sustainability #AI

Congratulations to the 2024 @CallforCode Global Challenge winning teams! 🌎🏆 Discover how generative #AI solutions with #watsonx are driving #TechforGood—improving access to education, income, and essentials like clothing for communities in need: https://ibm.co/3ZN9d3O

In today’s data-driven world, efficiently managing and automating AI workflows is crucial. IBM Watson Studio, a key component of IBM's advanced AI and data platform, offers a robust suite of tools designed to streamline these processes. Check this tutorial to create and manage pipelines in Watson Studio, with a focus on parallel processing, seamless integration with IBM Cloud Object Storage (COS), and prompt automation. Explore a real-world example of processing Java files for code explanation and summarization, demonstrating how Watson Studio can significantly enhance your machine learning workflows: https://ibm.co/49rxkbz

Forests are more than just trees—they are vital ecosystems that protect biodiversity and support livelihoods worldwide. But how do we truly understand and protect these complex systems? In our latest blog, we dive into how Environmental Intelligence APIs are transforming forest analysis. From tracking deforestation and carbon sequestration to monitoring tree health and adapting to climate impacts, these tools provide insights for industries such as agriculture, supply chain, and public sector forestry. Read more about how Earth intelligence is shaping forest analysis: https://ibm.co/3ZHEXGz - - - - - - - - #EarthIntelligence #ForestAnalysis #Sustainability #TechForGood

Check out the updated InstructLab tutorial by Ahmed Azraq, now featuring the latest version of InstructLab 0.21! This new release boasts exciting changes, including System Profile Auto-Detection, enhanced memory optimization, and using IBM Granite as the default chat model for inference. Don’t miss out on exploring these improvements and more in the updated tutorial: https://ibm.co/3BbIUuI

Check out this tutorial authored by senior Generative AI engineer Bhavishya Pandit on how you can use LLMs to generate pre-processed, high-quality data for classic ML models: https://ibm.co/3Vjvt2u Through code examples and practical guidance, learn how LLM-driven data generation can enhance ML model performance by reducing overfitting risks, preserving data quality, and expanding the capabilities of classic ML applications. #AI #ML #GenAI

Start your Retrieval Augmented Generation (RAG) journey now with our newly launched RAG Cookbook: https://ibm.co/3Omktxv This Cookbook will help you harness latest tools, ranging from IBM’s watsonx.ai to open-source frameworks like LangChain and LlamaIndex. It contains an exhaustive list of best practices, considerations, and tips for building RAG solutions tailored to a variety of business applications. A comprehensive guide that has an end-to-end coverage of the entire RAG pipeline for architects, data engineers, developers, and 'hands on' technical folks with practical advice on implementing and optimizing RAG solutions for specific use cases. ----- #AI #RAG #developers

The world of AI is advancing at lightning speed, offering unprecedented opportunities for innovation in environmental applications. But let’s be real—working in this space isn’t without its challenges! From navigating geospatial data complexities to handling petabyte-scale datasets and identifying the most reliable environmental APIs, developers in this field tackle unique hurdles daily. In a recent blog post, we break down the Top 5 Challenges for Environmental Application Developers and explore how IBM Environmental Intelligence APIs can help you build climate-resilient solutions faster and more efficiently. Check out the full blog here: https://ibm.co/4eKBCMa Let’s build solutions that not only keeps pace with #AI but also protects our planet! #EnvironmentalTech #Sustainability

It is crucial yet tedious task to compare outputs from multiple LLMs for selecting a model that is tailored to your specific need. A model that maximize performance, minimize biases, and optimize costs. It can be tricky to choose between open-source models like Llama, Granite, and Mistral. To facilitate this process, Senior GenAI Engineer at IBM, Bhavishya Pandit, has authored this tutorial to provide solutions for a systematic evaluation and the code necessary to compare various LLMs, highlighting the benefits of efficient model selection and optimized workflows: https://ibm.co/4hs2seM #AI #LLM #OpenSource

Large Language Models (LLMs) have immense potential, but they come with challenges like the need for high-quality training data, specialized skills, and extensive computing resources. Forking and retraining these models can be time-consuming and costly. That’s where InstructLab steps in! In this tutorial, CSM Solutions Architect at IBM, Ahmed Azraq explains how to accomplish the same goal of fine-tuning open-source LLMs using InstructLab UI: https://ibm.co/4fmmR2V The InstructLab User Interface (UI) allows you to easily contribute knowledge or skills to the InstructLab taxonomy repository without worrying about YAML structure, the different validation rules, or the GitHub pull request (PR) process.