Understanding the Target Audience DeepCode is designed for a diverse group of users, primarily researchers, software engineers, and academic professionals. These individuals often face significant challenges when translating complex research into functional software. Common pain points include: Time-consuming manual coding processes from research papers. Lack of reproducibility in research implementations. Difficulty in quickly prototyping software…

South Korea is emerging as a significant player in the field of large language models (LLMs), thanks to a combination of government support, corporate innovation, and academic research. This strategic focus not only aims to reduce reliance on foreign technologies but also enhances data privacy and fosters advancements in critical sectors such as healthcare, education,…

Introduction to LFM2-VL Liquid AI has made a significant leap in the field of artificial intelligence with the release of LFM2-VL, a new family of vision-language foundation models. These models are tailored for low-latency and device-aware deployment, making them suitable for various devices such as smartphones, laptops, and wearables. With two variants, LFM2-VL-450M and LFM2-VL-1.6B,…

Introduction to ZenFlow In the world of large language model (LLM) training, efficiency is key. The introduction of ZenFlow by the DeepSpeed team is set to revolutionize the way we handle GPU resources. Traditionally, training models has come with various bottlenecks, especially when it comes to CPU-induced stalls. For example, fine-tuning a model like Llama…

Deep Learning Framework Showdown: PyTorch vs TensorFlow in 2025 The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while maintaining distinct strengths. This article explores the latest patterns from a comprehensive survey paper from Alfaisal University,…

Introduction to Google AI’s New Agents Google Cloud has recently introduced five innovative AI agents aimed at enhancing developer workflows. These tools are designed to reduce manual tasks, speed up data analysis, and simplify automation processes. Each agent targets specific challenges faced by developers, from managing data pipelines to improving GitHub repository handling. Let’s delve…

Understanding the Target Audience The target audience for this playbook includes architects, developers, and business managers involved in AI integrations. These professionals often face challenges such as: Difficulty managing and maintaining custom integrations High technical debt due to brittle code Challenges in achieving interoperability between systems The need for scalable, flexible solutions that reduce integration…

Understanding the COPILOT Function in Excel Excel has taken a major leap forward with the introduction of the COPILOT function. This feature allows users to interact with their data using natural language, making complex tasks simpler and more intuitive. By leveraging artificial intelligence, COPILOT can analyze, summarize, and even generate new data based on user…

Understanding Signal and Noise in LLM Evaluation What is Signal? Signal measures how well a benchmark can differentiate between better and worse models. High signal implies distinct performances across different models, allowing for clear rankings. Conversely, a low signal results in closely clustered scores, making it hard to determine which model excels. What is Noise?…

Understanding the Target Audience The tutorial on building a self-hosted LLM workflow with Ollama, REST API, and Gradio Chat Interface is tailored for a diverse audience. Key groups include: Data Scientists and AI Practitioners: These individuals are eager to implement machine learning models in real-world applications. Software Developers: Developers looking to integrate AI capabilities into…