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How to implement your design system in a Flutter app (1/2) (medium.com)

Flutter Design Systems Mobile App Development UI/UX Design

The article addresses the fundamentals of implementing a design system in Flutter apps, emphasizing the limitations of default theming and the benefits of creating a dedicated, reusable package. It discusses organizing the design system into atomic, molecular, and cellular levels and the significance of theme extensions for colors, fonts, and dimensions.
Main Points
- Define a design systemA design system includes reusable components, style guides, and standards for consistency.
- Divide system into levelsThe system is usually divided into atomic, molecular, and cellular levels for better organization.
- Implement custom theming using design systemCustom theming can assist in overcoming the limitations of default Flutter theming.
- Use dedicated packages and naming conventionsDedicated packages and naming conventions can simplify the design system's implementation across apps.
- Utilize theme extensions for customizationIncorporate theme extensions for colors, fonts, and dimensions for a more efficient and customizable design approach.
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Why is shuffle support needed? (medium.com)

shuffle execution plan hash table memory allocation performance improvement scalability

The article discusses the necessity of shuffle support in database operations, highlighting its benefits in preventing memory allocation failures, enhancing scalability, and improving performance. It emphasizes the role of shuffle in redistributing data for more efficient processing.
Main Points
- Importance of Shuffle SupportShuffle support is crucial for addressing the challenges of memory allocation failure, enhancing the horizontal scalability of compute nodes, and improving overall performance by breaking down large hash tables into smaller, more manageable pieces.
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Look ma, no WiFi! Gemma on Android and iPhone and more local LLM updates from MLC (medium.com)

The article introduces Google Gemma 2B, a lightweight 2B parameter version capable of running on Android and iPhone without the need for WiFi. It is a significant update from MLC aimed at enhancing mobile device capabilities for running local LLMs. The adoption of Gemma 2B by the MLC community and their success in running it locally showcases the potential of lightweight LLMs in mobile computing. The application of LLMs on the edge addresses important issues like latency and privacy, marking a shift towards more efficient and secure model deployments.
Main Points
- Gemma 2B running on Android and iPhoneGoogle Gemma 2B, a lightweight 2B parameter version of Gemma, can now run on mobile devices including Android and iPhone. The model outputs 20 tokens/sec and does not require WiFi for operation. It highlights the advancement in lightweight, local LLMs suitable for mobile platforms.
- Gemma 2B local implementationThe MLC community successfully got Gemma 2B running locally in under a day using the new MLC SLM compilation flow, demonstrating the rapid adoption and integration capabilities of open source LLM projects.
- Benefits of running models on the edgeThe concept of running models on the edge, combined with larger models in the cloud, addresses key issues such as latency, compute pressure, and privacy concerns, highlighting the benefits of hybrid cloud/local setups.
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Discover the power of LLM based SQL Agent for SAP HANA queries (medium.com)

The article presents a detailed guide on leveraging LLM based SQL Agents for automating complex SQL queries within SAP HANA environments. It covers the journey from conceptualization to implementation, including necessary code snippets and an example of creating a FastAPI application.
Main Points
- LLM based SQL Agent potential for SAP HANAExploring the potential and applications of LLM based SQL Agents for enhancing business intelligence operations within SAP HANA environments.
- Integration of langchain library componentsDemonstration of integrating langchain library components to automate and simplify SQL query generation and execution.
- FastAPI application setup exampleProvision of a practical example for setting up a FastAPI application to interface with the SQL database and LLM based agents.
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Data Analysis with Elixir (medium.com)

The article introduces Elixir’s Explorer library as a robust tool for data analysis, capable of cleaning, structuring, and analyzing data efficiently. It emphasizes the integration of Explorer with Livebook for an enhanced, interactive experience in data analysis. The utility of Smart Cells for automating data manipulation tasks is also highlighted, showcasing the alternative advantages of Elixir in the realm of data science.
Main Points
- Data cleaning with ElixirExplained the process of cleaning data using Elixir's Explorer library, including filling missing values and identifying outliers.
- Data VisualizationDiscussed how data visualization is enhanced with the kino_explorer library and Smart Cells feature in Livebook.
- Automating data analysis with Smart CellsHighlighted how Smart Cells in Livebook can automate advanced data manipulation tasks, making it easier for users.
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