Key insights 🧠 Developing an AI-based business data analyst using open AI function calling can potentially challenge the role of traditional data analysts. 🧩 The AI-based business data analyst was able to load and inspect the CSV data, generate Python code, and create a chart, showcasing its potential in automating data analysis tasks. 🤷‍ "Overall, I'm not very concerned" – Despite the overestimation, the speaker doesn't seem too worried, indicating a potential disagreement or controversy regarding the significance of the AI's accuracy. 🔄 The use of AI-based tools like the code interpreter raises controversy around the potential replacement of human data analysts. 💡 The potential functions of the chatbot can range from filtering and aggregating data to generating visualizations and even running SQL queries, making it a versatile tool for data analysis. 💡 The AI model can recommend specific functions, such as the plot time series function with the metric sales, to visualize data and provide valuable insights to the user. 💡 Using function calling to develop custom agents that can act as data analysts is a promising approach with several advantages, including full control over generated plots. 🚧 Implementing guardrails and integration tests can help ensure the reliability and accuracy of AI-based business data analysts. PUBLICATION PERMISSIONS:
PyData provided Coding Tech with the permission to republish PyData talks. CREDITS:
PyData YouTube channel: https://www.youtube.com/@PyDataTV https://www.youtube.com/watch?v=8NfvLDhINdI

Dapr's Features and Functionality 🚀 Dapr offers a range of APIs, including the newer Dapr workflows, which enhance the capabilities and functionality of the platform.
🌐 The rise of cloud-native approaches has introduced new challenges for developers, such as state management and ensuring secure and consistent persistence of state in individual microservices.
🌍 Dapr's building block APIs enable developers to create portable applications that are not tied to any specific language or framework, promoting flexibility and interoperability.
⚙️ Dapper's concept of resiliency acknowledges the inevitability of failure in systems, highlighting the importance of building robust and fault-tolerant microservices.
🔧 Developers can define their own fault tolerance policies using a resiliency manifest, allowing for customization and fine-tuning of the application's behavior.
🐳 Dapper also includes a Dapper Zipkin container for distributed tracing, allowing developers to easily track and analyze the flow of requests and responses in their microservices architecture.
🌐 Dapr supports both programmatic and declarative subscriptions, providing flexibility in how developers can subscribe to topics and handle events in their applications.
🌐 Dapr provides a convenient way for applications to subscribe to specific topics on a broker, ensuring that messages are only received by the intended subscribers.
💡 Dapr's multi-op run capability allows developers to consolidate multiple Dapper applications into one manifest, simplifying the process of running and managing microservices.
🆔 Giving each individual application a unique Dapper app ID is critical for service invocation and allows for easy identification and communication between apps.
💾 The Dapr API allows developers to easily store data in a backing Redis component, providing a convenient way to persist information.
💪 The State Management API offers a range of powerful features, including strong consistency, optimistic concurrency control, transactions, and state encryption, providing developers with flexibility and security for managing application state.
Dapr's Community and Momentum 💡 Dapr is a community-driven and vendor-neutral project that has gained significant momentum, becoming the 10th largest CNCF project with over 2,800 contributors on GitHub.
📈 The number of Dapr components continues to grow with every release, showcasing the momentum and flexibility of the Dapr project.
💪 The growth of the Dapper user base and the increasing adoption of its APIs as a standard is empowering more and more organizations to embrace microservices architecture.
Dapr's Benefits for Developers 🔃 By using Dapr, developers can leverage a variety of Azure services such as Azure Key Vault, Azure Service Bus, and Azure Cosmos DB for secrets, pub-sub implementation, and state API respectively, without the need to modify their application code.
💡 Dapr allows developers to focus on writing business logic instead of dealing with complex plumbing code for distributed application concerns. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=mBgQBMhboyU https://www.youtube.com/watch?v=74A7YwsmVwM

The io_uring subsystem was introduced in Linux v5.1 and provided a new way to do asynchronous I/O on Linux, improving on the existing AIO subsystem. Since then io_uring has been a source of active development, gaining the ability to delegate credentials across process boundaries in Linux v5.6. Unfortunately, all of this happened without engaging the LSM community, and as a result LSM access controls were not added to io_uring until Linux v5.16. This talk will discuss the challenges in adding LSM controls to the io_uring subsystem, thoughts on why the controls lagged the functional development, and what the LSM community might do to help reduce the changes of similar problems in the future. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=AaaH6skUEI8 https://www.youtube.com/watch?v=F82Qdi5kyjw