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Gen AI And LLMs Will Change Our Lives Profoundly

How will Gen AI and LLMs impact the nature of people's jobs and worker productivity? "Data Cloud Now" anchor Ryan Green kicked off the Data and AI Predictions 2024 event in January by discussing that topic with Snowflake's CEO Sridhar Ramaswamy and Mona Attariyan, Director of Engineering. The conversation also covers the potential for AI to generate misinformation and the need to establish ethical guardrails for the technology.

#12 Kafka Live Stream | HTTP Sink Connector & Business Automation with Make

See the new Lenses Kafka to HTTP Sink Connector in action with Lenses.io and @itsmake. In this 30 minute session, we show you how to trigger APIs that automate your business processes: a message in Kafka calls a Make workflow, then triggering an automation in Salesforce.

Enhancing Software Testing with Large Language Models: Navigating the Challenge of Hallucinations

Software testing is an indispensable stage in the software development lifecycle, tasked with verifying application reliability, security, and performance before deployment. This process evaluates software components to ensure they adhere to specified requirements and perform reliably under varied conditions.

Creating iOS App Clips: Essential Guide for Developers

Introduced in iOS 14, App Clips allow users to quickly access a specific feature within an application (e.g. paying for parking or ordering a coffee) without downloading the full app. So they allow our users to interact with our apps on their terms, creating more targeted interactions that benefit us as well as them.

What is the Listen to Yourself Pattern? | Designing Event-Driven Microservices

The Listen to Yourself pattern is implemented by having a microservice emit an event to a platform such as Apache Kafka, and then consuming its own events to perform internal updates. It can be used as a solution to the dual-write problem since it separates Kafka and database writes into different processes. However, it also provides added benefits because it allows microservices to respond quickly to requests by deferring processing to a later time.