Software testers, or SDETs, have several responsibilities in today's QA-driven software industry. In addition to collaborating with developers to plan and execute tests, they are often responsible for setting up and maintaining continuous integration (CI) processes, analyzing test results, and generating reports for stakeholders. In this article, you'll learn about the evolution of the SDET role and how automation and artificial intelligence (AI) can help improve efficiency.
Artificial intelligence (AI) is now well and truly mainstream. Once the preserve of futurists and doom-mongers muttering about job losses, it has become a global watercooler topic thanks to the rise of ChatGPT, which promises to transform the way the entire world goes to work. But AI has been a vital tool in the developer’s armoury for a while. It has given us new ways to optimize workflow and focus on those high-level tasks that will be forever human.
Generative AI and large language models (LLMs) are revolutionizing many aspects of both developer and non-coder productivity with automation of repetitive tasks and fast generation of insights from large amounts of data. Snowflake users are already taking advantage of LLMs to build really cool apps with integrations to web-hosted LLM APIs using external functions, and using Streamlit as an interactive front end for LLM-powered apps such as AI plagiarism detection, AI assistant, and MathGPT.
Making a Question Answering (QA) bot that can cite your own documentation and help channels is now possible thanks to chatGPT and Langchain, an open-source tool that cleverly uses chatGPT but doesn’t require retraining it. But it’s a far cry from “out of the box.” One example is that you have to get the prompt just right. To get an LLM (large language model) to do exactly what you want, your instructions will have to be very clear, so what if we automate that too?
by Victor Sonck, Developer Advocate, ClearML Sarcasm can be difficult to detect in text, especially for machines. However, with the power of large language models, it’s possible to create a tool that can identify sarcastic comments with high accuracy. That’s exactly what the ClearML team did with their latest project: a sarcasm detector that combines various ClearML tools to showcase the capabilities of MLOps.
The world of artificial intelligence and machine learning is constantly evolving, with new challenges and innovations emerging every day. Tzag Elita is a leading provider of HPC and AI solutions in Israel, and understands the importance of staying ahead of the curve and delivering cutting-edge solutions to their customers. That’s why ClearML is excited to announce our partnership with Tzag Elita.
