7th Annual AI Breakthrough Awards Program Honors SmartBear for Best AI Quality Management Solution
Prestigious international awards program recognizes SmartBear as trailblazing AI innovator.
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Risk Mitigation through Generative AI: Safeguarding Revenue against Fraud and Cybersecurity Threats
In today’s digital age, businesses face an ever-increasing array of risks, particularly fraud and cybersecurity threats. McKinsey states, “Cyberattacks will cause $10.5 trillion a year in damage by 2025.” That’s a 300% increase from 2015 levels. These risks can significantly impact a company’s bottom line, reputation, and customer trust.
Announcing AI-Powered API Test Generation in Katalon Studio
It's well known that creating API test cases can be time-consuming and repetitive. Manually adjusting web service requests and verification steps is not only tedious but also prone to errors, especially when dealing with complex systems. Today, we’re thrilled to announce a game-changing feature in Katalon Studio that will revolutionize your testing workflow: AI-powered API test generation from OpenAPI/Swagger specifications.
Databricks: Achieve performance and reliability with purpose-built AI
88% of Databricks users surveyed are turning to AI to improve bug-fixing effectiveness (Databricks). Why? Troubleshooting modern data stacks is typically a toilsome and manual process. The good news – data teams that use DataOps practices and tools will be 10 times more productive (Gartner). With this in mind, Unravel is hosting this live event to demonstrate how AI-enabled observability for Databricks’ Data Intelligence Platform helps you proactively achieve performance and reliability.
How to Scale RAG and Build More Accurate LLMs
This article was originally published on The New Stack on June 10, 2024. Retrieval augmented generation (RAG) has emerged as a leading pattern to combat hallucinations and other inaccuracies that affect large language model content generation. However, RAG needs the right data architecture around it to scale effectively and efficiently.
Embedded Snowpark Container Services Set RelationalAI's Snowflake Native App on Path for Success
Despite the seemingly nonstop conversation surrounding AI, the data suggests that bringing AI into enterprises is still easier said than done. There’s so much potential and plenty of value to be captured — if you have the right models and tools. Implementing advanced AI today requires a solid data foundation as well as a set of solutions, each demanding its own tools and complex infrastructure.
Manage Resource Utilization and Allocation with ClearML
Written by Noam Wasersprung, Head of Product at ClearML Last month we released the Resource Allocation & Policy Management Center to help teams visualize their compute infrastructure and understand which users have access to what resources. This new feature makes it easy for administrators to visualize their resource policies for enabling workload prioritization across available resources.
Revolutionize Your Business Dashboards with Large Language Models
In today’s data-driven world, businesses rely heavily on their dashboards to make informed decisions. However, traditional dashboards often lack the intuitive interface needed to truly harness the power of data. But what if you could simply talk to your data and get instant insights? In the latest version of Cloudera Data Visualization, we’re introducing a new AI visual that helps users leverage the power of Large Language Models (LLMs) to “talk” to their data..
Building AI With Ollama and Django
If you’re not building with AI, are you even building these days? Sometimes, it seems not. AI has become such an integral part of workflows throughout many tools that a clear understanding of integrating it into your product and framework is critical. Django is such a framework that powers thousands of products across the web: Instagram, Pinterest, and Mozilla are all services built on Django.
S1.E8: AI & Machine Learning in Testing | QA Therapy Podcast
Feeling like your team is pinning all their hopes on AI and ML to solve every challenge? In this episode of QA Therapy, we're thrilled to have Tariq King, QA Therapist, join us to explore how AI and ML will shape the future of testing. Tariq, currently serving as the Vice President of Product-Service Systems at EPAM, with over 40 research articles under his belt.