Systems | Development | Analytics | API | Testing

Industry leaders sat down to explore the need for company-wide AI readiness, knowledge graphs and using data curation to drive smarter business decisions.

STARWEST 2024 was not just a conference; it was a vibrant hub of exploring knowledge and exploration into the transformative realm of generative AI and software testing. At this event, we started day 2 with an energetic workshop of "Evaluating and Testing Generative AI: Insights and Strategies", led by Jason Arbon, CEO of Checkie.AI, which covered the complex challenges of testing AI systems like ChatGPT and LLAMA.

Fivetran now supports the Milvus vector database as a destination, making it easier to onboard every data source for RAG and AI-powered search.

Multimodal AI is a critical player in the new wave of artificial intelligence. By combining different types of data like text, images, and audio, multimodal AI creates more intuitive and versatile AI systems that can more closely mimic human decision-making.

It’s no secret that artificial intelligence (AI) is revolutionizing the way companies operate with its ability to sift through mountains of data and make accurate predictions at record speed. But with great power comes great responsibility. As AI systems are more regularly incorporated into business, it’s critical that data sources are both accurate and secure to prevent error.

In the world of banking, challenges abound. Fragmented processes and add-on technologies that don’t integrate well with legacy equipment pose issues for financial institutions already struggling with ever-increasing regulatory compliance requirements and customer expectations. Banks have invested heavily in anti-money laundering (AML) solutions to keep up with heightened risks and remain competitive.

Artificial Intelligence (AI) is transforming industries, enhancing decision-making processes, and creating new opportunities across various domains. However, selecting the right type of AI for your specific needs can be challenging. Broadly, AI can be categorized into predictive (sometimes known as discriminative or traditional) AI and generative AI, each serving different purposes.

What are the differences between generative AI vs. large language models? How are these two buzzworthy technologies related? In this article, we’ll explore their connection. To help explain the concept, I asked ChatGPT to give me some analogies comparing generative AI to large language models (LLMs), and as the stand-in for generative AI, ChatGPT tried to take all the personality for itself.