Systems | Development | Analytics | API | Testing

Top 3 Data + AI Predictions for Manufacturing in 2024

Investment in AI for manufacturing is expected to grow by 57% by 2026. That’s hardly surprising — with AI’s ability to augment worker productivity, improve efficiency and drive innovation, its potential in manufacturing is vast. AI’s predictive capabilities can help manufacturing leaders anticipate market trends and make data-driven decisions, creating financial opportunities for suppliers as well as customers.

6 Ways Marketers Are Using Generative AI: Is It Really Saving Time?

AI was the hot topic of 2023 and will continue to reign in 2024: ChatGPT first launched at the end of 2022 and became a massive hit in just a few months. Google released Bard shortly after, and then, new AI tools just kept popping up, prompting marketers to learn how to leverage them to become more efficient and productive.

LLMOps vs. MLOps: Understanding the Differences

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. But a successful deployment of LLMs has to go beyond prototyping, which is where LLMOps comes into play. LLMOps is MLOps for LLMs. It’s about ensuring rapid, streamlined, automated and ethical deployment of LLMs to production. This blog post delves into the concepts of LLMOps and MLOps, explaining how and when to use each one.

Accelerate Gen AI Securely With Snowflake Cortex And Snowpark Container Services

Fueled by vast data volumes and powerful computing, AI is revolutionizing work. To capture the value of Generative AI for business, companies need to customize LLMs with their enterprise data. But feeding sensitive data into externally hosted LLMs poses security and exposure risks, and self-hosting LLMs carry a heavy operational burden from maintaining complex environments.

Accelerating Gen AI for Customer Service with Fivetran, Google Cloud, BigQuery and Vertex AI

Learn how Fivetran’s automated data movement platform allows you to accelerate building Gen AI applications for customer service in Google Cloud with BigQuery and Vertex AI. Kelly Kohlleffel steps you through creating four connectors to BigQuery, including a relational database connector plus Jira, Slack, and Zendesk connectors. Then you’ll see how easy it is to quickly build two Gen AI apps, one for search and one for chat, using Vertex AI and the new customer service datasets in BigQuery.

5 Steps to Data Diversity: More Diverse Data Makes for Smarter AI

In an iconic Top Gun scene, Charlie tells Maverick that a maneuver is impossible. Maverick replies, “The data on the MIG is inaccurate.” In the more recent sequel, despite his extensive, firsthand knowledge, Maverick is told “the future’s coming and you’re not in it.” While flying may be more automated now, the importance of accurate and diverse data for aviation safety remains — and is likely even more critical.