Practical Enterprise AI: Common Roadblocks and How to Avoid Them
Come learn what to keep in mind when implementing AI-powered applications and effective strategies for scalable, practical generative AI.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Snowflake Arctic Cookbook Series: Instruction-Tuning Arctic
On April 24, we released Snowflake Arctic with a key goal in mind: to be truly open. In line with that goal, the Snowflake AI Research team is writing a series of cookbooks to describe how to pretrain, fine-tune, evaluate, and serve large-scale mixture-of-experts (MoEs) such as Arctic.
With AI Writing Code, Will AI Replace Software Engineers?
Software developers have plenty to keep them awake at night. Their top concern is no longer how to express the latest algorithm in their favorite language (C, C++, Erlang, Java, etc.). Instead, it’s being replaced by artificial intelligence (AI). Here we take a look at the process for AI writing code and answer the question: Will AI replace programmers? Read along or jump ahead to the section that interests you the most.
5 Ways Advertising, Media and Entertainment Companies are Using Gen AI
The emergence of generative AI (gen AI) heralds a new, groundbreaking era for advertising, media and entertainment. According to a recent Snowflake report, Advertising, Media and Entertainment Data + AI Predictions 2024, gen AI is going to transform the industry — from content creation to customer experience. The companies that will come out ahead during this time are those that most successfully and quickly supercharge their data strategy.
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Testing LLM Backends for Performance with Service Mocking
While incredibly powerful, one of the challenges when building an LLM application (large language model) is dealing with performance implications.
Introducing Cloudera's AI Assistants
In the last couple of years, AI has launched itself to the forefront of technology initiatives across industries. In fact, Gartner predicts the AI software market will grow from $124 billion in 2022 to $297 billion in 2027. As a data platform company, Cloudera has two very clear priorities. First, we need to help customers get AI models based on trusted data into production faster than ever.
GitTogether | GenAI & Open Source | Kunal Deo
The resurgence of Artificial Intelligence (AI) in recent years owes much to a pivotal moment: the publication of a groundbreaking paper by Google. This event underscores the significant role of Open Source in advancing AI technologies. In this presentation, we delve into how Open Source is not just influencing but also shaping the landscape of Generative AI (GenAI). However, our focus extends beyond the traditional dichotomy of Open Source versus proprietary technologies. Instead, we explore the complementary nature of both realms in fostering the development of the AI ecosystem.
What is Intelligent Process Automation? 5 Key Facts
As generative AI grows in popularity and enterprises scramble to embrace new technology in a scalable, compliant way, it can be difficult to know the right path forward. Your enterprise has already invested in automating processes to free up resources and improve organizational efficiency, but is it enough? This is where intelligent process automation comes into play.
Product analytics for generative AI model and media asset companies using BigQuery
Using BigQuery object tables, we analyze unstructured Cloud Storage data with generative AI models and join the results with BigQuery structured data.