ai 
The Pragmatic Engineer
MAY 1, 2024
I'm sharing this piece in public more than a month later, as it provides important context and analysis for the AI dev tools space. There’s been a number of news stories about “AI developers,” recently. The world’s first “AI developer” did not touch its creator’s website.
The Pragmatic Engineer
MARCH 19, 2024
There’s been a number of news stories about “AI developers,” recently. The company says: “Devin is the new state-of-the-art on the SWE-Bench coding benchmark, has successfully passed practical engineering interviews from leading AI companies, and has even completed real jobs on Upwork.
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Data Engineering Podcast
OCTOBER 1, 2023
Now that AI has reached the level of sophistication seen in the various generative models it is being used to build new ETL workflows. In this episode Jay Mishra shares his experiences and insights building ETL pipelines with the help of generative AI. What are some of the types of errors that you are likely to experience from the AI?
Snowflake
MARCH 5, 2024
As Large Language Models are revolutionizing natural language prompts, Large Vision Models (LVMs) represent another new, exciting frontier for AI. One of the leaders in this area is Landing AI, a company founded by globally recognized AI expert Andrew Ng.
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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success?
databricks
APRIL 26, 2024
We’re excited to announce the Databricks Generative AI Hackathon winners. This hackathon garnered hundreds of data and AI practitioners spanning 60 invited companies.
Precisely
NOVEMBER 20, 2023
AI transforms how we interact with technology, make decisions, and solve complex problems. What defines a successful AI initiative, and how can your organization ensure that your investments and hard work deliver maximum value for your organization? What Does a Successful AI Initiative Look Like? What does that mean for AI?
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In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities? Infusing advanced AI features into reports and analytics can set you apart from the competition.
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Organizations look to embedded analytics to provide greater self-service for users, introduce AI capabilities, offer better insight into data, and provide customizable dashboards that present data in a visually pleasing, easy-to-access format.
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations.
Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase
Putting the right LLMOps process in place today will pay dividends tomorrow, enabling you to leverage the part of AI that constitutes your IP – your data – to build a defensible AI strategy for the future.
Speaker: Tony Karrer, Ryan Barker, Grant Wiles, Zach Asman, & Mark Pace
We'll walk through two compelling case studies that showcase how AI is reimagining industries and revolutionizing the way we interact with technology. Don't miss out on this opportunity to stay ahead of the AI curve! Save your seat today and be part of the tech conversation that's shaping the future.
Speaker: Dr. Greg Loughnane and Chris Alexiuk
Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Aarushi Kansal, AI leader, is here to explore ongoing testing and evaluation strategies tailored specifically for LLM-based applications. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.
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Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.
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