Posts Tagged ‘machine learning’

“Clean rooms” have emerged as a pivotal data sharing innovation with both Databricks and Snowflake providing enterprise alternatives. Clean rooms are secure environments designed to allow multiple parties to collaborate on data analysis without exposing sensitive details of data. They serve as a sandbox where participants can perform computations on shared datasets while keeping raw […]

I’ve been coding in notebooks for so long, I forgot how much I missed a nice, deployed application. I also didn’t realize how this was limiting my solution space. Then I started working with Databricks Apps. Databricks Apps are designed to extend the functionality of the Databricks platform, providing users with enriched features and capabilities […]

Databricks announced a full, free version of the platform at the Data and AI Summit. While the Free Edition is targeted to students and hobbyists, I also see opportunities where enterprise architects can effectively evangelize Databricks without going through Procurement for a license. Choosing the right platform to manage, analyze, and extract insights from massive […]

Lakebase is Databricks‘ OLTP database and the latest member of its ML/AI offering. Databricks has incorporated various components to support its AI platform, including data components. The Feature Store has been available for some time as a governed, centralized repository that manages machine learning features throughout their lifecycle. Mosaic AI Vector Search is a vector […]

Perficient is excited to announce that we have achieved Elite level partner status within the Databricks partner network. This top-tier recognition highlights the outstanding efforts of our talented Databricks strategists, architects, industry leaders, and engineers. It’s a testament to our data and AI expertise and unwavering commitment to delivering transformative results for our clients. Perficient’s […]

The financial services sector is experiencing transformative changes driven by technological advancements and innovative trends. We are witnessing the integration of AI, the rise of hyper-personalization, and the adoption of advanced digital platforms, all of which are revolutionizing operations and client interactions. Additionally, the emergence of embedded finance and an increased focus on regulatory compliance […]

A friend recently shared a research paper from Oxford Academic about Large Language Models (LLMs) and their human-like biases. I found it fascinating. The article explains how some groups use LLMs to simulate human participants. Since these models are trained on human-generated data, they can emulate human responses across diverse psychological and behavioral experiments. It […]

Artificial Intelligence (AI) has exploded into the mainstream, largely through chatbots and agents powered by Large Language Models (LLMs). Users can now have real-time conversations with multimodal AI tools that understand your text, voice, and images – even documents! The progress has been mind blowing, and tech companies are racing to integrate AI features into […]

In the rapidly evolving landscape of digital transformation, businesses are constantly seeking innovative ways to enhance their operations and gain a competitive edge. While Generative AI (GenAI) has been the hot topic since OpenAI introduced ChatGPT to the public in November 2022, a new evolution of the technology is emerging that promises to revolutionize how […]

Nowadays, AI is a crucial field with various frameworks like ML.NET that can be used to build amazing applications using pre-built models from cloud providers. It’s important to learn how these services work behind the scenes, how to create custom models, and understand how your application can interact with AI frameworks beyond just cloud providers […]

The Setting Imagine a solitary walk in a crowded park in the middle of downtown. Walking down the main path, one can hear joggers bounding past one’s left, a couple laughing to one’s right, a street musician playing the violin over one’s shoulder, and a group of children laughing at the playground somewhere off and […]

Feature Engineering is the preprocessing step used to make raw data usable as input to an ML model through transformation, aggregation, enrichment, joining, normalization and other processes. Sometimes feature engineering is used against the output of another model rather than the raw data (transfer learning). At a high level, feature engineering has a lot in […]