Data Science Salon New York 2025 – a glimpse into the future of financial services
The New York edition of Data Science Salon offered a mix of tech and business talks on AI and finance…

The New York edition of Data Science Salon offered a mix of tech and business talks on AI and finance…

Optimizing SaaS Customer Lifetime Value (CLTV) requires continuous collection and monitoring of customer…

I spent months overengineering an AI chatbot. Then I threw most of it…

Most current workflow systems are non-dynamic (static) in nature. Once a workflow is …
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With 30% of AI-related mishaps in 2022 attributable to adversarial assaults, cybersecurity has…

Emerging retrieval-augmented generation (RAG)-powered enterprise conversational QA applications leverage massive internal knowledge bases…

Generative AI is a subset of artificial intelligence that focuses on creating new content. In the enterprise, there are several key opportunities to leverage…
Modern Artificial Intelligence is an umbrella term that includes the Machine Learning techniques and tools that enable computers to produce desired outcomes based on large quantities of data…

Fraud has been a persistent threat to commerce and businesses, significantly undermining their financial health and adversely affecting their bottomline…

The universe of machine learning (ML) and its applications is expanding at an ever-increasing rate and there is hardly any industry that is not leveraging the…

Over the last two years, the artificial intelligence discussion has been preoccupied with scale. Larger models, more parameters and continually increasing…

As artificial intelligence continues to expand, the importance of effectively communicating with large language models (LLMs) is crucial…

Jörg Schad, CTO at ArangoDB, illustrates how the fusion of Large Language Models and Knowledge Graphs creates a potent synergy, bypassing the need for specialist teams to manage database queries…

Companies in the healthcare industry utilize their large amounts of data in combination with natural language processing (NLP) techniques to enhance personalized care, identify high risk…

This post is adapted from a talk by Charles Alcorn – Head of Data Science at Roche Molecular Systems and describes medical content management…

AI is leading the charge in the age of data-driven technology, transforming business and daily life. But this development comes with a price, frequently at the sacrifice…

The days of walking miles up and down shopping streets to find an appropriate dress are long gone. Online services like Stitch Fix leverage data and algorithms to help customers find…

As technology continues to advance, AI has become an integral part of the e-commerce industry. However, there are several challenges that AI faces in this domain. One of the major challenges is ensuring personalized and accurate…

Comet’s annual Convergence conference gathers AI and data-science practitioners around the latest industry trends. The Convergence is one of Data Science Salon’s partner events, where…

Data is now essential for organizations, driving their operations as a lifeblood and fueling Artificial Intelligence (AI). The amount of data produced daily is…

At times it may seem that AI and robots are poised to make us humans obsolete. But the opposite is happening: every advance in technology makes humans more relevant. To be precise…

Presented by Fatih Akici – Manager, Risk Analytics and Data Science at Populus Financial Group during Data Science Salon Austin, you can watch the full talk here…
Right now, somewhere in a planning meeting, someone’s asking “can we make this real-time” and everyone’s nodding. Sounds much better, obviously. New data. Fast decisions. Dashboards on the move. Who would advocate for slower? I’ve made this...
It’s easy to get caught up in the excitement of doing WAY more in less time. Work that once required days of data cleaning, analysis, modeling, presentation building, and insight development can now be delivered in hours with AI. Managers want...
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Your best analyst gets things wrong. Misremembered figures. Stale assumptions. A confident error in a board deck. You trust them anyway, and the reason explains more about enterprise AI than any benchmark does. You trust them...
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