A glance at natural language processing
Natural language processing (NLP) is a discipline where machines are built with the main aim of manipulating human language or data resembling human language in the manne...
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High-performance computing’s role in real-time graph analytics
A podcast with CEO Ricky Sun of Ultipa Image by Gerd Altmann from Pixabay Relationship-rich graph structures can be quite complex and resource consuming to process at sca...
Choosing the right technique: Prompt engineering vs fine-tuning
Artificial intelligence and machine learning applications have been revolutionizing many industries for the last decade, but due to generative AI models like ChatGPT, Bar...
From MLOps to LLMOps— and hardware headaches ahead
A model on its own is typically not enough. It requires the data, which comes in a very specific format and has to be the same format that will be used at the time of inf...
Top 7 use cases of GenAI in FinTech
In 2024, the fusion of AI and financial technology is not just a wave of the future – it’s a rapidly evolving present. Artificial Intelligence, especially the...
Revolutionizing healthcare with chatbots: A humanized exploration
This article explores the versatile applications of healthcare chatbots, shedding light on their transformative impact on patient care and medical processes....
Search is Dead, Long Live Search!
This article is more about building better LLM and GPT-like applications, than search. Yet most people use GPT as a substitute for search. Indeed, OpenAI replaced search ...
How (and when?) to hire a data scientist
Image by Christina @ wocintechchat.com / Unsplash Ten years ago, data was something an analyst reviewed and handed over to people who were going to use it. Now, businesse...
The impact of emerging technologies on data excellence
Data is the lifeblood of our digital world. We crave it, analyze it, and base decisions on it. But a hidden truth lurks beneath the glossy surface of charts and graphs: o...
Choosing the right machine learning algorithm for business success
Machine learning can be overwhelming with its variety of tasks. Most tasks can be solved with a few ML algorithms. You need to be aware of which algorithms to select, whe...