Image by Editor | ChatGPT # Introduction Hallucinations — the bane of the language model (LM) and its users — are the plausible-sounding but factually incorrect statements produced by LMs. These hallucinations are problematic because they can erode user trust, propagate misinformation, and mislead downstream decisions even when the output is expressed with high confidence. …
We’re expanding our risk domains and refining our risk assessment process. AI breakthroughs are transforming our everyday lives, from advancing mathematics, biology and astronomy to realizing the potential of personalized education. As we build increasingly powerful AI models, we’re committed to responsibly developing our technologies and taking an evidence-based approach to staying ahead of emerging …
days, people are taking more loans than ever. For anyone who wants to build their own house, home loans are available and if you own a property, you can get a property loan. There are also agriculture loans, education loans, business loans, gold loans, and many more. In addition to these, for buying items like …
Image by Author | Ideogram # Introduction When you’re new to analyzing with Python, pandas is usually what most analysts learn and use. But Polars has become super popular and is faster and more efficient. Built in Rust, Polars handles data processing tasks that would slow down other tools. It is designed for speed, memory …
Our new method could help mathematicians leverage AI techniques to tackle long-standing challenges in mathematics, physics and engineering. For centuries, mathematicians have developed complex equations to describe the fundamental physics involved in fluid dynamics. These laws govern everything from the swirling vortex of a hurricane to airflow lifting an airplane’s wing. Experts can carefully craft …
Discovering new solutions to century-old problems in fluid dynamics Read More »
language models has made many Natural Processing (NLP) tasks appear effortless. Tools like ChatGPT sometimes generate strikingly good responses, leading even seasoned professionals to wonder if some jobs might be handed over to algorithms sooner rather than later. Yet, as impressive as these models are, they still stumble on tasks requiring precise, domain-specific extraction. Motivation: …
Image by Editor | ChatGPT/font> As large language models (LLMs) become increasingly central to applications such as chatbots, coding assistants, and content generation, the challenge of deploying them continues to grow. Traditional inference systems struggle with memory limits, long input sequences, and latency issues. This is where vLLM comes in. In this article, we’ll …
Acknowledgements We thank the International Collegiate Programming Contest (ICPC) for their support. This project was a large-scale collaboration, and its success is due to the combined efforts of many individuals and teams. Hanzhao (Maggie) Lin led the overall technical direction for Gemini competitive programming and ICPC 2025 efforts, and co-led with Heng-Tze Cheng on the …
systems, understanding user intent is fundamental especially in the customer service domain where I operate. Yet across enterprise teams, intent recognition often happens in silos, each team building bespoke pipelines for different products, from troubleshooting assistants to chatbots and issue triage tools. This redundancy slows innovation and makes scaling a challenge. Spotting a Pattern in …
Image by Ideogram Most of my days as a data scientist look like this: Stakeholder: “Can you tell us how much we made in advertising revenue in the last month and what percentage of that came from search ads?” Me: “Run an SQL query to extract the data and hand it to them.” Stakeholder: …
Here’s How I Built an MCP to Automate My Data Science Job Read More »
