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When I first started as a data scientist, there was a gap. I met with dozens of organizations who would invest time and resources into building accurate and tuned models and then ask, “What now?” They had a fantastic model in hand but couldn’t get it into a place and […] The post There is […]
There is yet another AI productivity gap Read More »
If you have ever trained a model, fine-tuned an LLM, or even experimented with AI on a weekend, chances are you have landed on Hugging Face. It has quietly become the GitHub of datasets – a place where developers, researchers, and data professionals go to build models and accelerate ideas. From code benchmarks and web-scale
10 Most Downloaded Hugging Face Datasets and Their Use-cases Read More »
With the popularity of AI coding tools rising among some software developers, their adoption has begun to touch every aspect of the process, including human developers using the tools to improve existing AI coding tools. We’re not talking about runaway self-improvement here; just people using tools to improve the tools themselves. In interviews with Ars
OpenAI built an AI coding agent and uses it to improve the agent itself Read More »
On Thursday, OpenAI released GPT-5.2, its newest family of AI models for ChatGPT, in three versions called Instant, Thinking, and Pro. The release follows CEO Sam Altman’s internal “code red” memo earlier this month, which directed company resources toward improving ChatGPT in response to competitive pressure from Google’s Gemini 3 AI model. “We designed 5.2
OpenAI releases GPT-5.2 after “code red” Google threat alert Read More »
When a person admits they made a mistake, something surprising happens. The confession often restores trust rather than breaking it. People feel safer around someone who owns their errors than someone who hides them. Accountability builds confidence. What if AI models can do the same? Most AI systems give confident answers, even when they are
How Confessions Can Keep Language Models Honest? Read More »
People are starting to compile resolutions for the new year, focusing on evolving their own habits and goals. At SAS, we’ve also looked toward 2026 to gather predictions on how AI in the public sector might evolve over the next 12 months. Prediction: By 2026, governments will utilize large language […] The post Using LLMs
Using LLMs to create synthetic data and tangible progress in the public sector Read More »
If you only look at automated scores, most LLMs seem great—until they write something subtly wrong, risky, or off-tone. That’s the gap between what static benchmarks measure and what your users actually need. In this guide, we show how to blend human judgment (HITL) with automation so your LLM benchmarking reflects truthfulness, safety, and domain
LLM Benchmarking, Reimagined: Put Human Judgment Back In Read More »
Virtual assistants are progressing beyond simple question-and-answer formats to solving complex queries. Today, AI-driven virtual assistants communicate in multiple languages easily, and large language models, or LLMs, power this transformation. Now you can ask your device for restaurant recommendations in English and get an answer in Spanish. That’s what LLMs have made possible in recent
Role of Large Language Models in Powering Multilingual AI Virtual Assistants Read More »
Imagine hiring a new employee. One candidate is a “jack of all trades”—knows a little bit about everything, but not in depth. The other has 10 years of experience in your exact industry. Who do you trust with your critical business decisions? That’s the difference between general-purpose large language models (LLMs) and domain-specific LLMs. While
Building Domain-Specific LLMs: Precision AI for Every Industry Read More »
When most people think of large language models (LLMs), they imagine chatbots that answer questions or write text instantly. But beneath the surface lies a deeper challenge: reasoning. Can these models truly “think,” or are they simply parroting patterns from vast amounts of data? Understanding this distinction is critical — for businesses building AI solutions,
Understanding Reasoning in Large Language Models Read More »
