Large Language Models

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Attackers prompted Gemini over 100,000 times while trying to clone it, Google says

ai, AI (Artificial Intelligence), AI language models, AI security, Artificial Intelligence, Biz & IT, ChatGPT, chatgtp, deepseek, Distillation, Gemini, Google, Google Gemini, Large Language Models, LLMs, Machine Learning, OpenAI

On Thursday, Google announced that “commercially motivated” actors have attempted to clone knowledge from its Gemini AI chatbot by simply prompting it. One adversarial session reportedly prompted the model more than 100,000 times across various non-English languages, collecting responses ostensibly to train a cheaper copycat. Google published the findings in what amounts to a quarterly […]

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Adversarial Prompt Generation: Safer LLMs with HITL

ai, AI (Artificial Intelligence), Artificial Intelligence, Generative AI, HITL, Human-in-the-loop (HITL), Large Language Models, LLM, Shaip Blogs

What adversarial prompt generation means Adversarial prompt generation is the practice of designing inputs that intentionally try to make an AI system misbehave—for example, bypass a policy, leak data, or produce unsafe guidance. It’s the “crash test” mindset applied to language interfaces. A Simple Analogy (that sticks) Think of an LLM like a highly capable

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LLM Benchmarking, Reimagined: Put Human Judgment Back In

ai, AI (Artificial Intelligence), Artificial Intelligence, Human-in-the-loop (HITL), Large Language Models, LLM, Shaip Blogs

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

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Role of Large Language Models in Powering Multilingual AI Virtual Assistants

ai, AI (Artificial Intelligence), Artificial Intelligence, Large Language Models, LLM, Shaip Blogs

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

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Building Domain-Specific LLMs: Precision AI for Every Industry

ai, AI (Artificial Intelligence), Artificial Intelligence, Large Language Models, LLM, Shaip Blogs

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

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Understanding Reasoning in Large Language Models

ai, AI (Artificial Intelligence), Artificial Intelligence, Large Language Models, LLM, Shaip Blogs

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,

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NLP vs LLM: Differences Between Two Related Concepts

ai, AI (Artificial Intelligence), Artificial Intelligence, Large Language Models, LLM, NLP, NLP(Natural Language Processing), Shaip Blogs

Language is complex—and so are the technologies we built to understand it. At the intersection of AI buzzwords, you’ll often see NLP and LLMs mentioned as if they’re the same thing. In reality, NLP is the umbrella methodology, while LLMs are one powerful tool under that umbrella. Let’s break it down human-style, with analogies, quotes,

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AI vs ML vs LLM vs Generative AI: What’s the Difference and Why It Matters

ai, AI (Artificial Intelligence), Artificial Intelligence, Generative AI, Large Language Models, LLM, Machine Learning, Shaip Blogs

In today’s AI-driven world, buzzwords like AI, Machine Learning (ML), Large Language Models (LLMs), and Generative AI are everywhere—but often misunderstood. They’re used interchangeably, though each has a distinct role and impact. In this blog, we won’t just define them in silos. Instead, we’ll pit them against each other, clarify how they’re related, how they

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What is Fine-Tuning for Large Language Models? Applications, Methods, and Future Trends

ai, AI (Artificial Intelligence), Artificial Intelligence, Large Language Models, LLM, Shaip Blogs

Large language models like GPT-4 and Claude have revolutionized AI adoption, but general-purpose models often fall short when it comes to domain-specific tasks. They’re powerful, but not tailored for specialized use cases involving proprietary data, complex industry terminology, or business-specific workflows. Fine-tuning large language models (LLMs) solves this problem by adapting pre-trained models for specific

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Grounding AI: Towards Intelligent, Stable Language Models

ai, AI (Artificial Intelligence), Artificial Intelligence, Conversational AI, Large Language Models, LLM, Shaip Blogs

Introduction to Grounding in Artificial Intelligence In the fast-changing landscape of artificial intelligence, Large Language Models (LLMs) have become powerful tools that generate human-like text. However, these outputs are not always accurate or contextually appropriate. That’s where grounding AI comes in—anchoring models to real-world data to improve factuality and relevance. Ungrounded models might sound coherent

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