Introduction Have you ever wondered how AI can understand and answer questions just like a human? What are the underlying technologies that make this possible? How to evaluate the performances of AI answering questions? With what techniques can AI’s performance be enhanced? Last but not least, what are the

Introduction Today, we delve into two giants in the realm of generative AI: Llama 3 and ChatGPT 4. How do these models differ in architecture, performance, and real-world applications? Join us as we explore their capabilities, strengths, and the future they promise. Overview of Generative AI Models: Llama 3 and

Introduction Welcome to our exploration of OpenHermes 2.5, a groundbreaking dataset developed by Teknium. This blog dives into the features, applications, and advancements of this state-of-the-art model extension.  What Is Openhermes 2.5? Basic Background of Openhermes 2.5 Developed by Teknium, Openhermes 2.5 is an extension and

Introduction In November 2023, Elon Musk’s company xAI introduced a new AI model named Grok. What makes Grok special is how it can crack jokes and sometimes even act a bit rebellious, which people think shows a side of Musk’s own personality.  In this blog, we will discuss

Introduction In the world of tech today, there’s a big push for AI-driven tools and services. Big players like OpenAI and Gemini are leading the charge with their LLM (Large Language Model) APIs, offering powerful ways to process language that let developers create cool new stuff. But getting to

Introduction Are you a researcher or developer interested in the field of dialogue summarization? If so, you won’t want to miss the groundbreaking SAMSum Dataset— a unique dataset that is poised to transform the state of the art. In this blog post, referencing the paper “SAMSum Corpus: A Human-annotated

Introduction In this blog, we delve into the fascinating world of large language models (LLMs) and their capabilities in performing translation tasks. Inspired by the academic paper titled “Adaptive Machine Translation with Large Language Models,” we will explore the following questions: * How do LLMs accomplish translation without any additional training

Introduction What if language models could tackle complex problems with the same step-by-step approach humans use? In the realm of large language models (LLMs), the strategy of Least-to-Most Prompting offers a promising solution. Referencing the paper “Least-To-Most Prompting Enables Complex Reasoning in Large Language Models,” this blog explores how this

Introduction As large language models (LLMs) like GPT-3, PaLM, ChatGPT and others gain immense popularity, the need to thoroughly evaluate their capabilities has become crucial. These advanced AI models can understand and generate human-like text, making them powerful tools across various applications.  However, with great power comes great responsibility — we

Introduction Large Language Model (LLM) APIs are powerful tools that allow businesses and developers to integrate advanced natural language processing functionalities into their applications. An LLM API pricing comparison is crucial for making informed decisions that balance performance and cost-effectiveness. This blog will provide an in-depth look at what LLM

Introduction How are large language models developed? How can they be used in medicine? What are some popular LLMs in medicine? How to train my own LLM in medicine? What are the limitations of LLM in medicine? In this blog, we will explore these questions one by one. How Are

Key Highlights * Understanding LLM API: LLM APIs integrate advanced AI for tasks like natural language processing and text generation. * Claude 3 Opus vs. Novita AI LLM API: Claude excels in multimodal capabilities and performance benchmarks, while Novita AI offers affordability, low latency, scalability, and uncensored content. * User Experience and Integration:

Introduction What are the limitations of large language models (LLMs)? Starting from the definition of LLM, we are going to discuss 8 limitations one by one. For each limitation, we ask 3 questions: What does this limitation mean and why? What are the implications of this limitation in practice? How

Introduction What is cumulative reasoning with large language models? Why do we need cumulative reasoning for LLMs? What does cumulative reasoning with LLMs look like? Can LLMs Do Cumulative Reasoning Well? In this blog, we will discuss these questions one by one in a plain and simple way, referencing the

Introduction How do we humans discern the causes behind the effects we observe around us? When we see storm clouds gathering, why do we predict rain, or how do we conclude that a medication was effective when our health improves? This ability, known as causal reasoning, is a key component

Introduction Can large language models transform computational social science? Wait a second, what does computational social science do? Welcome to the dynamic field of computational social science (CSS), where large language models (LLMs) are revolutionizing the way we analyze and interpret social behaviors, opinions, and trends. In this blog, centering

Introduction Recently, an LLM with only 70B parameters outperforms GPT 3. This LLM, called Chinchilla, was developed by Hoffmann and his colleagues. In their work, they state that current LLMs are not compute-optimal. Why is this? How do they train their so-called compute optimal LLM Chinchilla? What are the limitations

Introduction How good are large language models at program synthesis? Some scholars may say, “For the largest LLMs, good enough!”  In this blog, we will embark on the journey of understanding program synthesis with large language models, from its definition and functioning to the frontier study about empirical evaluations of

Introduction What will happen when large language models encode clinical knowledge? In this article, we will discuss the theoretical applications of LLMs in the medical domain, the constraints that prohibit their use, the consequences of LLMs encoding clinical knowledge, current open-source medical LLMs and the way to train your own

Introduction How can large language models self-improve? Let’s demystify this magic! This blog aims to unravel the intricacies of how these models, once a figment of science fiction, are now a reality, enhancing their capabilities through internal mechanisms without the need for external supervision. We will delve into the

Introduction Are emergent abilities of large language models a mirage? The short answer to this question is: mostly, yes. Some scholars from Stanford argue that it’s all about metrics. To be specific, LLMs develop their abilities gradually, not abruptly according to most metrics, while these emergent miracles only show

Introduction As machine learning technologies become increasingly prevalent, the need to ensure the privacy and security of the data used to train these LLMs has become a critical concern. One key approach to addressing this challenge is the use of differential privacy (DP) techniques. In this article, we will delve

Introduction  How and why do larger language models do in-context learning differently? In this article, we will explore the concept of “in-context learning” (ICL), discuss the latest findings about in-context learning behaviors of models of different sizes in plain English, and delve into ways that can leverage different LLM’s

Introduction Why are people talking about Replika MOD APK? What is it? What can I do with it? What are the potential risks to consider when using it? What are the alternatives to Replika MOD APK? In this article, we will discuss these questions one by one. Importantly, considering the

Introduction Often heard of Llama weights but have little idea about it? Don’t worry! In this ultimate guide, we will explore the concept of weight, discuss the content and the importance of Llama weights, ways of downloading llama weights and the most efficient method of adopting LLMs — — API. So,