Open post Separators

Why are separators important for prompt engineering?

Separators, also known as delimiters, play a crucial role in enhancing the performance and effectiveness of prompts used with Large Language Models (LLMs). The integration of separators within prompting is a strategy inspired by human cognitive processes, aimed at improving the reasoning capabilities of large language models (LLMs). This method, involves strategically placing separators in...

Open post Prompt Chaining

What is Prompt Chaining?

Prompt chaining is a technique used in generative AI models, particularly within the realms of conversational AI and large language models (LLMs). This method involves using the output from one model interaction as the input for the next, creating a series of interconnected prompts that collectively address a complex problem or task[1][2]. This approach contrasts...

Open post In-Context Learning

What is In-Context Learning of LLMs?

In-context learning (ICL) refers to a remarkable capability of large language models (LLMs) that allows these models to perform new tasks without any additional parameter fine-tuning. This learning approach leverages the pre-existing knowledge embedded within the model, which is activated through the use of task-specific prompts consisting of input-output pairs. Unlike traditional supervised learning that...

Open post Emergent

Do Emergent Abilities in AI Models Boil Down to In-Context Learning?

Emergent abilities in large language models (LLMs) represent a fascinating area of artificial intelligence, where models display unexpected and novel behaviors as they increase in size and complexity. These abilities, such as performing arithmetic or understanding complex instructions, often emerge without explicit programming or training for specific tasks, sparking significant interest and debate in the...

Open post Large Language Models

An introduction to how Large Language Models work

Large Language Models (LLMs) have revolutionized the field of Natural Language Processing (NLP) by offering unprecedented capabilities in generating coherent and fluent text[1]. The evolution of LLMs can be traced back to early language models that were limited by their simplistic architecture and smaller datasets. These initial models primarily focused on predicting the next word...

Open post coding

Coding in the age of AI

Artificial Intelligence (AI) has been making subtle yet significant inroads into the daily workflows of tech professionals. Despite the lack of mainstream media coverage, these transformative tools are reshaping how work is done, often with profound benefits to individual workers rather than firms. Here, we explore two illustrative accounts from Nicholas Carlini and Erik Schluntz,...

Open post hallucinations

‘Intersectional hallucinations’: why AI struggles to understand that a six-year-old can’t be a doctor or claim a pension

When you go to the hospital and get a blood test, the results are put in a dataset and compared with other patients’ results and population data. This lets doctors compare you (your blood, age, sex, health history, scans, etc) to other patients’ results and histories, allowing them to predict, manage and develop new treatments....

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