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Revolutionizing Human-Machine Interaction: The Emergence of Prompt Engineering
Author(s): Dimitris Poulopoulos Originally published on Towards AI. Decoding the art and science of prompt engineering, the secret sauce for supercharging Large Language Models. This member-only story is on us. Upgrade to access all of Medium. Photo by Mojahid Mottakin on Unsplash …
Swipe Right for Your Career: Build A Tinder for Jobs
Author(s): Anand Taralika Originally published on Towards AI. A tech deep-dive to build the ultimate hiring platform using large language models & vector databases Photo by Cytonn Photography on Unsplash “Do you know what’s harder than finding a needle in a haystack? …
Talk to your documents as PDFs, txts, and even web pages
Author(s): Damian Gil Originally published on Towards AI. Complete guide to creating a web and the intelligence that allows you to ask questions to docs such as PDFs, TXTs, and even web pages using LLMs. Content Table · Introduction· How does it …
ROUGE Metrics: Evaluating Summaries in Large Language Models.
Author(s): Pere Martra Originally published on Towards AI. The increment of business applications that are based on Large Language Models has brought the need to measure the quality of the solutions provided by these applications. Here is where metrics like ROUGE become …
A Framework For Efficiently Serving Your Large Language Models
Author(s): Zoumana Keita Originally published on Towards AI. Serve your large language models just like you would using OpenAI API but at no cost This member-only story is on us. Upgrade to access all of Medium. Photo by Austrian National Library on …
The Zero Redundancy Optimizer (ZeRO): A Short Introduction with Python
Author(s): Armin Norouzi, Ph.D Originally published on Towards AI. Uncover how Zero Redundancy Optimizer transforms data parallelism, boosting memory and computational efficacy. This member-only story is on us. Upgrade to access all of Medium. source: https://www.microsoft.com/en-us/research/blog/zero-deepspeed-new-system-optimizations-enable-training-models-with-over-100-billion-parameters/ The Zero Redundancy Optimizer (ZeRO) improves …
What Are Large Language Models?
Author(s): Youssef Hosni Originally published on Towards AI. Embarking on a Journey with Large Language Models (LLMs) This member-only story is on us. Upgrade to access all of Medium. The world of artificial intelligence has been revolutionized by the emergence of Large …
The Python Decorator That Supercharges Developer Experience 🚀
Author(s): Matan Kleyman Originally published on Towards AI. The Python Decorator That Supercharges Developer Experience U+1F680 Python’s @overload decorator, found in the typing builtin Python module, allows developers to specify multiple type-specific signatures for a function or method. This provides a foundation …
Create Your Own Data Analyst Assistant With Langchain Agents
Author(s): Pere Martra Originally published on Towards AI. Allow me to share my personal opinion on LLM Agents: They are going to revolutionize everything! If you’re already working with Large Language Models, you probably know them. If you’re new to this concept, …
Beach Reading: a Short History of Pre-Trained Models
Author(s): Patrick Meyer Originally published on Towards AI. Step into a world of wonder and amazement as we unravel the captivating tale of artificial intelligence’s incredible journey. From the birth of the first neural network in the 1950s to the rise of …
Query Your DataFrames with Powerful Large Language Models using LangChain.
Author(s): Pere Martra Originally published on Towards AI. Get ready to use your own data with Large Language Models From Hugging Face Using a Vector Database and LangChain! Image By Author, generated with Dall-e 2 In the previous article, I explained how …
Exploring the World of Generative AI, Foundation Models, and Large Language Models: Concepts, Tools, and Trends
Author(s): Claudio Giorgio Giancaterino Originally published on Towards AI. pixabay Artificial Intelligence (AI) has made tremendous strides in recent years, largely driven by advances in Deep Learning. With the advent of ChatGPT last year, the popularity of the Generative AI world increased …
In-Context Learning with Transformer-Based Neural Sequence Models.
Author(s): Jair Ribeiro Originally published on Towards AI. Uncovering the Implicit Implementation of Standard Learning Algorithms in Neural Sequence Models. During my Sunday reading this week, I found this research paper which explores the hypothesis that transformer-based neural sequence models can implicitly …
Pre-train, Prompt, and Predict — Part2
Author(s): Harshit Sharma Originally published on Towards AI. 2 step approach to Prompting (This is Part 2 of a multi-part series describing the prompting paradigm in NLP. The content is inspired by this paper (a survey paper explaining the prompting methods in …
Automated Annotation of Protein Features Using Language Models
Author(s): LucianoSphere Originally published on Towards AI. At UniProt, ProtNLM is already assisting scientists by connecting protein sequences with descriptions of protein traits in the English language Figure by the author. Note PRTEIN SEQVENCE is not a typo but just reflects the …
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