Large Language Models (LLMs) are Deep Learning models trained to produce text. With this impressive ability, LLMs have become the backbone of modern Natural Language Processing (NLP). Traditionally, they are pre-trained by academic institutions and big tech companies such as OpenAI, Microsoft and NVIDIA. Most of them are then made available for public use. This plug-and-play … [Read more...] about Choosing The Right Language Model For Your NLP Use Case
Natural Language Processing
DALL·E 2, Explained: The Promise And Limitations Of A Revolutionary AI
DALL·E 2 is the newest AI model by OpenAI. If you’ve seen some of its creations and think they’re amazing, keep reading to understand why you’re totally right — but also wrong. OpenAI published a blog post and a paper entitled “Hierarchical Text-Conditional Image Generation with CLIP Latents” on DALL·E 2. The post is fine if you want to get a glimpse at the results … [Read more...] about DALL·E 2, Explained: The Promise And Limitations Of A Revolutionary AI
Transformers And Multimodal: The Same Key For All Data Types
The world of Machine Learning is undoubtedly fascinating, constantly growing, and capable of touching the most diverse sectors, from medicine to space racing, from catering to big manufacturing. There are countless fields of application for this technology and just as many techniques that have been developed over the decades, but they all have one thing in common: … [Read more...] about Transformers And Multimodal: The Same Key For All Data Types
10 Leading Language Models For NLP In 2022
UPDATE: We have published the updated version of this article with the top 10 transformative LLM research papers from 2023. The introduction of transfer learning and pretrained language models in natural language processing (NLP) pushed forward the limits of language understanding and generation. Transfer learning and applying transformers to different downstream NLP tasks … [Read more...] about 10 Leading Language Models For NLP In 2022
Unconstrained Chatbots Condone Self-Harm
WARNING. This post contains references to self-harm and suicide. It includes conversations between a human and DialoGPT, with the sole purpose of surfacing the danger of uncontrolled AI. If you or a loved one are dealing or have dealt with suicidal thoughts, I suggest skipping this article. In the context of an accelerating mental health crisis, Natural Language … [Read more...] about Unconstrained Chatbots Condone Self-Harm
Construct A Biomedical Knowledge Graph With NLP
I have already demonstrated how to create a knowledge graph out of a Wikipedia page. However, since the post got a lot of attention, I’ve decided to explore other domains where using NLP techniques to construct a knowledge graph makes sense. In my opinion, the biomedical field is a prime example where representing the data as a graph makes sense as you are often analyzing … [Read more...] about Construct A Biomedical Knowledge Graph With NLP
Can Too Much BERT Be Bad for You?
BERT and GPT-2: we all love language models… I mean, who doesn’t? Language models like BERT and GPT-2 (and GPT-3) have had an enormous impact on the entire NLP field. Most of the models that obtained groundbreaking results on the famous GLUE benchmark are based on BERT. I, too, have benefited from BERT, since I released a library for topic modeling and some HuggingFace … [Read more...] about Can Too Much BERT Be Bad for You?
On The Gap Between Adoption And Understanding
This blog post describes our recent paper: Federico Bianchi and Dirk Hovy (2021). On the Gap between Adoption and Understanding in NLP. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. The main focus of this work is to describe issues that currently affect NLP research and hinder scientific development. NLP is driven by … [Read more...] about On The Gap Between Adoption And Understanding
Topical Language Generation With Transformers
Full Paper Codes Large-scale transformer-based language models (LMs) demonstrate impressive capabilities in open text generation. However, controlling the generated text’s properties such as the topic, style, and sentiment is challenging and often requires significant changes to the model architecture or retraining and fine-tuning the model on new supervised data. We … [Read more...] about Topical Language Generation With Transformers
The Secret Guide To Human-Like Text Summarization
Summarization has become a very helpful way of tackling the issue of data overburden. In my earlier story, I shared how you can create your personal text summarizer using the extractive method — if you have tried that, you may have noticed that, because no new sentences were generated from the original content, at times you may have difficulties understanding the generated … [Read more...] about The Secret Guide To Human-Like Text Summarization