Trending this week: Google’s LaMDA model to enhance chatbots; A new AI-based theory that explains your weird dreams; Smart toilets that analyze your stool for diseases through AI; Deep learning-Based recommender systems.
Every week we analyze the most discussed topics on Twitter by Data Science & AI influencers.
The following topics, URLs, resources, and tweets have been automatically extracted using a topic modeling technique based on Sentence BERT, which we have enhanced to fit our use case.
This week, Data Science and AI influencers on Twitter have talked about:
- Deep Learning Updates
- Disruptive AI Applications
- Tech Trends
The following sections provide all the details for each topic.
Deep Learning Updates
This week, influencers have shared some deep learning updates related to natural language processing, computer vision, and other domains.
Amongst all the resources visited, we have retained the following ones that were shared by Dr. Ganapathi Pulipaka:
A post introducing Google’s new conversational machine learning: LaMDA, short for “Language Model for Dialogue Applications (LaMDA)” that Promises to Elevate the Common Chatbot. LaMDA — like Google’s BERT and MUM, and like external models such as GPT-3 — is based on the Transformer neural network architecture Google developed in 2017. But, unlike these other models, LaMDA focuses on dialogue processing for conversation.
A link to a Github repository containing an Open Neural Network Exchange (ONNX) Model Zoo, a collection of pre-trained, state-of-the-art models in the ONNX format. ONNX is an open format built to represent machine learning models in order to enable AI developers to use them with a variety of frameworks, tools, runtimes, and compilers. Accompanying each model are Jupyter notebooks for model training and running inference with the trained model.
An article talking about Deep Learning-Based Recommender Systems. This post recalls how traditional recommendation systems work, and then presents the more complex deep learning-based ones. This post presents the principal feature that differs DL-based recommender systems from traditional ones, and finally provides the main pros and cons of the first.
Disruptive AI Applications
Some amazing artificial intelligence use cases have been shared on Twitter this week. These examples of applications of AI could represent major breakthroughs in the research domain and transform our lives.
Here follows a collection of them shared by Nige Willson:
An article titled “Smart Toilets Will Soon Analyse Your Stool for Diseases Through Artificial Intelligence”. This post presents a study that explains how researchers are developing a new artificial intelligence tool that can be added to the standard toilet to help analyze patients’ stools and give gastroenterologists the information they need to provide appropriate treatment. This study indicates that the new technology could assist in managing chronic gastrointestinal issues such as inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS).
A post that talks about a new AI-based theory that explains your weird dreams. This article cites a new paper that suggests that dreaming helps us generalize our experiences so that we can adapt to new circumstances. According to this theory, the strangeness of dreams is what makes them useful. This post asserts that this idea is supported by some data, though new experiments could help confirm it.
An article titled titled “Artificial intelligence system can predict the impact of research”. This post talks about an artificial intelligence system trained on almost 40 years of journals that correctly identified 19 out of 20 research papers that have had the greatest scientific impact on biotechnology — and has selected 50 recent papers it predicts will be among the top 5% of biotechnology papers in the future. According to this post, Scientists say the system could be used to find hidden gems of research overlooked by other methods, and even to guide decisions on funding allocations so that it will be most likely to target promising research.
This week again, AI influencers have shared some links to publications presenting some technological projections.
The article talks in greater detail about Digitalism, Antitrust Laws, and Quantum Computing and Neural Networks at the Speed of Light.
Ipfconline shared an article on the Best Programming Languages to Learn in 2021. It talks about the best programming languages to learn in 2021. Of course, there are a lot of programming languages out there and you may have a different approach!