GPT-3, also known as the third generation Generative Pre-trained Transformer is a neural network machine-learning model that uses internet data to generate any kind of text. Developed by OpenAI, it requires very little input text to produce large volumes of machine-generated text that is relevant and sophisticated. OpenAI was founded in 2015 as an independent...
Tag: machine learning
Ten App Trends for 2022
Artificial intelligence carries a huge upside. But potential harms need to be managed
Transfer Learning – Small Data with big Effects
For many people artificial intelligence is synonymous with big data. This is because large data sets are the foundation of some of the most important AI breakthroughs over the past decade. ImageNet is a data set that contains millions of images, each hand-sorted into thousands of categories. Image classification has made huge strides since the...
There are fundamental Problems how we train AI
The current machine learning training and testing process is not rigorous enough to ensure that the models being trained will work in the real world. During the training process many different models can be produced that all perform equally well when tested in lab settings and differ only in small, arbitrary ways. The differences stem...
Prepare for Artificial Intelligence to Produce Less Wizardry | WIRED
It has become very expensive to train modern networks; in fact it has become so expensive, that some companies are choosing not to use AI methods at all. A new research paper by Neil Thompson et. al. argues that it is, or will soon be, impossible to keep increasing computational power at rate needed to...
AI Ethics Reading | AI Truth.org
If you want to take a deep dive into AI and ethics, go to AI Ethics Reading | AI Truth.org for an overview of critical surveys, papers, books from AI experts. It’s definitely worth checking out :-). Photo by h heyerlein on Unsplash
DeepMind’s Losses and the Future of Artificial Intelligence | WIRED
If you look at AI from a purely business point of view, Alphabet’s DeepMind last year’s loss of $572 million should make you worry. Especially, when considering the rising magnitude of DeepMind’s losses: $154 million in 2016, $341 million in 2017 and $572 million in 2018. Basically, you need to have really deep pockets to...
Almost 80% of AI and ML Projects Have Stalled, Survey Says – Robotics Business Review
Doing an AI project is hard. The main obstacle is the volume and quality of the training data, so Nathaniel Gates, CEO and co-founder of Alegion While large companies (more than 100,000 employees) are the most likely to have an AI strategy, only 50% of them currently have one, according to MIT Sloan Management Review....