What is a state of the art algorithm?

The state of the art (sometimes cutting edge or leading edge) refers to the highest level of general development, as of a device, technique, or scientific field achieved at a particular time.

What is the state of the art in machine learning?

A newly discovered challenge to ML is the Rashomon effect, which means that data are possibly generated from a mixture of heterogeneous sources. A simple classification standard can shed light on emerging forms of ML.

What is state of the art equipment?

adjective [usually ADJECTIVE noun] If you describe something as state-of-the-art, you mean that it is the best available because it has been made using the most modern techniques and technology. the production of state-of-the-art military equipment.

What is a state of the art paper?

State of the art papers reflect the present state of scientific or engeneering development. Review papers reflect a broader view: history, development, and present state of scientific development.

Is transformer state of the art?

A Transformer is a deep learning model that adopts the mechanism of attention, differentially weighing the significance of each part of the input data. It is used primarily in the field of natural language processing (NLP) and in computer vision (CV).

Is Bert a transformer?

Bidirectional Encoder Representations from Transformers (BERT) is a transformer-based machine learning technique for natural language processing (NLP) pre-training developed by Google. BERT was created and published in 2018 by Jacob Devlin and his colleagues from Google.

What are the different types of problems in Artificial Intelligence?

One of the biggest Artificial Intelligence problems is data acquisition and storage. Business AI systems depend on sensor data as its input. For validation of AI, a mountain of sensor data is collected. Irrelevant and noisy datasets may cause obstruction as they are hard to store and analyze.

What are some of the best performing machine learning algorithms?

In Language Modeling one of the best performing algorithms can be found in Megatron-LM. This model and the paper were first presented in 2019 by the Nvidia team. A model similar to GPT-2 was trained on 8300 billion params. It was able to reduce the current state-of-the-art score of 15.8 to a test perplexity of only 10.8.

What are some of the most promising algorithms in machine translation?

One of the most promising algorithms in this field is the Transformer Big +BT. It was presented in this paper in 2018 by the Google Brain Team. In general, Transformers are state-of-the-art for dealing sequences and for machine translation. Transformers do not use recurrent connections but parse instead sequences simultaneously [7].

What are the best data analysis methods for machine learning?

Deep learning and topological data analysis (TDA) are two promising methods with a lot of current research. Deep learning works particularly well on image/NLP data or very large datasets. TDA has a host of unsupervised learning tools, visualization techniques, and even predictive modeling/statistical testing capabilities.

What is the most accurate classification algorithm in 2019?

One of the current leading algorithms is BERT which achieved an accuracy of 55.5 on the SST-5 Fine-grained classification dataset in 2019. The original paper was published by the Google AI Team [5]. BERT stands for Bidirectional Encoder Representations from Transformers and applies a bidirectional training of the Transformer technique.