The number of AI tools users in the 'AI Tool Users' segment of the artificial intelligence market worldwide was modeled to stand at ************** in 2024. Following a continuous upward trend, the number of AI tools users has risen by ************** since 2020. Between 2024 and 2031, the number of AI tools users will rise by **************, continuing its consistent upward trajectory.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Artificial Intelligence.

Global Total Number of Scientific Publications in Artificial Intelligence Share by Country (Units (Publications)), 2023 Discover more data with ReportLinker!

The number of Artificial Intelligence (AI) tool users in Poland amounted to approximately *********** in 2024. Their AI users are forecast to rise to over **** million in 2030.

Forecast: Number of Scientific Publications in Artificial Intelligence in the US 2024 - 2028 Discover more data with ReportLinker!

Forecast: Number of Scientific Publications in Artificial Intelligence in Thailand 2024 - 2028 Discover more data with ReportLinker!

Forecast: Number of Scientific Publications in Artificial Intelligence in France 2024 - 2028 Discover more data with ReportLinker!

In the decade since 2014, Google has produced, by far, the largest amount of notable AI models or some *** models. That leaves them with nearly twice the number of models as the next competitor, Meta. While this is a significant number, Google does also routinely cut projects or fold older projects into newer ones, which could inflate the number given.

Industry is the key driver of notable AI models globally, with more than ** notable models produced since 2003. The importance of industry can be seen in the fact that no other collaboration or cooperation has produced a notable AI model.

The dataset is generated based on 5 different filters, i. Gaussian blur (sigma=2.5), ii. width and height shift range=0.2, iii. Rotation range <10, iv. zoom range=0.4, and v. brightness between [0.4,1.5].

The dataset is 40 x 28 pixels and the total number is 8851 images.

The ".csv" file is the labeled dataset which the first column shows the label and the rest columns are the value of the grayscale image.

Forecast: Number of Scientific Publications in Artificial Intelligence in Finland 2024 - 2028 Discover more data with ReportLinker!

The MNIST dataset is a dataset of handwritten digits. It is a popular dataset for machine learning and artificial intelligence research. The dataset consists of 60,000 training images and 10,000 test images. Each image is a 28x28 pixel grayscale image of a handwritten digit. The digits are labeled from 0 to 9.

The United States remains the most prolific producer of notable AI models across the globe in 2024 with some ** models of exceptional capabilities produced. The next competitor is China with ** and Europe as a region contains just around *****.

Forecast: Number of Scientific Publications in Artificial Intelligence in China 2024 - 2028 Discover more data with ReportLinker!

Forecast: Total Number of Scientific Publications in Artificial Intelligence in Canada 2024 - 2028 Discover more data with ReportLinker!

Forecast: Number of Scientific Publications in Artificial Intelligence in Egypt 2024 - 2028 Discover more data with ReportLinker!

Forecast: Total Number of Scientific Publications in Artificial Intelligence in Saudi Arabia 2024 - 2028 Discover more data with ReportLinker!

Forecast: Number of Scientific Publications in Artificial Intelligence in India 2024 - 2028 Discover more data with ReportLinker!

Forecast: Total Number of 10% Top-Cited Scientific Publications in Artificial Intelligence in the UK 2024 - 2028 Discover more data with ReportLinker!

Forecast: Total Number of Scientific Publications in Artificial Intelligence in Singapore 2024 - 2028 Discover more data with ReportLinker!

Most respondents, or ** percent, expected the service operation aspect of business to most likely decrease in employees in 2023. Decrease was widely considered to be the most likely aspect of generative AI adoption, though little or no change was also an expected outcome. The increase in staff needs due to generative AI adoption was considerably lower than expectations of decreased employee levels.