Why Knowledge Graphs Are Central to Industry 4.0 Initiatives
We are in the midst of a major technological inflection point: knowledge graphs have developed into a foundational component of the modern Industry 4.0 technology
We are in the midst of a major technological inflection point: knowledge graphs have developed into a foundational component of the modern Industry 4.0 technology
Artificial intelligence (AI) and machine learning (ML) have become a driving force of innovation in recent years. In 2022 alone, large language models like OpenAI’s
If you’re a data scientist or you work with machine learning (ML) models, you have tools to label data, technology environments to train models, and
OpenAI has just announced an enterprise version of its popular generative AI product, ChatGPT. But in this case, OpenAI is a fast follower — not
To say that it’s challenging to achieve AI at scale across the enterprise would be an understatement. An estimated 54% to 90% of machine learning
There’s no such thing as a standard end-to-end data science journey. With organisations across every industry facing a series of specific challenges when it comes
Hashing is a core operation in most online databases, like a library catalogue or an e-commerce website. A hash function generates codes that replace data
AI is looking to significantly impact the future global search engine market as powerhouses Microsoft, using OpenAI ChatGPT, and Google, with LaMDA technology, compete to
Natural language processing (NLP) is a subset of AI which finds growing importance due to the increasing amount of unstructured language data. The rapid growth
Vodafone leverages Google Cloud to deploy AI/ML use cases at scale As one of the largest telecommunications companies worldwide, Vodafone is working with Google Cloud
A recent study suggests that denying AI decision makers access to sensitive data actually increases the risks of discriminatory outcome. That’s because the AI draws
With the rise of artificial intelligence, machine learning and big data, organizations have become increasingly aware of the importance of MLOps (Machine Learning Operations), ModelOps,
Machine Learning is a subset of Artificial Intelligence that enables machines to learn and make predictions from data, without being explicitly programmed. The main difference between traditional programming and machine learning is that traditional programming requires the programmer to specify all rules for the program, while machine learning uses algorithms and data samples to build models that can identify patterns in data and make predictions or decisions with a minimal human intervention needed.
With machine learning, data analysis, and predictive modeling can be done in an automated way, reducing the amount of manual work required. Furthermore, machine learning algorithms can self-improve over time as they learn from the data they meet. As a result, it is an invaluable instrument for comprehending complex patterns in data that would otherwise be extremely difficult to discover. It can also be used to forecast future outcomes based on past data, allowing you to create models customized to your particular requirements.
Machine learning models are trained using large amounts of data, including but not limited to numerical data, categorical data, text data, image data, and audio/video data. Data scientists use these various types of data to train models that can accurately predict outcomes or classify items according to their attributes. They also use deep learning methods, which enable machines to learn from experience and adjust their strategies accordingly.