Artificial Intelligence and its subset Machine Learning are at the heart of innovation for digitally transformed businesses. However, ML, in particular, needs to be highly interoperable for smart technologies to be truly disruptive and innovative at scale.
If there was no interoperability, AI development would be limited and only accessible to big tech. This is because only tech giants have access to the necessary resources and, more importantly, the most data that makes continuous and meaningful learning possible.Read more
Text-to-speech (TTS) – this term is virtually self-explanatory: With a text-to-speech service you can convert written text into spoken words. The programs used are being continually further developed. Although there are still no applications today in which the machine origin of the spoken word is not discernible, the technological progress is unstoppable. And with every improvement of the technology, these systems will be able to create more and more natural sounding voices.
What are the advantages of text-to-speech systems? Most importantly, vision-impaired people can benefit from those systems. In addition, they can also be used by companies as a means of expanding their outreach.
Machine learning algorithms can be applied to a number of tasks, including decision-making and data mining. It’s critical to select the appropriate machine learning software and hardware for the work at hand because there are a variety of options available. To evaluate how well a machine learning algorithm is performing, a variety of model assessments can be used. The proper machine learning algorithm should be selected for the task at hand after being aware of the limits of each one.
Natural Language Processing (NLP) is a subfield of Artificial Intelligence that deals with the interaction between humans and computers using natural language.
NLP data sets are used to train models that can then be used for various tasks such as text classification, entity recognition, machine translation, etc.
There are many different applications of NLP, and in this post we will take a look at some of the most popular and the importance of NLP data sets for training applications.
Data preprocessing is one of the early steps of creating and utilizing a machine learning model. In this step, the raw data is prepared to be suitable for feeding to the machine learning model. It is often the first step undertaken when creating a machine learning project, as the availability of clean and well-formatted data is not always possible.Read more
Speech recognition is becoming a popular “must have” feature. It has been around for over 50 years and developed by several companies in the United States, Europe, Japan and China. But what people don’t know is that it also requires a lot of work behind the scenes to make speech recognition possible as well as practical.Read more
Despite the popularity of typing, writing by hand is still very common. In fact, a study by Michigan State University found that students who took notes by hand had a better understanding of the material than those who typed their notes. The researchers believe this is because handwriting allows for a more personal connection to the material, which results in a deeper understanding. This emphasis on handwritten notes is even more important in the field of artificial intelligence (AI), where it is crucial to have an intimate understanding of data in order to train AI systems effectively. In this blog post, we will explore one particular handwriting dataset and its applications in the training of AI systems.Read more
Waves of ML/AI are already impacting industries like Information Technology (IT), Financial Technology (FinTech), Healthcare Technology (HealthTech), Education Technology (EdTech), and others. Companies are more laser-focused on AI value, moving beyond the testing phase and concentrating on rapidly expanding their usage of AI.Read more
Artificial intelligence (AI) is transforming the industry by automating tasks and making them more efficient. The food industry is one of those fields where AI can make an incredible impact on day-to-day operations–and ultimately transform your business in a major way! Automation will allow us to continue providing a diverse menu, but also make it easier for consumers to find products that align with their tastes. The human touch remains important in all aspects of food service, as well as quality control through data-driven recommendations from intelligent machines.Read more
The business world is quickly becoming aware of the potential for artificial intelligence (AI) to improve efficiency and create value. Many companies are looking into how they can incorporate AI into their operations, but few have the expertise or resources to do so. That’s where whitepapers on AI come in. Whitepapers are documents that outline best practices and strategies for implementing a certain technology or methodology. They are created by subject matter experts in the field, making them an invaluable resource for businesses looking to get up to speed on Artificial Intelligence.
Thankfully, there are plenty of excellent whitepapers on AI available online, completely free of charge. In this blog post, we’ll provide an overview of some of the best AI white papers out there.Read more