AI is revolutionizing industries, from healthcare to automotive. You can see its applications everywhere. However, these AI models rely on high-quality training data to function optimally. When you train AI and machine learning models with data that has issues, the outcomes will not be reliable. Biased results, inaccurate predictions, and poor performance can plague your AI project and make your AI model inflexible and inefficient.
In recent years, the paradigm of video data has undergone a shift, transitioning from a mere conduit for moving images to a vital source of acquiring actionable insights. Although industries like surveillance, healthcare, automotive, entertainment, or retail have long leveraged video, its contemporary importance stems from its role as a primary data source for cutting-edge AI solutions.
Until recently, a majority of data annotation for training AI models was carried out manually, which invited the usual challenges that come with human intervention. Manual data annotation is prone to a variety of biases and errors and is also time-consuming.
Language played a pivotal role in the ascendancy of humans over (other) animals. It enabled thoughts and ideas to be transferred from one generation to the next thus allowing successive generations to improvise and progress. Writing gave this a boost and the internet supercharged it.
The launch of ChatGPT in late 2022, and the subsequent discussion on artificial intelligence (AI) and, to a lesser degree, machine learning (ML) engendered something inherent in humans: fear. There were apprehensions about AI becoming super intelligent and taking over the human race—with some even calling for a moratorium on AI experiments, or shutting the whole thing down entirely.
Social media networks are an essential feature of contemporary living- for individuals, professionals, and communities alike. However, these platforms also serve as a breeding ground for instances of bullying, hate speech, and false news. Many social networks increasingly rely on social media content moderation, which is the process of assessing and eliminating objectionable or illegal content, to tackle this issue.
Video annotation is essential to improve the performance of many AI-based models and projects. Video annotation helps in achieving correct datasets to train machines and different models. In this blog post, we have talked about what is video annotation and how different types of video annotation techniques can benefit various organizations and businesses.
Like humans, machines also need to learn, understand and analyze things to produce desirable outcomes. One of the most efficient ways to make machines learn is using text annotation services. With advancements in time and technology, machines have leveled up their ability to understand human language.
Our eyes are the windows to the outside world for us. We recognize objects and people through them, aiding in navigating the world. It helps give us an understanding of our standing with respect to our surroundings. We can then take the necessary action that brings us closer to the objective.
Living a conscious life and aiming for sustainable development should be our focus as human beings. Cutting down on carbon emission is a global objective for the generation. Paper plays an important role in our lives and digital medium can be a great alternative to store data and decrease paper dependency. Text Summarization is one such process that should be adopted for its numerous benefits. The article explains all about this technology and how it can change your life.