neural network

Does the following routine sound familiar? In the morning, your voice assistant gives you today's weather forecast. And then, on your way to work, a navigation app gives you real-time traffic updates, and in the evening, a cooking app helps you cook up dinner with audible steps. In such a routine, machine-generated voice plays an integral part, creating an engaging, personalized experience. The technology that powers this is called text-to-speech, or TTS for short. It is a kind of assistive technology reading aloud…

What Is Text Classification? Text classification is a machine learning subfield that teaches computers how to classify text into different categories. It's commonly used as a supervised learning technique, which means that the algorithm is trained on a set of texts that have already been labeled with their respective categories. Once it's been trained on this data, the algorithm can use what it's learned to make predictions about new, unlabeled texts. The algorithm looks for patterns in the text to determine which…

Geoffrey Hinton was an artificial intelligence pioneer. In 2012, Hinton and two of his graduate students at the University of Toronto created technology that became the intellectual foundation for the AI systems that the tech industry's biggest companies believe is a key to their future.On Monday, however, he officially joined a growing chorus of critics who say those companies are racing toward danger with their aggressive campaign to create products based on generative AI, the technology that powers popular chatbots…

As we have seen in our previous article, artificial intelligence (AI) is transforming many aspects of our lives, including the world of art. With the help of machine learning algorithms and generative models (i.e., a machine “learns” a piece of information and uses it to generate a new image), AI can now create works of art that are often indistinguishable from those created by human artists. AI-generated images are a type of art that is generated through algorithms that analyze patterns and styles in existing art and use…

Over the past decade, neural networks have succeeded immensely in various industries. However, the black-box nature of their predictions has prevented their broader and more reliable adoption in fields such as health and security. This has led researchers to investigate ways to explain neural network decisions.  One approach to explaining neural network decisions is through saliency maps, which highlight areas of the input that a neural network uses most while making a prediction. However, these methods often produce…

Colossal hype ensues whenever there's progress or even the slightest shift in the world of machine learning (ML). When it comes to AI, the craze always ends up growing out of proportion and insane claims invariably follow. You've probably noticed this recently as more people are beginning to use Midjourney, ChatGPT, Copilot, and so on. The truth about these systems, however, is always more prosaic. Machine learning is mathematical, and the real implications of the ML models are not nearly as profound as some bloggers…

Machine learning (ML) has revolutionized various industries by enabling data-driven decision-making along with the automation of certain tasks. For instance, many banking institutions deploy advanced machine-learning models to detect fraudulent transactions. These models need to evolve constantly otherwise there will be a steep rise in false positives. However, deploying new machine learning models in production can be challenging. Training the model on production data, deploying it, and maintaining it isn’t easy. Many a…

LLMs do Natural Language Processing (NLP) to represent the meaning of the text as a vector. This representation of the words of the text is an embedding. The Token Limit: The LLM Prompting Biggest Problem Currently, one of the biggest problems with LLM prompting is the token limit. When GPT-3 was released, the limit for both the prompt and the output combined was 2,048 tokens. With GPT-3.5, this limit increased to 4,096 tokens. Now, GPT-4 comes in two variants. One with a limit of 8,192 tokens and another with a limit of…

Rapid development in machine learning and AI technologies have made significant progress in computer vision for object detection and recognition. Yet creating a system that can recognize humor and amusement in people is still a challenging problem for programmers, since comedy and entertainment are subjective and based on personal tastes and cultural context. Thus, it is tricky creating a system that can precisely determine what individuals find amusing or enjoyable. However, computer vision in facial recognition and…

Whether you’re just getting started or have been working with AI models for a while, there are some common machine learning and deep learning mistakes we all need to be aware of and reminded of from time to time. These can cause major headaches down the road if left unchecked! If we pay close attention to our data, model infrastructure, and verify our outputs as well we can sharpen our skills in practicing good data scientist habits. Machine Learning and Deep Learning Data Mistakes to Avoid When getting started in…