With the surge in global tourism, the demand for AI-driven travel assistants is rapidly growing. These systems are expected to generate practical and highly customized itineraries to individual preferences, including dynamic factors such as real-time data and budget constraints. The role of AI in this area is to improve the efficiency of the planning process… →
Large language models (LLMs) have gained significant attention in the field of artificial intelligence, primarily due to their ability to imitate human knowledge through extensive datasets. The current methodologies for training these models heavily rely on imitation learning, particularly next token prediction using maximum likelihood estimation (MLE) during pretraining and supervised fine-tuning phases. However, this… →
Speech tokenization is a fundamental process that underpins the functioning of speech-language models, enabling these models to carry out a range of tasks, including text-to-speech (TTS), speech-to-text (STT), and spoken-language modeling. Tokenization offers the structure required by these models to efficiently analyze, process, and create speech by turning raw speech signals into discrete tokens. Tokenization… →
Deep learning has made significant strides in artificial intelligence, particularly in natural language processing and computer vision. However, even the most advanced systems often fail in ways that humans would not, highlighting a critical gap between artificial and human intelligence. This discrepancy has reignited debates about whether neural networks possess the essential components of human… →
Artificial intelligence (AI) has made significant strides in recent years, especially with the development of large-scale language models. These models, trained on massive datasets like internet text, have shown impressive abilities in knowledge-based tasks such as answering questions, summarizing content, and understanding instructions. However, despite their success, these models need help regarding specialized domains where… →
Human and primate perception occurs across multiple timescales, with some visual attributes identified in under 200ms, supported by the ventral temporal cortex (VTC). However, more complex visual inferences, such as recognizing novel objects, require additional time and multiple glances. The high-acuity fovea and frequent gaze shifts help compose object representations. While much is understood about… →
The ability of vision-language models (VLMs) to comprehend text and images has drawn attention in recent years. These models have demonstrated promise in tasks like object detection, captioning, and image classification. However, it has frequently proven difficult to fine-tune these models for particular tasks, particularly for researchers and developers who require a streamlined procedure to… →
Reinforcement learning (RL) enables machines to learn from their actions and make decisions through trial and error, similar to how humans learn. It’s the foundation of AI systems that can solve complex tasks, such as playing games or controlling robots, without being explicitly programmed. Learning RL is valuable because it opens doors to building smarter,… →