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We’re testing the ability for ChatGPT to remember things you discuss to make future chats more helpful. You’re in control of ChatGPT’s memory.

The exploration of augmenting large language models (LLMs) with the capability to understand and process audio, including non-speech sounds and non-verbal speech, is a burgeoning field. This area of research aims to extend the applicability of LLMs from interactive voice-responsive systems to sophisticated audio analysis tools. The challenge, however, lies in developing models that can…

Developing models capable of understanding and generating sequences has become a cornerstone of progress. Among these, transformers have emerged as the gold standard, celebrated for their ability to capture the intricacies of language and other sequential data with unparalleled precision. This prominence is set against a backdrop of continuous exploration for models that promise both…

Personalized image generation is the process of generating images of certain personal objects in different user-specified contexts. For example, one may want to visualize the different ways their pet dog would look in different scenarios. Apart from personal experiences, this method also has use cases in personalized storytelling, interactive designs, etc. Although current text-to-image generation…

In the rapidly evolving field of audio synthesis, a new frontier has been crossed with the development of Stable Audio, a state-of-the-art generative model. This innovative approach has significantly advanced our ability to create detailed, high-quality audio from textual prompts. Unlike its predecessors, Stable Audio can produce long-form, stereo music, and sound effects that are…

The vast amount of online information makes it difficult for individuals to find, read, and understand the information they need efficiently. There have been attempts to address this issue through various tools and services designed to help users manage and digest online content. These range from simple bookmarking tools that organize content to more complex…

The quest to enhance Large Language Models (LLMs) has led to a groundbreaking innovation by a team from the Beijing Academy of Artificial Intelligence and Gaoling School of Artificial Intelligence at Renmin University. This research team has introduced a novel methodology known as Extensible Tokenization, aimed at significantly expanding the capacity of LLMs to process…

In the annals of computational history, the journey from the initial mechanical calculators to Turing Complete machines has been revolutionary. While impressive, early computing devices, such as Babbage’s Difference Engine and the Harvard Mark I, lacked the Turing Completeness—a concept defining systems capable of performing any conceivable calculation given adequate time and resources. This limitation…

Deep convolutional neural networks (DCNNs) have been a game-changer for several computer vision tasks. These include object identification, object recognition, image segmentation, and edge detection. The ever-growing size and power consumption of DNNs have been key to enabling much of this advancement. Embedded, wearable, and Internet of Things (IoT) devices, which have restricted computing resources…

Time Series forecasting is an important task in machine learning and is frequently used in various domains such as finance, manufacturing, healthcare, and natural sciences. Researchers from Google introduced a decoder-only model for the task, called TimeFM, based on pretraining a patched-decoder style attention model on a large time-series corpus comprising both real-world and synthetic…