Data scientists and engineers often encounter difficulties when collaborating on machine learning (ML) tasks due to concerns about data reproducibility and traceability. Software code tends to be transparent about its origin and modifications, but it's often hard to ascertain the exact provenance of the data used for training ML models and the transformations conducted.
To tackle…
Researchers from IBM Research have developed a new architecture, dubbed Alignment Studio, which enables developers to mould large language models (LLMs) to fit specific societal norms, laws, values and regulations. The system is designed to mitigate ongoing challenges in the artificial intelligence (AI) sector surrounding issues such as hate speech and inappropriate language.
While efforts…
Researchers from Tsinghua University and Microsoft Corporation have unveiled a groundbreaking study known as LLMLingua-2, as part of a collaborative effort that reinforces the cruciality of interdisciplinary research. The study primarily focuses on improving the efficiency of language models, which play a pivotal role in ensuring fluent communication between humans and machines. The core challenge…
Researchers from HyperGAI have developed a ground-breaking new multimodal language learning model (LLMs) known as Hyper Pretrained Transformers (HPT) that can proficiently handle and process seamlessly, a wide array of input modalities, such as text, images, and videos. Existing LLMs, like GPT-4V and Gemini Pro, have limitations in comprehending multimodal data, which hinders progress towards…
The field of artificial intelligence (AI) has significantly advanced with the development of Large Language Models (LLMs) such as GPT-3 and GPT-4. Developed by research institutions and tech giants, LLMs have shown great promise by excelling in various reasoning tasks, from solving complex math problems to understanding natural language nuances. However, despite their notable accomplishments,…
Rodney Brooks, co-founder of iRobot and keynote speaker at MIT’s “Generative AI: Shaping the Future” symposium, warned attendees not to overestimate the capabilities of this emerging AI technology. Generative AI is used to create new material by learning from data they were trained on, with applications in art, creativity, functional coding, language translation and realistic…
Generative AI technologies have transformed the landscape of search engines, with Microsoft Bing AI and Google Bard AI leading the charge. They use advanced AI models to revolutionise the way we search and interact with online information.
Microsoft Bing AI is an AI-enabled assistant designed to improve our interaction with digital information. It integrates with…
In recent years, heavyweights in the cloud service industry such as AWS (Amazon Web Services), Microsoft Azure, and Google Cloud have emerged as undeniable forces in the realm of Artificial Intelligence (AI). Despite their strong and scalable infrastructure playing a crucial role in AI's expansion, these giants' immense control can often lead to a loss…
Language models such as GPT-3 have demonstrated impressive general knowledge and understanding. However, they have limitations when required to handle specialized, niche topics. Therefore, a deeper domain knowledge is necessary for effectively researching specific subject matter. This can be equated to asking a straight-A high school student about quantum physics. They might be smart, but…
Over several years, successful AI software projects have hinged on algorithms based on Mathematical Programming, Simulation, Heuristics, ML, and generative AI. These projects have returned significant profits for several major organizations. However, many businesses outside the software industry still face challenges in implementing successful AI strategies. In many cases, CDOs may only produce "standard" data…
During the "Generative AI: Shaping the Future" symposium held as part of MIT's Generative AI Week, experts discussed the opportunities and risks of generative AI, a type of machine learning that creates realistic outputs such as images, text, and code. The keynote speaker, Rodney Brooks, co-founder of iRobot and professor emeritus at MIT, warned against…
In the field of Natural Language Processing (NLP), optimizing the Retrieval-Augmented Generation (RAG) pipeline often presents a significant challenge. Developers strive to strike the right balance among various components such as large language models (LLMs), embeddings, query transformations, and re-rankers in order to achieve optimal performance. With a lack of effective guidance and user-friendly tools,…