Deep learning and artificial intelligence (AI) have influenced autonomous vehicle technology significantly over the past ten years. Self-driving vehicles rely on advanced decision-making systems that read data from sensors to navigate autonomously. As AI grows, these systems have increased in complexity, with modules dedicated to perception, path planning, behavior arbitration, and motion control. Deep learning…
Computational biology, an essential field that merges biological research and computer science, has been focusing intently on predicting biomolecular structures. The ability to predict such structures accurately can have immense implications in understanding cellular functions and developing new medical therapies. Despite the complex nature of this discipline, it is instrumental in studying proteins, nucleic acids,…
The researchers from Huazhong University of Science and Technology, the University of New South Wales, and Nanyang Technological University have unveiled a novel framework named HalluVault, aimed at enhancing the efficiency and accuracy of data processing in machine learning and data science fields. The framework is designed to detect Fact-Conflicting Hallucinations (FCH) in Large Language…
Neuromorphic Computing, Quantum Computing for AI, Explainable AI (XAI), AI-augmented Design and Creativity, Autonomous Vehicles and Robotics, AI in Cybersecurity, and AI for Environmental Sustainability are the seven key areas where AI advancements are considerably changing several sectors.
Neuromorphic Computing is a technology that is designed to mirror the structure and functioning of the human brain.…
Understanding and processing Hebrew language has always been a challenge due to its morphologically rich structure and the use of prefixes, suffixes, and infixes that change the meaning and tense of words. This has posed particular challenges for AI language models, which often struggle to interpret the subtleties of lesser-known, low-resource languages accurately. Addressing this…
Language models play a crucial role in advancing artificial intelligence (AI) technologies, revolutionizing how machines interpret and generate text. As these models grow more intricate, they employ vast data quantities and advanced structures to improve performance and effectiveness. However, the use of such models in large scale applications is challenged by the need to balance…
"Finetuned adapters" play a crucial role in generative image models, permitting custom image generation and reducing storage needs. Open-source platforms that provide these adapters have grown considerably, leading to a boom in AI art. Currently, over 100,000 adapters are available, with the Low-Rank Adaptation (LoRA) method standing out as the most common finetuning process. These…
AI21 Labs has launched a new model, the Jamba-Instruct, which is designed to revolutionize natural language processing tasks for businesses. It does this by improving upon the limitations of traditional models, particularly their limited context capabilities. These limitations affect model effectiveness in tasks such as summarization and conversation continuation.
The Jamba-Instruct model significantly enhances this capability…
AI21 Labs has unveiled its Jamba-Instruct model, a solution designed to tackle the challenge of using large context windows in natural language processing for business applications. Traditional models usually have constraints in their context capabilities, impacting their effectiveness in tasks such as summarising lengthy documents or continuing conversations. In contrast, Jamba-Instruct overcomes these barriers by…