Inception, Cerebras, and MBZUAI have released Jais 2, a 70 billion parameter open-weight Arabic LLM. Jais 2 is trained on an Arabic-first dataset and features a redesigned architecture for stronger reasoning and fluency across Arabic dialects and English. It integrates a safety-first framework and demonstrates capabilities in understanding Arabic poetry, culture, and social media tone. Why it matters: Jais 2 addresses the historical underrepresentation of Arabic in AI by providing a culturally and linguistically faithful model, potentially accelerating innovation across the region.
The Inception Team presented a system for Semantic Question Similarity in Arabic as part of the NSURL 2019 Task 8. The system explores different methods for determining question similarity in Arabic. Their best result was an ensemble model using a pre-trained multilingual BERT model, achieving a 95.924% F1-Score and ranking first among nine participating teams. Why it matters: This demonstrates strong performance on a key Arabic NLP task, advancing the state-of-the-art in semantic understanding for the language.
KAUST hosted the KAUST Research Conference: Advances in Well Construction with Focus on Near-Wellbore Physics and Chemistry from November 7 to 9. The conference was co-chaired by Eric van Oort, a professor at UT Austin, and Tadeusz Patzek, director of the University’s Upstream Petroleum Engineering Research Center. Attendees included professors from the University of Queensland and UT Austin, and directors from GenesisRTS and Labyrinth Consulting Services, Inc. Why it matters: The conference facilitates international collaboration on advancements in petroleum engineering and well construction technologies, which are strategically important for Saudi Arabia.
KAUST Discovery highlighted Prof. Karl Leo's insights on translating science into business from an Entrepreneurship Center speaker series. Prof. Leo, with 440 publications and 8 co-founded companies, emphasized the importance of curiosity-driven basic research. He envisions organic semiconductors dominating electronics in 20-30 years, noting the success of Novaled, his OLED company in Dresden. Why it matters: This underscores KAUST's focus on fostering entrepreneurship and translating research into practical applications within the Kingdom.
Giulio Tononi, director of the Wisconsin Institute for Sleep and Consciousness, lectured at KAUST's 2019 Winter Enrichment Program on the topic of consciousness. He discussed how consciousness is not just about the environment, citing examples such as dreaming and brain activity in vegetative states. Tononi proposed five axioms to better understand consciousness: intrinsic existence, composition, information, integration, and exclusion. Why it matters: The lecture highlights KAUST's engagement with fundamental questions in neuroscience and cognitive science, showcasing the university's interdisciplinary approach to research.
G42's Inception has open-sourced Jais, a 13-billion parameter Arabic large language model (LLM). Jais was trained on a 395-billion-token Arabic and English dataset and outperforms existing Arabic models. The model is a collaboration between Inception, MBZUAI, and Cerebras Systems, and was trained on the Condor Galaxy supercomputer. Why it matters: This release establishes a new standard for Arabic language AI, providing over 400 million Arabic speakers access to generative AI and fostering innovation in the region.
InfiAgent is a new agent framework comparable to GPT4-Agent, developed by replicating Codex. It includes InfiCoder, an open-source model for text-to-code, code-to-code, and freeform code-related QA tasks. The framework focuses on data analysis and integrates an LLM with programming capabilities and a sandbox environment for executing Python code. Why it matters: This research demonstrates the potential for advancements in AI operating systems and highlights areas where current models like GPT-4V can be improved, contributing to the broader development of more capable and versatile AI agents.
Scimagine is a KAUST-based startup that provides a cloud-based platform for managing and storing experimental data for material scientists. The platform allows researchers to store, manage, and share their data, as well as create scientific visuals. It addresses the problem of experimental data being hidden in PDF files and not easily searchable. Why it matters: This platform improves data accessibility and collaboration in materials science research, potentially accelerating discovery and innovation in the field.