AI meets AR: How Rokid Glasses bring multilingual, real-time intelligence to smart eyewear globally
Updated
March 3, 2026 3:50 PM
Rokid's smart glasses. PHOTO: ROKID
Rokid, a Chinese company specializing in AI-powered smart eyewear and human–computer interaction, has rolled out a major software update for the international version of its Rokid Glasses. This update makes it the first smart glasses manufacturer to natively support Google’s Gemini, alongside three other leading large language models: OpenAI’s ChatGPT, Alibaba’s Qwen and DeepSeek.
The integration is powered by Rokid’s device-to-cloud architecture, which enables users to switch between AI models on the fly. In practice, this means a traveler can receive a real-time translation in Japanese using one AI model, then quickly switch to ChatGPT to answer a technical query—without noticeable delay. The system also supports multi-modal inputs like voice and gestures, making interactions more intuitive for everyday use.
This is more than a routine software update. By combining AI models from both U.S. and Chinese developers, Rokid is making its smart glasses relevant to global users, with features that adapt to local languages and preferences while maintaining high performance.
These technological advancements have directly fueled Rokid’s international growth. Between November 2024 and October 2025, Shangpu Group data shows Rokid Glasses ranked No.1 in global sales for AI glasses with display functionality. Crowdfunding milestones further reflect this momentum: the product became the fastest smart glasses to raise over 100 million Japanese Yen on Japan’s MAKUAKE platform and broke Kickstarter records for smart eyewear.
Taken together, Rokid’s update highlights a shift in the smart glasses space: success increasingly comes from openness, flexibility and localized AI experiences rather than closed, single-platform ecosystems. By giving users choice, integrating global AI capabilities and bridging cultural and linguistic gaps, Rokid is positioning itself as a serious contender in the international AR and AI wearable market.
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A closer look at how machine intelligence is helping doctors see cancer in an entirely new light.
Updated
January 8, 2026 6:33 PM
Serratia marcescens colonies on BTB agar medium. PHOTO: UNSPLASH
Artificial intelligence is beginning to change how scientists understand cancer at the cellular level. In a new collaboration, Bio-Techne Corporation, a global life sciences tools provider, and Nucleai, an AI company specializing in spatial biology for precision medicine, have unveiled data from the SECOMBIT clinical trial that could reshape how doctors predict cancer treatment outcomes. The results, presented at the Society for Immunotherapy of Cancer (SITC) 2025 Annual Meeting, highlight how AI-powered analysis of tumor environments can reveal which patients are more likely to benefit from specific therapies.
Led in collaboration with Professor Paolo Ascierto of the University of Napoli Federico II and Istituto Nazionale Tumori IRCCS Fondazione Pascale, the study explores how spatial biology — the science of mapping where and how cells interact within tissue — can uncover subtle immune behaviors linked to survival in melanoma patients.
Using Bio-Techne’s COMET platform and a 28-plex multiplex immunofluorescence panel, researchers analyzed 42 pre-treatment biopsies from patients with metastatic melanoma, an advanced stage of skin cancer. Nucleai’s multimodal AI platform integrated these imaging results with pathology and clinical data to trace patterns of immune cell interactions inside tumors.
The findings revealed that therapy sequencing significantly influences immune activity and patient outcomes. Patients who received targeted therapy followed by immunotherapy showed stronger immune activation, marked by higher levels of PD-L1+ CD8 T-cells and ICOS+ CD4 T-cells. Those who began with immunotherapy benefited most when PD-1+ CD8 T-cells engaged closely with PD-L1+ CD4 T-cells along the tumor’s invasive edge. Meanwhile, in patients alternating between targeted and immune treatments, beneficial antigen-presenting cell (APC) and T-cell interactions appeared near tumor margins, whereas macrophage activity in the outer tumor environment pointed to poorer prognosis.
“This study exemplifies how our innovative spatial imaging and analysis workflow can be applied broadly to clinical research to ultimately transform clinical decision-making in immuno-oncology”, said Matt McManus, President of the Diagnostics and Spatial Biology Segment at Bio-Techne.
The collaboration between the two companies underscores how AI and high-plex imaging together can help decode complex biological systems. As Avi Veidman, CEO of Nucleai, explained, “Our multimodal spatial operating system enables integration of high-plex imaging, data and clinical information to identify predictive biomarkers in clinical settings. This collaboration shows how precision medicine products can become more accurate, explainable and differentiated when powered by high-plex spatial proteomics – not limited by low-plex or H&E data alone”.
Dr. Ascierto described the SECOMBIT trial as “a milestone in demonstrating the possible predictive power of spatial biomarkers in patients enrolled in a clinical study”.
The study’s broader message is clear: understanding where immune cells are and how they interact inside a tumor could become just as important as knowing what they are. As AI continues to map these microscopic landscapes, oncology may move closer to genuinely personalized treatment — one patient, and one immune network, at a time.