Underserved patients couldn't see specialists. A Telegram bot now reads X-rays and consults in Arabic.
A graduate-level research university in Abu Dhabi develops AI solutions to improve healthcare access for over 400 million Arabic speakers across the Middle East and Africa.
Underserved communities in the region lack consistent access to medical specialists, and existing AI models fail to support the necessary...
“With its Arabic-English bilingual interactions, our model extends healthcare access to over 400 million Arabic-speaking individuals as an inclusive and comprehensive healthcare solution. We believe it is the first medical large multimodal model built on Llama 3.1.”
Graduate research university for artificial intelligence and machine learning.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Related implementations across industries and use cases
Rigid decision trees needed seven questions to spot a chest pain emergency. Dot catches it on turn one and adapts to each member's context.
Manual coordination slowed care. Voice agents now manage intake and housing aid via phone, scaling safely after 3,000+ safety simulations.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.
Charting ate into patient time and kept nurses late. Ambient listening now captures notes in real time as they move room to room.
Reports read one by one, cohorts assembled in spreadsheets—weeks of work. Now physicians ask in plain language; answers arrive in seconds.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Underserved patients couldn't see specialists. A Telegram bot now reads X-rays and consults in Arabic.
A graduate-level research university in Abu Dhabi develops AI solutions to improve healthcare access for over 400 million Arabic speakers across the Middle East and Africa.
Underserved communities in the region lack consistent access to medical specialists, and existing AI models fail to support the necessary...
“With its Arabic-English bilingual interactions, our model extends healthcare access to over 400 million Arabic-speaking individuals as an inclusive and comprehensive healthcare solution. We believe it is the first medical large multimodal model built on Llama 3.1.”
Graduate research university for artificial intelligence and machine learning.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Related implementations across industries and use cases
Rigid decision trees needed seven questions to spot a chest pain emergency. Dot catches it on turn one and adapts to each member's context.
Manual coordination slowed care. Voice agents now manage intake and housing aid via phone, scaling safely after 3,000+ safety simulations.
Fragmented data and manual workflows slowed care. Now, AI helps staff optimize surgical scheduling and physicians diagnose rare diseases.
Charting ate into patient time and kept nurses late. Ambient listening now captures notes in real time as they move room to room.
Reports read one by one, cohorts assembled in spreadsheets—weeks of work. Now physicians ask in plain language; answers arrive in seconds.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.