Cohere Labs
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Cohere Labs
@Cohere_Labs
@Cohere's research lab and open science initiative that seeks to solve complex machine learning problems. Join us in exploring the unknown, together.


🔢 @KatrinaL2899 has been leading the ML Math Group for two years and brings so much enthusiasm to everything she does. From participating in multiple Expeditions to hosting one of our biggest ML Summer School sessions on math, Katrina’s passion for the field is clear. She’s even launched her own YouTube channel focused on all things math - an extension of the dedication she brings to the community.








Our Computer Vision group is looking forward to hosting @BrianCChao for a presentation on "Foveated Diffusion: Efficient Spatially Adaptive Image and Video Generation" next week on Tuesday, April 28th! Thanks to @cataluna84 and @Arkhymadhe for organizing this session! 🤩 Learn more: cohere.com/events/cohere-…

Our Computer Vision group is looking forward to hosting @BrianCChao for a presentation on "Foveated Diffusion: Efficient Spatially Adaptive Image and Video Generation" next week on Tuesday, April 28th! Thanks to @cataluna84 and @Arkhymadhe for organizing this session! 🤩 Learn more: cohere.com/events/cohere-…

Our Geo Regional Africa group is looking forward to hosting @pjox13 and @very_lauri from @CommonCrawl for a presentaion focused on "Expanding Linguistic and Cultural Coverage in Common Crawl." Thanks to community leads @katomubirusteve and @Bronsn4 for organizing this session! 🌟 Learn more: cohere.com/events/cohere-…


𝐇𝐞𝐫𝐞 𝐢𝐬 𝐭𝐡𝐞 1st 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭 𝐭𝐡𝐚𝐭 𝐰𝐨𝐫𝐤𝐬 𝐨𝐧 𝐚 𝐩𝐡𝐨𝐧𝐞, 𝐢𝐧 𝐚𝐧 𝐀𝐟𝐫𝐢𝐜𝐚𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞, 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐭𝐡𝐞 𝐢𝐧𝐭𝐞𝐫𝐧𝐞𝐭. More than a year ago, we joined the @Cohere_Labs open science community contributing to the Aya training pipeline. One thing I've learned from being part of this community: 𝒐𝒑𝒆𝒏-𝒔𝒐𝒖𝒓𝒄𝒆 𝒎𝒐𝒅𝒆𝒍𝒔 𝒅𝒐𝒏'𝒕 𝒎𝒐𝒗𝒆 𝒕𝒉𝒓𝒐𝒖𝒈𝒉 𝒑𝒓𝒆𝒔𝒔 𝒓𝒆𝒍𝒆𝒂𝒔𝒆𝒔. 𝑻𝒉𝒆𝒚 𝒎𝒐𝒗𝒆 𝒘𝒉𝒆𝒏 𝒃𝒖𝒊𝒍𝒅𝒆𝒓𝒔 𝒔𝒉𝒐𝒘 𝒘𝒉𝒂𝒕'𝒔 𝒑𝒐𝒔𝒔𝒊𝒃𝒍𝒆. So here what has been built. This year, the community launched Expedition Tiny Aya. Our team, led by @Bronsn4 Bakunga, set out to test something nobody had tried: 𝐜𝐚𝐧 𝐚 𝐬𝐦𝐚𝐥𝐥 𝐦𝐮𝐥𝐭𝐢𝐥𝐢𝐧𝐠𝐮𝐚𝐥 𝐦𝐨𝐝𝐞𝐥 𝐞𝐱𝐞𝐜𝐮𝐭𝐞 𝐫𝐞𝐚𝐥 𝐭𝐚𝐬𝐤𝐬 𝐨𝐧 𝐚 𝐩𝐡𝐨𝐧𝐞, 𝐨𝐟𝐟𝐥𝐢𝐧𝐞, 𝐢𝐧 𝐚𝐧 𝐀𝐟𝐫𝐢𝐜𝐚𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞? In two weeks, we built 𝐓𝐢𝐧𝐲 𝐅𝐚𝐜𝐚𝐝𝐞 , an open-source Android service that loads the model once and shares it with every app on the phone. Tested across 53 languages, 1,500+ configurations. A model with no tool-calling training outperformed one more than twice its size ,by 22 points on Luganda, 17 on Swahili. A health worker speaks Swahili. The phone understands, calls the right function, returns the answer. Under three seconds. Airplane mode on. They fixed @ollama (@jmorgan 's world wide tool)🔥 Along the way, we found and fixed a bug in Ollama cutting performance by 30% for every Tiny Aya user worldwide. @AlexisGimmy built Linga, a client app proving the pattern works. @AdnanElAssadi ran the test sweeps.@ojwrapper Onyeagwu stepped in to help. Julia Kreutzer from @cohere mentored the research and pushed us to ship something rigorous, not just fast. What excites us most is what comes next. Tiny Facade is model-agnostic — any open-source model that fits on a phone can plug in. The next generation of on-device models is arriving with capabilities that change everything ie hashtag#Gemma4: 𝐧𝐚𝐭𝐢𝐯𝐞 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧 𝐜𝐚𝐥𝐥𝐢𝐧𝐠 𝐛𝐮𝐢𝐥𝐭 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐦𝐨𝐝𝐞𝐥 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐠𝐫𝐨𝐮𝐧𝐝 𝐮𝐩, 𝐛𝐮𝐢𝐥𝐭-𝐢𝐧 𝐬𝐩𝐞𝐞𝐜𝐡 𝐫𝐞𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧 𝐬𝐨 𝐚 𝐟𝐚𝐫𝐦𝐞𝐫 𝐜𝐚𝐧 𝐬𝐩𝐞𝐚𝐤 𝐝𝐢𝐫𝐞𝐜𝐭𝐥𝐲 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐚 𝐬𝐞𝐩𝐚𝐫𝐚𝐭𝐞 𝐭𝐫𝐚𝐧𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧 𝐬𝐭𝐞𝐩, 𝐜𝐚𝐦𝐞𝐫𝐚-𝐛𝐚𝐬𝐞𝐝 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐫𝐞𝐚𝐝𝐢𝐧𝐠 𝐬𝐨 𝐚 𝐡𝐞𝐚𝐥𝐭𝐡 𝐰𝐨𝐫𝐤𝐞𝐫 𝐜𝐚𝐧 𝐩𝐡𝐨𝐭𝐨𝐠𝐫𝐚𝐩𝐡 𝐚 𝐩𝐚𝐭𝐢𝐞𝐧𝐭 𝐟𝐨𝐫𝐦 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐀𝐈 𝐫𝐞𝐚𝐝𝐬 𝐚𝐧𝐝 𝐚𝐜𝐭𝐬 𝐨𝐧 𝐢𝐭, 𝐚𝐧𝐝 𝐬𝐭𝐞𝐩-𝐛𝐲-𝐬𝐭𝐞𝐩 𝐫𝐞𝐚𝐬𝐨𝐧𝐢𝐧𝐠 𝐬𝐨 𝐭𝐡𝐞 𝐦𝐨𝐝𝐞𝐥 𝐭𝐡𝐢𝐧𝐤𝐬 𝐛𝐞𝐟𝐨𝐫𝐞 𝐢𝐭 𝐫𝐞𝐬𝐩𝐨𝐧𝐝𝐬 — 𝐚𝐜𝐫𝐨𝐬𝐬 140+ 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬, 𝐮𝐧𝐝𝐞𝐫 𝐚 𝐟𝐮𝐥𝐥𝐲 𝐨𝐩𝐞𝐧 𝐜𝐨𝐦𝐦𝐞𝐫𝐜𝐢𝐚𝐥 𝐥𝐢𝐜𝐞𝐧𝐬𝐞. Thank you to @mziizm Fadaee, @Alejandro Rodríguez Salamanca, @brittawnyap , @Madeline Smith, and @Julia Kreutzer for building a community where a team from Kampala can do work that matters globally. 𝐌𝐨𝐫𝐞 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐰𝐨𝐫𝐤: huggingface.co/blog/Bronsn/ti…

Cohere Labs x ICLR 2026: Making, Not Taking, the Best of N Introduing Fusion-of-N (FusioN) where we replace “pick the best sample” with “generate a better one by combining samples.”🚀

Cohere Labs x ICLR 2026: Making, Not Taking, the Best of N Introduing Fusion-of-N (FusioN) where we replace “pick the best sample” with “generate a better one by combining samples.”🚀







