Jollyvids. -
(often referred to via their social handles as Jollyvids ) is a popular entertainment brand known for bridging cultural gaps through humor, food, and genuine reactions. Primarily featuring hosts Josh Carrott and Ollie Kendal , the channel is a spin-off of their original project, Korean Englishman , and focuses on introducing international audiences—often British—to unique global experiences. Core Content Pillars
“We realized that most platforms know exactly when you are sad—they just don’t care because sad people scroll longer,” says Jenna K. , lead UX designer for the project. “Our algorithm asks one question: Would this video feel good to watch while eating breakfast? If the answer is no, it doesn’t go on the For You page.” jollyvids.
Let me know what you're interested in! JOLLY (@jollyvids) - Facebook (often referred to via their social handles as
| Aspect | What the paper offers | How you can leverage it | |--------|----------------------|------------------------| | | Detailed statistics (category distribution, duration histograms, language coverage), collection pipeline, and quality‑control measures. | Quickly assess whether JollyVids matches your target domain or task. | | Annotation schema | Multi‑level annotations (global caption, per‑segment actions, audio transcript, object bounding boxes for a 10 % subset). | Re‑use the schema for extending your own dataset or for fine‑grained evaluation. | | Baseline models & code | End‑to‑end training scripts for CLIP‑style video‑text encoders, a transformer‑based captioner, and a retrieval system (all released under Apache‑2.0). | Jump‑start experiments without building the pipeline from scratch. | | Benchmark results | Comparative tables on MSR‑VTT, ActivityNet Captions, and HowTo100M, showing absolute improvements of 4–12 % when pre‑training on JollyVids. | Cite concrete performance gains when arguing for JollyVids pre‑training in a paper or grant. | | Ethical considerations | Discussion of bias analysis (demographic, geographic, and content‑type), licensing compliance, and a data‑usage policy. | Use the authors’ checklist to ensure responsible deployment of models trained on JollyVids. | | Future directions | Suggestions for multimodal reasoning (e.g., video‑question answering), long‑form video extensions, and cross‑modal generation. | Identify open research problems you can target in your own work. | , lead UX designer for the project
In a digital landscape often defined by algorithm anxiety, echo chambers, and cynicism, offers a radical proposition: what if the internet was fun again?
: Their comment sections are very active, with fans frequently suggesting new foods for them to try.
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