Update README.md

README.md

@@ -18,22 +18,37 @@ configs:
     path: personas/*.parquet
 ---
 
-## Multimodal seeds/Pretraining data.
+## Multimodal Pretraining
 
-### Non-US Patents
+### Youtube-Commons
 
-While USPTO has been extensively digitized, available public data leave aside non-US patents. We managed to collect the complete collection of European patents (EPO) in the original pdf format, including tens of millions of technical diagram beyond texts.
+Youtube-Commons is the current referenced dataset for Youtube videos under creative commons allowing for full commercial reuse. The dataset was noticeably used to train Nvidia's SOTA text to speech model <a href="https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2">Parakeet</a>.
 
-The initial sample is split into a parquet file (result of our internal digitization process)
+While the public version of Youtube-Commons only includes metadata and transcripts and has not been updated since 2024, our internal asset includes audio attached to transcripts and metadata for 4.1 Million videos.
 
-### Regulated sectors (Finance, telecom)
+We provide an initial samples of 5,000 audio samples with associated metadata in parquet.
+
+### Global academic thesis
+
+We hold the largest collection of academic thesis with more than three million documents in PDF at a global scale. 
+
+Our coverage extends significantly beyond western sources, with half of our holding are not even indexed in scientific databases like OpenAlex. Typically, it includes XXX,XXX thesis from India with a significant language variety: Hindi, . The collection is uniquely fitting for long horizon multimodal tasks.
+
+The current sample include 1052 thesis in pdf formats in many languages.
 
-We collaborate with leading professional organizations, GSMA and the Authority of 
+### Non-US Patents
+
+We are currently collecting the largest available asset of non-US patents. It currently includes the complete collection of European patents (EPO) in the original pdf format and we're currently scaling our data collection to Asia.
+
+Patents commonly come with technical diagrams we can communicate in a separate forms (for now, about 20 million images). The diagrams are described in other parts of the text with complex layout and structure, providing unresolved challenges for frontier multimodal domains across a wide range of disciplines and technical expertise.
 
-## Scientific data
+The current sample includes 5,000 unique samples in large .tar files along with associated metadata.
 
+### Regulated sectors (Finance, telecom)
+
+[To write]
 
-## Structured data seeds
+## Synthetic data seeds/environment
 
 ### Wikidata
 
@@ -47,8 +62,6 @@ Our internal assets scaling the synthetic personas at a global scale. We collect
 
 We provide a sample of 1 millions personas across 108 countries. Our full asset includes currently 100 millions personas but is indefinitely scalable. Similarly to Wikidata, we can also provide continuous updates taking into enhanced information and demographic changes.
 
-## Synthetic environment
-
 ### Twitter/X
 
 Synthetic environment prepared for the subway of Paris comprising 2 millions realistic synthetic tweets in French and other foreign language. The synthetic pipeline was presented this year at ACL and is reproducible for multiple similar social media simulations. We especially designed new generators and evaluations for realistic social media emissions.