🚀 Open-source upgrade unlocked. Tencent Hy-MT2 is now under Apache License 2.0 — maximum freedom for research, commercial use, fine-tuning, and derivatives. No strings attached.😎😎😎 Proud to push model weights back to the community. Our two variants are currently sitting at #1# and #4# on the Hugging Face trending leaderboard. Clone, fork, break things, ship feedback. The iteration loop is live.🔥 Let’s keep building the frontier together. #Tencent# #Hy# #HyMT2# #Apache2# #HuggingFace# #OpenSourceA#

Apache Iceberg is now generally available in Palantir AIP. Sovereignty at all levels of the stack. Customers can now use an open, interoperable table format alongside the capabilities required to operate critical data: pipeline building, governance, security, lineage, and Ontology. The full open standard, not some Palantir variant of it...... THE FULL OPEN STANDARD. Managed Iceberg tables and Palantir’s Iceberg REST catalog are GA on standard Foundry enterprise environments. Tables can be stored in Palantir managed storage or a customer-provided bucket. This means one bucket (yours, ours or theirs), one iceberg file, Palantir and your other Iceberg enabled systems working on the same physical file. Zero Data Copy. Teams can build pipelines, perform row-level updates and changelog processing, create Ontology object types backed by Iceberg, analyze tables in with SQL, python or connect external tools directly to the catalog. Completely open. Adopting and supporting an open standard means more than consuming it. Our FDEs have also contributed back to the Iceberg standard to enable features we had built in Foundry but now is available as part of the standard for all, just a few examples: - Table encryption in iceberg-rust - Incremental append scans, schema evolution, and other Iceberg features in Polars - Incremental append scans and other contributions to PyIceberg More about some of the new value add: and

Apache Polaris™ 1.5: pluggable auth (including Apache Ranger™), broader federation, better CLI workflows, and performance improvements. Check out what's new:

Apache Iceberg™ 1.11 isn’t about flashy features. It’s about making Iceberg actually work in production: ✦︎ Fewer bugs ✦︎ Better performance ✦︎ More predictable behavior Take a closer look at what's new and why it matters:

Introducing Apache Spark® 4.3, now available in Databricks Runtime 19! The release brings major new capabilities across real-time processing, history-preserving pipelines, small-data performance, Spark Connect, and SQL. What’s new: - Bring state to Real-Time Mode with streaming aggregation and transformWithState - Preserve history with SCD Type 2 Auto CDC - Iterate faster on small data with Project Feather - Reach Spark from more applications with expanded Spark Connect capabilities It also begins a new quarterly feature-release cadence, bringing completed improvements to users sooner. Get started:

Testing Apache Iceberg™ streaming at 1M+ TPS shouldn’t require building the surrounding infrastructure first. Snowpark Container Services generates the load, Snowpipe Streaming batches it server-side, and Snowflake lands and compacts the Parquet files. See the architecture: