6hr delay, board, deplane, board, taxi, return to gate and @AmericanAir has 2 bags of pretzels to offer.
Maybe time to heed the engine's warnings and not try to push it trans-atlantic
Gemma 4 just got even faster!
We're releasing Multi-Token Prediction (MTP) drafters that deliver up to a 3x speedup, without any degradation in output quality or reasoning logic.
New in Gemini: Generate files and export them
Tell Gemini what you want to create and the format, and it now does the work for you.
Now supporting:
📄 Google Docs, Word (.docx) & PDFs
📊 Google Sheets, Excel (.xlsx) & CSV
🖥️ Google Slides
🛠️ Markdown, LaTeX, TXT, RTF
Available now on all surfaces globally!
Hi, we are releasing ColGrep 1.2.0
ColGrep now incorporate BM25 trigrams to further enhance our multi-vector models using hybrid search.
Now, ColGrep print relative paths by default (fewer tokens per result)
Exact same features as GREP
Improved CUDA usage and installation
💫 Introducing New SOTA Long Context VLM
LightOn OriOn-Qwen-SR1 reasons over full documents and executes it implicitly at inference.
Reasoning is compressed into the model's weights, no verbose output, no added latency.
🥇 SOTA on MMLongBenchDoc, ahead of Qwen3 VL with 7× fewer parameters.
🙌 Kudos to @further_ai for this new milestone!
Reasoning starts at reading.
👉 https://t.co/fLsnY9USeA
Starlette 1.0 is here!🎉
After nearly eight years, Starlette has reached its first stable release. Downloaded almost 10 million times a day, it serves as the foundation for FastAPI and the Python MCP SDK.
Blog post: https://t.co/KdSmoBJnah
Release notes: https://t.co/m8Si0XDexJ
rpg 0.8.0 – modern PostgreSQL terminal https://t.co/UyLC2wNzhi
in this release:
EXPLAIN plans that actually help you
Instead of staring at a wall of text, rpg now shows a summary header with execution time, buffer stats, and automatic warnings — seq scans on large tables, row estimate errors, sorts spilling to disk. The full plan is preserved with color coding so the hot path jumps out instantly.
Plan export to popular visualization/analysis tools
When you find a slow query, share the plan in one command:
\explain share depesz
→ https://t.co/JvBpX233tE
Works with depesz, dalibo, and pgMustard. No copy-paste, no browser tabs.
Lua custom commands
Write a Lua script, drop it in ~/.config/rpg/commands/, and you have a new \backslash command.
Other highlights
- Markdown output (\pset format markdown; psql --markdown) — paste query results directly into GitHub issues
- Better \s history — filter with patterns, syntax highlighted, through the pager
- Tab completion for all rpg commands
- pspg integration with 20+ themes
- lots of fixes based on feedback I've got yesterday/today
⭐ https://t.co/volv01adzo
Well, well, well...
One perks of building on top of sentence-transformers is that everytime @tomaarsen ships, PyLate gets free features...
And I am hearing that lately he might have focused on... multimodality
https://t.co/BRvudwrlG9
Yes, ColPali will soon be supported by PyLate :)
(Actually, not only images 🚀)
NEW SOTA OCR MODEL DROPPED
Congrats to @VikParuchuri and team for releasing Chandra OCR 2!
- 85.9% on olmocr bench, making it first place 🏆
- 90+ language support
- 4B model
- Full layout information
- Extracts + captions images and diagrams
- Strong handwriting, math, form, table support
Compare every OCR model on the hub and choose the one adapted to your needs 👇
The multi-vector era is here and there is no going back.
Reason-ModernColBERT tops BrowseComp-Plus, the hardest agentic search benchmark available, by 7.59 points on accuracy.
🥇on accuracy.
🥇on recall.
🥇on calibration.
📉 Fewest search calls.
The models it outperforms? Up to 54× larger.
Reasoning-intensive retrieval (BRIGHT), code search (MTEB Code), agentic Deep Research (BrowseComp-Plus). The pattern is the same: late interaction dominates, with a fraction of the parameters.
149M parameters. Open weights. Open code. Built with PyLate in a few hours.
Full results, analysis and recipe on LightOn blog: https://t.co/7PiseAwhQP
Introducing Kitten TTS V0.8: open-source TTS that fits in 25MB.
Three variants: 80M | 40M | 14M (<25MB)
Highly expressive. Runs on CPU. Built for edge.
No GPU? No problem. Ship voice anywhere.
Check it out:
BrowseComp-Plus, perhaps the hardest popular deep research task, is now solved at nearly 90%...
... and all it took was a 150M model ✨
Thrilled to announce that Reason-ModernColBERT did it again and outperform all models (including models 54× bigger) on all metrics