Who's Who of AI

AK

540 trust @_akhaliq · 516,758 followers
Why they matter

Tracked through public AI activity and peer connections inside the directory.

AI signals
11
past 30d
Sources
1
distinct domains
Discussions
0
past 30d
Latest signal
6d ago
View every signal from AK →
What they're sharing

Articles & links

paper: https://t.co/gD6tgeLIOt

Paper page - Orca: The World is in Your Mind huggingface.co
AI Weekly's analysis →
  • Orca pretrains on 125K hours of video and 160M event annotations using a single Next-State-Prediction objective on a frozen Qwen3.5 backbone.
  • Orca-4B averages 51.8 across MVBench, TemporalBench, 3DSRBench, and SWITCH, ahead of Qwen3.5-4B's 46.7 at the same size.
  • On a real-robot out-of-distribution test Orca reports 36.6% versus π₀.5's 27.6%, despite using no action labels in pre-training.
Read full analysis →
View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 3 from the directory shared this · 84d ago

AuK Technical Report An Open-Source Foundational Model for Speech Generation and Editing paper: https://t.co/tCsaoA5w6o https://t.co/hNH1qFczYo

Paper page - AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing huggingface.co
AI Weekly's analysis →
  • AuK, a 1.5-billion-parameter open-source model, was trained on roughly 3.03 billion instruction–audio instances and 1.95 million hours of supervision.
  • On Seed-TTS-Eval it posts a 2.65 average word-error rate versus Qwen3-TTS at 3.07, and cuts Chinese editing WER from 10.46 to 3.09.
  • A distilled AuK-Flash variant does 4-step inference without classifier-free guidance for a 4.5× wall-clock speedup over the full model.
Read full analysis →
View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 14d ago

Marigold V2 Revisiting Diffusion Transformers for Monocular Depth Estimation paper: https://t.co/718T7p8wCZ https://t.co/MJTvHC9jCt

Paper page - Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation huggingface.co
AI Weekly's analysis →
  • Marigold V2 reports a 16-26% AbsRel improvement over the previous best on KITTI and ETH3D from single-step flow-matching inference.
  • The recipe fine-tunes the pretrained Qwen-Image-Edit-2509 diffusion transformer with a rank-128 QLoRA on a single 32 GB consumer GPU.
  • The same pipeline extends to surface normals, intrinsic decomposition, sparse-to-dense metric depth completion and transparent-object depth.
Read full analysis →
View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 14d ago

Are you AK? Show it.

Add the Who’s Who of AI badge to your site or bio. It links back to this profile.

Listed in AI Weekly's Who's Who of AI

Markdown: [![Listed in AI Weekly's Who's Who of AI](https://aiweekly.co/modules/custom/aiweekly_whoswho/images/whoswho-badge.svg)](https://aiweekly.co/whos-who/person/ak)