PerceptionDLM
— AK (@_akhaliq) 22 juin 2026
Parallel Region Perception with Multimodal Diffusion Language Models pic.twitter.com/0vZdGaAPoy
PerceptionDLM Parallel Region Perception with Multimodal Diffusion Language Models
GENERATIVE AI
-
PerceptionDLM: Parallel Region Perception with Multimodal Language Models
By
–
-
Five Eyes: AI could amplify cyberattacks in a few months
By
–
The Five Eyes cyber defense agencies have warned that advanced AI models capable of dramatically amplifying cyberattacks against governments and businesses could be only a few months away, not years. Via The Guardian
-
GLM 5.2 lacks image understanding; uses numpy for WandB charts
By
–
3/4: One limitation worth noting: GLM 5.2 has no image understanding. While Opus and Fable can consistently identify trends in WandB charts, GLM resorts to writing numpy code to smooth and clean the raw WandB numbers before analyzing. For simpler runs like this example this is
-
GLM 5.2: First high-performance open-weights model for auto-research
By
–
Introducing GLM 5.2 for autoresearch
— alphaXiv (@askalphaxiv) 22 juin 2026
GLM 5.2 is the first open weights model we've tried on our autoresearch pipeline that's proven capable for real research tasks.
With Fable 5's restrictions on research, having an open weights alternative is a huge win for open source
Watch… pic.twitter.com/y0kBtJzj5KIntroducing GLM 5.2 for auto-research. GLM 5.2 is the first open-weights model we tested on our auto-research pipeline that proved capable for real research tasks. With Fable 5's restrictions on research, having a
-
AI mania: Spidey feeling that models have changed
By
–
My version of AI mania is when I get a spidey feeling that the models have changed. Opus 4.8 feels very different today.
-
Real-time streaming inference model for interactive worlds
By
–
/5 An interactive world isn't truly interactive if it lags. This model is built specifically for real-time streaming inference. Using DMD-style distillation and an autoregressive rolling KV cache, it generates environments chunk-by-chunk from noise. When paired with asynchronous
-
DreamX-World 1.0 eliminates color drift and style mutations via long-rollout training
By
–
/6 Long-form autoregressive generation usually suffers from accumulated prediction errors, leading to color drift and style mutations. Thanks to specialized long-rollout training, DreamX-World 1.0 overcomes this limitation. It maintains stunning visual fidelity, smooth motion,
-
DreamX-World 1.0 fixes AI video environment mutation with memory persistence
By
–
/4 One major flaw in AI video is that looking away and turning back often mutates the environment. DreamX-World 1.0 fixes this with Memory-Conditioned Scene Persistence. It retrieves past frames based on camera geometry and view overlap rather than just time. By packing these
-
DreamX-World 1.0: Text to interactive video environments
By
–
Text-to-video generation has officially leveled up from passive clips to fully navigable, interactive environments.
— AlphaSignal (@AlphaSignalAI) 22 juin 2026
The DreamX Team just released a paper on DreamX-World 1.0, a general-purpose interactive world model that translates text and images into long-horizon videos you… pic.twitter.com/rVzLwhGNoKText-to-video generation has officially leveled up from passive clips to fully navigable, interactive environments. The DreamX Team just released a paper on DreamX-World 1.0, a general-purpose interactive world model that translates text and images into long-horizon videos you
-
Announcement of new GPT-5.6, Pro, and bidirectional voice models this Thursday
By
–
It looks like we are going to have a whole range of new GPT models this Thursday: GPT-5.6, 5.6 Pro, and a new bidirectional voice model. Initial tests of the voice model have been exceptional, this is exactly what I was hoping for two years ago!