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tasty diffusion papers - september 2024

OmniGen: Unified Image Generation
what: one transformer for the text-to-image diffusion model.
- rectified flow.
- multimodal condition: text and image.
- one model processes all context and does diffusion steps.

Diffusion Policy Policy Optimization
what: set of best practices for fine-tuning diffusion-based policies in continuous control and robot learning tasks.

Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis
what: modification which helps to generalize better on few samples.

my thoughts
- i like how AI community is trying to simplify everything. surprisingly sometimes it works well. for example, rectified flow is simplified version of diffusion.
- rl + diffusion => next step in brain stimulation?
diffusion models could mimic brain patterns for smoother stimulation. with RL, they’d adapt in real-time, making treatments more precise and personalized. shifting from rigid protocols to dynamic brain interventions.

#digest



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tasty diffusion papers - september 2024

OmniGen: Unified Image Generation
what: one transformer for the text-to-image diffusion model.
- rectified flow.
- multimodal condition: text and image.
- one model processes all context and does diffusion steps.

Diffusion Policy Policy Optimization
what: set of best practices for fine-tuning diffusion-based policies in continuous control and robot learning tasks.

Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis
what: modification which helps to generalize better on few samples.

my thoughts
- i like how AI community is trying to simplify everything. surprisingly sometimes it works well. for example, rectified flow is simplified version of diffusion.
- rl + diffusion => next step in brain stimulation?
diffusion models could mimic brain patterns for smoother stimulation. with RL, they’d adapt in real-time, making treatments more precise and personalized. shifting from rigid protocols to dynamic brain interventions.

#digest

BY the last neural cell




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Pavel Durov, Telegram's CEO, is known as "the Russian Mark Zuckerberg," for co-founding VKontakte, which is Russian for "in touch," a Facebook imitator that became the country's most popular social networking site. After fleeing Russia, the brothers founded Telegram as a way to communicate outside the Kremlin's orbit. They now run it from Dubai, and Pavel Durov says it has more than 500 million monthly active users. The account, "War on Fakes," was created on February 24, the same day Russian President Vladimir Putin announced a "special military operation" and troops began invading Ukraine. The page is rife with disinformation, according to The Atlantic Council's Digital Forensic Research Lab, which studies digital extremism and published a report examining the channel. Emerson Brooking, a disinformation expert at the Atlantic Council's Digital Forensic Research Lab, said: "Back in the Wild West period of content moderation, like 2014 or 2015, maybe they could have gotten away with it, but it stands in marked contrast with how other companies run themselves today." Just days after Russia invaded Ukraine, Durov wrote that Telegram was "increasingly becoming a source of unverified information," and he worried about the app being used to "incite ethnic hatred."
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