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Tasty AI Papers | 01-31 August 2024

Robotics.

🔘Body Transformer: Leveraging Robot Embodiment for Policy Learning

what: one transformer to control whole body.
- propose Body Transformer (BoT)
- vanilla transformer with special attention mask, which reflects interconnection of the different body parts.

🔘CrossFormer Scaling Cross-Embodied Learning for Manipulation, Navigation, Locomotion, and Aviation

what: One transformer that can control various robot types.
- trained on 900K trajectories from 20 different robots.
- matches or beats specialized algorithms for each robot type.
- works on arms, wheeled bots, quadrupeds, and even drones.

Diffusion + AR Transformers

🟢Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

what: merge AR decoder with vanilla diffusion.
- train model with two objectives: causal language loss + diffusion objective
- deal with discrete and continuous in the same model.

🟡 Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

what: propose diffusion for discrete distribution
- beats other diffusion approach for text generation
- outperforms gpt-2.

🟡Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

what: combine AR transformer with MaskGIT.
- can generate image and understand them.
- text tokenization + image tokenization. Use MaskGIT losses for image tokens.
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Tasty AI Papers | 01-31 August 2024

Robotics.

🔘Body Transformer: Leveraging Robot Embodiment for Policy Learning

what: one transformer to control whole body.
- propose Body Transformer (BoT)
- vanilla transformer with special attention mask, which reflects interconnection of the different body parts.

🔘CrossFormer Scaling Cross-Embodied Learning for Manipulation, Navigation, Locomotion, and Aviation

what: One transformer that can control various robot types.
- trained on 900K trajectories from 20 different robots.
- matches or beats specialized algorithms for each robot type.
- works on arms, wheeled bots, quadrupeds, and even drones.

Diffusion + AR Transformers

🟢Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

what: merge AR decoder with vanilla diffusion.
- train model with two objectives: causal language loss + diffusion objective
- deal with discrete and continuous in the same model.

🟡 Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

what: propose diffusion for discrete distribution
- beats other diffusion approach for text generation
- outperforms gpt-2.

🟡Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

what: combine AR transformer with MaskGIT.
- can generate image and understand them.
- text tokenization + image tokenization. Use MaskGIT losses for image tokens.

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Telegram | DID YOU KNOW?

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At the start of 2018, the company attempted to launch an Initial Coin Offering (ICO) which would enable it to enable payments (and earn the cash that comes from doing so). The initial signals were promising, especially given Telegram’s user base is already fairly crypto-savvy. It raised an initial tranche of cash – worth more than a billion dollars – to help develop the coin before opening sales to the public. Unfortunately, third-party sales of coins bought in those initial fundraising rounds raised the ire of the SEC, which brought the hammer down on the whole operation. In 2020, officials ordered Telegram to pay a fine of $18.5 million and hand back much of the cash that it had raised. Telegram has gained a reputation as the “secure” communications app in the post-Soviet states, but whenever you make choices about your digital security, it’s important to start by asking yourself, “What exactly am I securing? And who am I securing it from?” These questions should inform your decisions about whether you are using the right tool or platform for your digital security needs. Telegram is certainly not the most secure messaging app on the market right now. Its security model requires users to place a great deal of trust in Telegram’s ability to protect user data. For some users, this may be good enough for now. For others, it may be wiser to move to a different platform for certain kinds of high-risk communications. Markets continued to grapple with the economic and corporate earnings implications relating to the Russia-Ukraine conflict. “We have a ton of uncertainty right now,” said Stephanie Link, chief investment strategist and portfolio manager at Hightower Advisors. “We’re dealing with a war, we’re dealing with inflation. We don’t know what it means to earnings.” Again, in contrast to Facebook, Google and Twitter, Telegram's founder Pavel Durov runs his company in relative secrecy from Dubai. It is unclear who runs the account, although Russia's official Ministry of Foreign Affairs Twitter account promoted the Telegram channel on Saturday and claimed it was operated by "a group of experts & journalists."
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