Baby Is Healed With World’s First Personalized Gene-Editing Treatment
"October The First Is Too Late"
Slate Star Codex was the former name for a blog by Scott Alexander about human cognition, politics, and medicine. In 2021, the name was changed to Astral Codex Ten: https://astralcodexten.substack.com/
"Xi Takes an AI Masterclass: Inside the Politburo's AI Study Session", Jordan Schneider 2025-05-13
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
"Oura Member Data Reveals Geographies With Greatest Health Gains", Oura (HRV, step count, sleep etc)
School district loses case arguing that illiterate dyslexic student received education because he used ChatGPT for everything
**Synthetic media describes the use of artificial intelligence to generate and manipulate data, most often to automate the creation of entertainment.** This field encompasses deepfakes, image synthesis, audio synthesis, text synthesis, style transfer, speech synthesis, and much more.
Christian Bök’s SF book has been successfully edited into _Deinococcus radiodurans_
[Article] "Chainlet Orbits: Topological Address Embedding for Blockchain", Azad et al 2025 (ACM)
This subreddit is for requesting and sharing specific articles available in various databases.
"Agatha Christie, Who Died in 1976, Will See You in Class: An avatar of the long-dead British novelist is “teaching” an online writing course. But do we want to learn from a digital prosthetic built by artificial intelligence?"
**Synthetic media describes the use of artificial intelligence to generate and manipulate data, most often to automate the creation of entertainment.** This field encompasses deepfakes, image synthesis, audio synthesis, text synthesis, style transfer, speech synthesis, and much more.
"LegoGPT: Generating Physically Stable and Buildable LEGO Designs from Text", Pun et al 2025
**Synthetic media describes the use of artificial intelligence to generate and manipulate data, most often to automate the creation of entertainment.** This field encompasses deepfakes, image synthesis, audio synthesis, text synthesis, style transfer, speech synthesis, and much more.
Are Amazon's New Vulcan Robots Revolutionizing Warehouse Efficiency?
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
Benchmarking ChatGPT sycophancy: "AI behavior is very weird and hard to predict."
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
"Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs", Tang et al 2025 {Huawei} (training a DeepSeek-R1-like 718b-param MoE on 6k Ascend NPUs)
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
[D] Why is RL in the real-world so hard?
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
"Borges Lecture April 9-10th, 1976", Minnesota ("believed only existing filmed footage of Borges giving talks in English")
For discussions of the works of Argentine author J.L. Borges.
"Introducing OpenAI for Countries: A new initiative to support countries around the world that want to build on democratic AI rails", OpenAI (pilot program for 10 countries to build OA datacenters & finetune LLMs?)
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
"The Steganographic Potentials of Language Models", Karpov et al 205
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
"Absolute Zero: Reinforced Self-play Reasoning with Zero Data", Zhao et al 2025
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
"Rewriting Pre-Training Data Boosts LLM Performance in Math and Code", Fujii et al 2025 (SwallowCodeSwallowMath; more paraphrasing/data-augmentation for boosting pretraining/finetuning)
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
"All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning", Swamy et al 2025
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
"Everyone Is Cheating Their Way Through College: ChatGPT has unraveled the entire academic project"
**Synthetic media describes the use of artificial intelligence to generate and manipulate data, most often to automate the creation of entertainment.** This field encompasses deepfakes, image synthesis, audio synthesis, text synthesis, style transfer, speech synthesis, and much more.
"Glyph-ByT5-v2: A Strong Aesthetic Baseline for Accurate Multilingual Visual Text Rendering", Liu et al 2024 (character-tokenized LLMs work much better for rendering text inside images)
**Synthetic media describes the use of artificial intelligence to generate and manipulate data, most often to automate the creation of entertainment.** This field encompasses deepfakes, image synthesis, audio synthesis, text synthesis, style transfer, speech synthesis, and much more.
"Evaluating Frontier Models for Stealth and Situational Awareness", Phuong et al 2025 {DM}
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
"'New News': System-2 Fine-tuning for Robust Integration of New Knowledge", Park et al 2025 (do LLMs need to 'think about' finetuning data, like training on multiple parahrased versions, to match ICL prompting?)
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
"Learning to Reason for Long-Form Story Generation", Gurung & Lapata 2025
Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and learning how to optimally acquire rewards. Examples are AlphaGo, clinical trials & A/B tests, and Atari game playing.
"Fast, scalable, clean, and cheap enough: How off-grid solar microgrids can power the AI race", Baranko et al 2024-12
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
