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https://arxiv.org/abs/2306.04031 Certified Reasoning with Language Models Language models often achieve higher accuracy when reasoning step-by-step in complex tasks. However, their reasoning can be unsound, inconsistent, or rely on undesirable prior assumptions. To tackle these issues, we introduce a class of tools for language arxiv.org 1. 언어 모델은 복잡한 작업에서 단계별로 추론을 할 때 종종 더 높은 정확도를 보입니다. 그러나 그들의..

https://www.deepmind.com/blog/alphadev-discovers-faster-sorting-algorithms AlphaDev discovers faster sorting algorithms In our paper published today in Nature, we introduce AlphaDev, an artificial intelligence (AI) system that uses reinforcement learning to discover enhanced computer science algorithms – surpassing those honed by scientists and engineers over decades. www.deepmind.com DeepMind의 ..

https://arxiv.org/abs/2306.01711 OMNI: Open-endedness via Models of human Notions of Interestingness Open-ended algorithms aim to learn new, interesting behaviors forever. That requires a vast environment search space, but there are thus infinitely many possible tasks. Even after filtering for tasks the current agent can learn (i.e., learning progress), c arxiv.org https://twitter.com/jeffclune/..

https://n.news.naver.com/article/001/0013982125?sid=105 전직 정보당국자 "美 정부 UFO 잔해 확보 의혹 설명해야" 前 미 국방부 부차관보 폴리티코에 기고…"비밀 프로젝트 증언 확보" 주장 "국민도 알 필요 있어…기술혁신 등에 도움될 수도" 한 전직 미국 고위 정보당국자가 미확인 비행물체(UFO)와 관련한 것 n.news.naver.com https://www.fmkorea.com/best/5835663635 미국 NASA와 국방부, UFO 최신 연구 공식발표 - 미지의 검은 입방체 미국 NASA와 국방부, 1년간의 UAP(미확인변칙현상) 분석 브리핑한줄요약: 현대 과학으로 설명 불가능한 '반투명한 금속질 구체 안의 검은 입방체'가 발견되고 있다(용어참고: A..

https://nymag.com/intelligencer/2023/06/ex-intel-official-government-hiding-alien-tech.html Ex–Intelligence Official Says Government Hiding Alien Technology From Congress A whistleblower on the Pentagon’s UFO investigation team claims there is evidence of “intact” alien vehicles being hidden from lawmakers. nymag.com 이 뉴욕 매거진(Intelligencer) 기사는 미국 정부가 외계 기술을 은폐하고 있다는 전 인텔리전스 공식의 주장을 다루고 있습니다. 지난..

https://arxiv.org/abs/2305.19466 The Impact of Positional Encoding on Length Generalization in Transformers Length generalization, the ability to generalize from small training context sizes to larger ones, is a critical challenge in the development of Transformer-based language models. Positional encoding (PE) has been identified as a major factor influencing l arxiv.org 설명: https://twitter.com..

https://arxiv.org/abs/2306.00323 Thought Cloning: Learning to Think while Acting by Imitating Human Thinking Language is often considered a key aspect of human thinking, providing us with exceptional abilities to generalize, explore, plan, replan, and adapt to new situations. However, Reinforcement Learning (RL) agents are far from human-level performance in any arxiv.org https://twitter.com/jef..

abs: https://arxiv.org/abs/2306.00739 SQL-PaLM: Improved Large Language ModelAdaptation for Text-to-SQL One impressive emergent capability of large language models (LLMs) is generation of code, including Structured Query Language (SQL) for databases. For the task of converting natural language text to SQL queries, Text-to-SQL, adaptation of LLMs is of paramo arxiv.org 1. 대형 언어 모델(LLM)의 놀라운 능력 중 ..

abs: https://arxiv.org/abs/2306.00008 Brainformers: Trading Simplicity for Efficiency Transformers are central to recent successes in natural language processing and computer vision. Transformers have a mostly uniform backbone where layers alternate between feed-forward and self-attention in order to build a deep network. Here we investigat arxiv.org 1. 트랜스포머는 자연어 처리와 컴퓨터 비전의 최근 성공에 중심 역할을 하는데, ..

https://arxiv.org/abs/2305.19452 Bigger, Better, Faster: Human-level Atari with human-level efficiency We introduce a value-based RL agent, which we call BBF, that achieves super-human performance in the Atari 100K benchmark. BBF relies on scaling the neural networks used for value estimation, as well as a number of other design choices that enable this sca arxiv.org https://github.com/google-re..