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相关概念视频

Language Development01:22

Language Development

391
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
391
Language and Cognition01:27

Language and Cognition

359
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
359
Language01:16

Language

236
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
236
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.4K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.4K
Components of Language01:24

Components of Language

300
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
300
Cognitive Learning01:21

Cognitive Learning

268
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
268

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相关实验视频

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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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阿利罗:一种利用大型语言模型的自动机器学习工具.

Hyunjun Choi1, Jay Moran1, Nicholas Matsumoto1

  • 1Department of Computational Biomedicine, Center for Artificial Intelligence Research and Education, Cedars Sinai Medical Center, West Hollywood, CA 90069, United States.

Bioinformatics (Oxford, England)
|October 5, 2023
PubMed
概括

阿利罗使用网络界面和大型语言模型为生物医学研究人员自动化机器学习分析. 这个开源工具简化了数据洞察力发现和算法选择.

科学领域:

  • 生物医学信息学是生物医学信息学.
  • 计算生物学是一种计算生物学.
  • 数据科学是数据科学.

背景情况:

  • 生物医学和医疗保健领域产生了庞大而复杂的数据集.
  • 使用机器学习 (ML) 分析这些数据对于非计算机科学家来说是个挑战.

研究的目的:

  • 推出Aliro,一个开源软件包,旨在简化ML分析.
  • 使研究人员能够与数据进行交互,并使用大型语言模型 (LLM) 检索/执行代码.

主要方法:

  • 阿利罗提供了一个用于自动化ML分析的Web界面.
  • 它集成了LLMs用于代码生成和数据交互.
  • 一个预训练的ML推系统有助于算法和超参数的选择.

主要成果:

  • 阿利罗加速发现新的数据洞察力.
  • 它为评估的模型和数据提供可视化工具.
  • 该软件自动化了ML算法和超参数选择.

结论:

  • 阿利罗降低了生物医学研究中ML采用的障碍.
  • 它使研究人员能够利用复杂的数据进行发现.

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  • 开源软件包有助于实现可重复和高效的数据分析.