Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Improving Translational Accuracy02:07

Improving Translational Accuracy

9.0K
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...
9.0K
Language Development01:22

Language Development

317
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...
317
Source Transformation01:15

Source Transformation

3.7K
Source transformation is a fundamental technique employed in circuit analysis, offering a valuable tool for simplifying complex electrical circuits. This technique involves the replacement of either a voltage source in series with a resistor by a current source in parallel with a resistor, or vice versa. The key concept here is that when the original sources are deactivated (turned off), the equivalent resistance at the circuit's end terminals remains the same.
It is essential to note that when...
3.7K
Language01:16

Language

193
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...
193
Components of Language01:24

Components of Language

243
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.
243
Language and Cognition01:27

Language and Cognition

323
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.
323

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Strain-induced crumpling of graphene oxide lamellas to achieve fast and selective transport of H<sub>2</sub> and CO<sub>2</sub>.

Nature nanotechnology·2025
Same author

Machine learning code snippets semantic classification.

PeerJ. Computer science·2023
Same author

Symbolic expression generation <i>via</i> variational auto-encoder.

PeerJ. Computer science·2023
Same author

Code4ML: a large-scale dataset of annotated Machine Learning code.

PeerJ. Computer science·2023
Same author

NFAD: fixing anomaly detection using normalizing flows.

PeerJ. Computer science·2021
Same author

SANgo: a storage infrastructure simulator with reinforcement learning support.

PeerJ. Computer science·2021
Same journal

DARUMA: a gateway to fast and easy prediction of intrinsically disordered regions.

PeerJ. Computer science·2026
Same journal

Alzheimer's disease detection using a quantum deep neural network with Haralick feature extraction and simulated annealing optimization.

PeerJ. Computer science·2026
Same journal

Network anomaly detection using Deep Autoencoder and parallel Artificial Bee Colony algorithm-trained neural network.

PeerJ. Computer science·2026
Same journal

An anomaly detection model for multivariate time series with anomaly perception.

PeerJ. Computer science·2026
Same journal

Retraction: A wormhole attack detection method for tactical wireless sensor networks.

PeerJ. Computer science·2026
Same journal

Evaluation of mental disorder with prioritization of its type by utilizing the bipolar complex fuzzy decision-making approach based on Schweizer-Sklar prioritized aggregation operators.

PeerJ. Computer science·2026
查看所有相关文章

相关实验视频

Updated: Jun 5, 2025

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

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

Published on: December 6, 2024

502

语言代码:在机器学习管道中创建转型代码的协同框架.

Ekaterina Trofimova1, Emil Sataev1, Andrey Ustyuzhanin2,3

  • 1Faculty of Computer Science, Higher School of Economics, Moscow, Russia.

PeerJ. Computer science
|December 9, 2024
PubMed
概括
此摘要是机器生成的。

Linguacodus使用微调的大型语言模型将自然语言任务描述翻译为可执行代码. 这个框架自动化代码生成,显著推进机器学习应用程序.

关键词:
自动代码生成自动化代码生成大型语言模型.机器学习的管道.

更多相关视频

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

2.1K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K

相关实验视频

Last Updated: Jun 5, 2025

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

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

Published on: December 6, 2024

502
Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

2.1K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 将自然语言任务描述翻译成可执行代码是机器学习的一个重大挑战.
  • 现有的方法往往需要大量的人工干预,缺乏强大的自动化.

研究的目的:

  • 引入Linguacodus,这是一个创新的框架,用于从自然语言描述中自动生成代码.
  • 为了证明微调的大型语言模型在将任务描述转化为功能代码中的有效性.

主要方法:

  • 开发Linguacodus,这是一个动态的管道,用于自然语言的代转换为代码.
  • 微调大型语言模型以评估和选择给定任务的最佳代码解决方案.
  • 关于在机器学习任务转换为代码过程中实现最小人际交互的算法的建议.

主要成果:

  • Linguacodus成功地将自然语言描述翻译成可执行的机器学习代码.
  • 在大型Kaggle数据集上进行了广泛的实验,验证了框架的有效性.
  • 证明了在各种科学领域广泛应用的潜力.

结论:

  • Linguacodus代表了机器学习自动化代码生成的重大进步.
  • 该框架有效地弥合了任务概念化和可执行代码之间的差距.
  • 在加速应用机器学习研究和开发方面,Linguacodus显示出了前景.