材料科学&化学

科学研究開発リーダーが知っておくべき AI 概念トップ 10

4月 29, 2024

OpenAIのChatGPTやGoogleのBardなど、大規模言語モデル(LLM)は自然言語で人と対話する能力において著しい進歩を遂げました。 ユーザーが言葉で要望を入力すれば、LLMは「理解」し、適切な回答を返してくれます。

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科学における大規模言語モデルの重要性

6月 11, 2023

OpenAIのChatGPTやGoogleのBardなど、大規模言語モデル(LLM)は自然言語で人と対話する能力において著しい進歩を遂げました。 ユーザーが言葉で要望を入力すれば、LLMは「理解」し、適切な回答を返してくれます。

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Enthought at ACS 2023 Fall Meeting

Top 5 Takeaways from the American Chemical Society (ACS) 2023 Fall Meeting: R&D Data, Generative AI and More

8月 29, 2023

By Mike Heiber, Ph.D., Director, Professional Services & Customer Success, Materials Informatics The Ameri…

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ITは科学の成功にいかに寄与するか

4月 24, 2024

With the increasing importance of AI and machine learning in science and engineering, it is critical that the leadership of R&D and IT groups at innovative companies are aligned. Inappropriate budgeting, policies, or vendor choices can unnecessarily block critical research programs; conversely an “anything goes” approach can squander valuable resources or leave an organization open to novel security threats.

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Enthought | Generative AI in Materials Science and Chemistry

From Data to Discovery: Exploring the Potential of Generative Models in Materials Informatics Solutions

6月 30, 2023

Generative models can be used in many more areas than just language generation, with one particularly promising area: molecule generation for chemical product development.

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enthought-science-research-cells

The Importance of Large Language Models in Science Even If You Don’t Work With Language

6月 11, 2023

OpenAI’s ChatGPT, Google’s Bard, and other similar Large Language Models (LLMs) have made dramatic strides in their ability to interact with people using natural language. Users can describe what they want done and have the LLM “understand” and respond appropriately. 

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Enthought | Making the Most of Small Data in R&D

Making the Most of Small Data in Scientific R&D

3月 11, 2023

For many traditional innovation-driven organizations, scientific data is generated to answer specific immediate research questions and then archived to protect IP, with little attention paid to the future value of reusing the data to answer other similar or tangential questions.

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Enthought | Digital Transformation of the Materials Science R&D Lab

Digital Transformation of the Materials Science R&D Lab

3月 31, 2022

“Digital transformation”, “machine learning”, and “artificial intelligence&#8221…

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Enthought | Scientific Data

Extracting Value from Scientific Data to Accelerate Discovery and Innovation

2月 1, 2023

In the digital era, robust data tools are crucial for all companies and the science-driven industries like the life sciences, materials science, and chemistry are no exception.

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Enthought | Configuring a Neural Network

Configuring a Neural Network Output Layer

5月 18, 2023

Introduction If you have used TensorFlow before, you know how easy it is to create a simple neural network mod…

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