Jupyter AI Magics Are Not ✨Magic✨

Sep 5, 2023

It doesn’t take ✨magic✨ to integrate ChatGPT into your Jupyter workflow. Integrating ChatGPT into your Jupyter workflow doesn’t have to be magic. New tools are seemingly coming out daily to help write code using large language models (LLMs). They appear to have a considerable positive impact on developers’ lives. GitHub claims 88% percent of developers…

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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

Aug 29, 2023

By Mike Heiber, Ph.D., Materials Informatics Manager Enthought, Materials Science Solutions The American Chemical Society (ACS) is a premier scientific organization with members all over the world from both academia and industry. Some of my team and I recently returned from their primary annual convening, the ACS 2023 Fall Meeting, held in San Francisco. I…

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Real Scientists Make Their Own Tools

Aug 8, 2023

There’s a long history of scientists who built new tools to enable their discoveries. Tycho Brahe built a quadrant that allowed him to observe the path and distance of a comet as it crossed the solar system, helping to prove the heliocentric model of the way the stars and planets move. Galileo Galilei built his…

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How IT Contributes to Successful Science

Jul 26, 2023

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

Jun 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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7 Pro-Tips for Scientists: Using LLMs to Write Code

Jul 11, 2023

Scientists gain superpowers when they learn to program. Programming makes answering whole classes of questions easy and new classes of questions become possible to answer. If you have some programming experience, large language models (LLMs) can raise the ceiling of your performance and productivity. Using LLMs to write code turns a challenging recall task (What’s…

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

Jun 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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4 Reasons to Learn Xarray and Awkward Array—for NumPy and Pandas Users

Jun 5, 2023

You know it. We know it. NumPy is cool. Pandas is cool. We can bend them to our will, but sometimes they’re not the right tools for the job. Enter Xarray and Awkward Array. Read on for the four reasons why you need to learn these Python packages.   Reason 1:  You need labeled arrays of…

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Enthought | Pharma and BioPharma

Leveraging AI in Cell Culture Analysis

Mar 22, 2023

Mammalian cell culture is a fundamental tool for many discoveries, innovations, and products in the life sciences.

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7 Lesser-Known Command Line Tools That Ship with Python

Apr 10, 2023

Like most people, I mostly interact with Python using the default REPL or with IPython. Yet, I often reach for one of the Python tools that come with the standard library. All these tools are implemented as “mains” in the various scripts and modules. Here are 7 I use on a semi-regular basis. 1. &…

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