Life Sciences

Scientist leveraging AI

Top 10 AI Concepts Every Scientific R&D Leader Should Know

Feb 21, 2024

R&D leaders and scientists need a working understanding of key AI concepts so they can more effectively develop future-forward data strategies and lead the charge towards groundbreaking discoveries.

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Enthought | Why a Data Fabric is Essential in Modern R&D

Why A Data Fabric is Essential for Modern R&D

Nov 14, 2023

Scattered and siloed data is one of the top challenges slowing down scientific discovery and innovation today. What every R&D organization needs is a data fabric as part of their technology solution set.

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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-science-research-cells

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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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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Enthought | Scientific Data

Extracting Value from Scientific Data to Accelerate Discovery and Innovation

Feb 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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3 Trends for Scientists To Watch in 2023

Dec 19, 2022

As a company that delivers Digital Transformation for Science, part of our job at Enthought is to understand the trends that will affect how our clients do their science. Below are three trends that caught our attention in 2022 that we predict will take center stage in 2023. ChatGPT This one just showed up on…

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True DX in the Pharma R&D Lab Defined by Enthought

May 25, 2022

Enthought’s team in Japan exhibited at the Pharma IT & Digital Health Expo 2022 life sciences conference in Tokyo, to meet with pharmaceutical industry leaders gathering for technological insight and to revitalize market growth. 200 companies exhibited across the 3-day in-person event, which drew over 6,700 attendees. With digital transformation a headline theme, the show…

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Life Sciences Labs Optimize with New Digital Technologies and Upskilling

May 16, 2022

Labs are resetting the trajectory for drug development: reducing timelines from years to months; decreasing costs from billions to millions; and gaining an advantage by delivering drugs to market in months rather than decades. This value combination is a compelling case for investment in digital capability and organizational transformation. A 100x or 1000x advance in…

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Enthought | Configuring a Neural Network

Configuring a Neural Network Output Layer

May 18, 2023

Introduction If you have used TensorFlow before, you know how easy it is to create a simple neural network model using the Keras API. Just create an instance of the Sequential model class, add the number of desired layers and accompanying layer nodes, define the activation functions to be used by each layer, and compile…

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