Welcome to the Intellegens newsletter, where we share the latest news, developments, and achievements from the team at Intellegens.
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Webinar – Training realistic ML models
Just getting started with machine learning can be difficult. There are many challenges in building an ML model from real, messy, experimental or process data. In this webinar, we’ll outline some of those difficulties and how they are overcome in the Alchemite™ Suite software. We’ll discuss issues such as handling missing data, uncertainty in both the model and experimental measurements, and coping with varied data types such as categoricals and ordinals. We’ll show how Alchemite™ overcomes such challenges to make building and applying a machine learning model a simple process, possible in a few button-clicks, and we’ll demonstrate some new features, designed based on user feedback, that fine-tune this process.
New white paper – Alchemite explained
If you’d like a glimpse into some of the methodology and mathematics behind the Alchemite™ machine learning algorithm, then you might be interested to read a new white paper authored by our CSO, Gareth Conduit.
New features make for fast, easy model creation
A series of newly-released enhancements to the Alchemite™ Suite apps make it even easier to create and apply machine learning models. The changes, based on user feedback and requests, include: slick handling of discrete numerical data, or ordinals; preserving contextual information while reducing the need for data cleaning; and more features to manage and use relationships between columns of data. The results are faster data upload and model creation and more realistic modelling, analysis, and predictions.
Blog – One size does not fit all
Our latest blog reflects on our recent Alchemite™ Suite product launch, which came amid continuing global excitement about AI breakthroughs. The focus of our launch was slightly different – what can we do to make the AI technology we already have as useful as possible? That question led us to some deep thinking about the machine learning tools people actually need for R&D.
Published paper – ML for Laser AM
Intellegens scientist Joel Strickland is a co-author on a new paper that applies machine learning to support a robust tool for predicting residual stresses and mitigating distortion in Laser Powder Bed Fusion (LBPF) processes. These are key factors in optimising design and manufacturing practices for this Additive Manufacturing technology.
Recorded webinar: Alchemite™ Suite Launch
In case you missed it, you can now watch a recording of the recent online session that demonstrated a new generation of machine learning tools for R&D in chemicals, materials, life sciences, FMCG, and manufacturing. Alchemite™ Suite delivers a set of supremely easy-to-use software apps targeted on key tasks for development teams. See how you can: set up Design of Experiments (DOE) runs in a few button-clicks; accelerate formulation development with tools that have helped to cut months from development timescales; and generate deep insights from R&D data.
Connect with us at these upcoming events.
24 Apr – Webinar: Training ML models with real experimental and process data
15 May – NPTMI Workshop: Automated Formulation Mindset (Liverpool, UK)
21-22 May – CHEM UK (Birmingham, UK)
15-19 Jun – AI in Materials & Manufacturing (Anaheim, CA)
9-10 Jul – The Advanced Materials Show (Birmingham, UK)
