"We once wanted to develop our own artificial intelligence systems. We very quickly came to the conclusion that we were unable to do it ourselves". Learn more in the full length success story with Dorfner here: https://t.co/mUj0qWkKrg
We've synthesized 12 years of experience into 5 pages. Find out how so many of our customers get value from AI in their first year. Gain insight from our top 3 tips and hear directly from our customers in linked videos.
https://t.co/7dzg6RAa8m
Pioneering the future of materials science since 2013! We’ve partnered with national labs, DOD, and DOE—now thrilled to advance US scientific discovery with @ Genesis Mission. Here's to accelerating innovation together!
https://t.co/lrefHp5iFR
https://t.co/q9cNGowTZm
🚀 The next paradigm in materials AI is here.
Join us for our upcoming webinar — Transformative Materials AI Capabilities — to see how the latest advancements can reshape your product development strategy.
https://t.co/rCJLw33Iys
#ELN#materialsinformatics#ai
Our VP of Strategy and Operations Stephen Edkins, Ph.D. is looking forward to speaking at the SCSK Corporation Materials Lab on Wednesday.
https://t.co/GTUVgrbZnL
Last chance to join the AI Talk panel session on "How not to fail at AI". Hear from Director of Research at Syensqo, David Thomas and Citrine Informatics' COO Kyle Killebrew
https://t.co/AirhZHJp8w
#ai#chemicals#Digitaltransformation
Subscribe to our YouTube channel to snack on materials informatics shorts and devour our videos on AI-driven chemical research and development. Each month we will be releasing new insightful content.
#materialsinformatics#ai#chemicals#materials
https://t.co/xdAoS76t7o
Our CEO Greg Mulholland shared insights into his leadership philosophy with Gene Hamnett of the Growth Think Tank podcast today. You can dive into session and learn more about Citrine's mission, vision and culture here.
https://t.co/pAL7A9pVQj
In this webinar:
• What is materials informatics used for, and how does it create business value?
• How much and what type of data do we need to get started?
• Why is AI more efficient than Design of Experiment and traditional trial-and-error methods?
https://t.co/iepCTcmUVx
In The Independent today: "Why Can't I Use ChatGPT for Everything?"
Read this article to understand the distinction between LLMs and the small data machine learning necessary when dealing small datasets generated through physical experiments.
#AI#LLM
https://t.co/bsmphiljk6
In the chemical and materials world, experiments are physical and therefore datasets are small. And that's just one reason, why you can't use ChatGPT for Chemical R&D.
Read this article to find out more.
https://t.co/7fME07HW8M