The rapid advancement of artificial intelligence (AI) technology has the potential to transform operations across multiple industries, especially in chemical and materials development.
Despite this progress, generic AI approaches fail to transform slow and expensive traditional methods, highlighting an urgent need for innovative solutions that improve efficiency and sustainability.
This eBook examines how tailored AI strategies can revolutionize product development timelines and foster significant advancements in the field, paving the way for a more agile and effective approach to innovation.
Download this eBook to discover:
- The transformative potential of AI in accelerating innovation and product development
- Insights into overcoming the complexities and challenges faced in chemical and materials research
- Strategies to enhance sustainability and efficiency
Accelerate Product Development and Shrink Time to Market with AI for Science 1
From Months to Minutes:
Accelerate Product Development
and Shrink Time to Market
with AI for Science
E-BOOK
Accelerate Product Development and Shrink Time to Market with AI for Science 2
Introduction
Hello,
I am a 30+ year veteran of technology companies, a venture capitalist, and a board director of Fortune 500 companies like VMWare,
Motorola Solutions, and Costco.
Our world and our lives are built on the materials that we create, and the need for new chemicals and formulations used in these
materials continues to grow with no end in sight. But it is also widely known and accepted that developing these chemicals, materials
and formulations is a very slow and expensive business today. Could AI be the answer here?
AI can indeed help transform many business processes and some industries. But I’ve learned that a generic ML approach or one built
on the buzzy LLM-based “Generative AI” techniques won’t suffice for chemicals and materials. There is an urgent need for a specialized
approach, an “AI Platform for Science” if you will, that addresses the complex product development challenges in these industries.
I have gotten to know NobleAI well over the last couple of years as an independent board director. It has become clear to me that
NobleAI’s unique Science-Based AI technology is proving to be a viable and scalable solution for these very real challenges.
Please let us know if you have questions or would like more information.
Respectfully,
Kenneth D. Denman
General Partner
Sway Ventures
Table of Contents
01 Digital Transformation in Chemicals & Materials
02 The Need for AI for Science
03 NobleAI: Your Force Multiplier
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Accelerate Product Development and Shrink Time to Market with AI for Science 4
01. Digital Transformation in Chemicals & Materials
Digital transformation has been challenging for companies operating in the chemical and materials space.
This is primarily because chemical and material product development is incredibly complex, involving specialized scientific experimentation
across multiple parameters, often at multiple scales - from molecules to formulations, up to systems and processes.
Traditionally, much of this type of experimentation happens in the lab, which is cost-prohibitive, time-consuming and limited in scope. Some of it
is done via complex simulation models that require massive amounts of data and a team of scientists to build, test and maintain.
By embracing digital transformation, chemicals and materials companies can unlock their true potential, have sustainable growth and solidify
their position in an ever-changing environment.
Value is migrating from the traditional R&D departments of chemical companies to material informatics platforms
Process of discovering and developing new chemicals is primarily lab-based
Difficult to predict the behaviors of materials under new conditions
Requires many lab experiments, which is expensive, unproductive, and time-consuming
A clear disconnect exists between the accelerating pace of change in the marketplace and slowness of the innovation process
Today
Source: Deloitte analysis
Digital transformation has many benefits: greater operational efficiency, more and better data for decision making, improved safety and compliance,
meeting sustainability standards, promoting business resilience and creating competitive advantage.
Recent surveys and research shows increasing impact and spending patterns:
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In 2024, the chemical industry will spend $4.9 billion in the US on digital transformation with this steadily increasing to $6.4 billion in 2028.
– ABI issue for chemical businesses
Digitalization has become the 2nd-most prominent capital issue for chemical businesses - with 65% expecting it to impact their businesses.
- EY DigiChem SurvEY Aug 2022
Value is migrating from the traditional R&D departments of chemical companies to material informatics platforms
New business models, driven by digital ecosystems that combine products and services, enable technology
Rise of open digital platforms used in material informatics
Capabilities to accumulate vast amounts of material knowledge from varied sources into a single, reliable, searchable format
Machine learning algorithms help in developing new innovations quickly and efficiently
Tomorrow
Source: Deloitte analysis
The Need for Digital Transformation is Clear
“AI in recent months has become almost synonymous with large language
models, or LLMs, but in science there are a multitude of different model
architectures that may have even bigger impacts.”
— Eric Schmidt, MIT Technology Review, 7/5/23
Rather than GenAI, another approach to AI - one that applies numerous scientific principles that are relevant to questions being
investigated - is needed. One such approach, what we might call Specialized AI, uses small, carefully curated use-case-specific AI
models (Small Science-infused Models or SSMs). This “AI For Science” is already being used to help accelerate the development of
chemical and material products.
It would be hard not to notice that AI was one of the hottest technology topics in the past year and continues
to be top of mind.
AI is advancing rapidly and it’s revolutionizing everyday lives and businesses. From content creation, to investing, to enhancing customer
service, optimizing supply chains and more, AI is now omnipresent. This tsunami of interest and applications is powered
by a new set of AI techniques, collectively referred to as Generative AI.
But these Generative AI systems are not suitable for Chemicals & Materials
development for a variety of reasons including:
Data is not secure and can create potential legal risks.
Massive amount of data is needed, and to make matters worse, is usually not available.
Outputs can be misleading or flat out false (often referred to as “AI hallucination”).
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“…given the growing importance of AI in generating business insights and enabling decisionmaking logic, any digital transformation should also be an AI transformation.”
— McKinsey & Company, “What is digital transformation?” 6/14/23
A Catalyst for Change
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Scientific discovery has experienced several paradigms throughout history. Jim Gray, computer scientist, a Turing Award winner and Microsoft
Technical Fellow, has characterized the historical evolution of scientific discovery in four paradigms: empirical, theoretical, computational and
data-driven science.
It’s Time For A New Approach: The 5th Paradigm of Science*
In the last several years, however, a new paradigm of scientific discovery is emerging. This shift is fueled by new methods for optimizing datahungry machine learning for scientific discovery. This fifth paradigm of scientific discovery trains machine learning models with fundamental
equations of physical properties to generate highly accurate, data-efficient predictions of how products will perform in real-world scenarios.
When trained appropriately for specific problems, these predictions can be highly accurate and data efficient providing researchers viable
predictions in minutes not months.
02. The Need for AI for Science
* Microsoft 5th Paradigm Of Science
<— 1600s
EMPIRICAL SCIENCE
~ 1600s
THEORETICAL SCIENCE
COMPUTATIONAL SCIENCE
~ 1950 —> DATA-DRIVEN SCIENCE
~ 2010 —>
Utilize combinations of novel AI/ML techniques
Incorporate relevant scientific laws and principles
Work with limited amounts of data, securely &
without re-use
Rapidly generate useful and actionable
insights and predictions
ACCELERATED DISCOVERY
aka AI FOR SCIENCE
~ 2020 —>
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A powerful fusion of artificial intelligence and scientific knowledge, optimized for product development - brings the fifth paradigm to chemical
and material product innovation.
NobleAI’s unique approach to AI for science, Science-Based AI, utilizes an ensemble of machine learning models, appropriately selected to match
the needs of the material or product under development. These models are then layered with constraints and guidance from relevant physical
properties, data sets and empirical observations.
NobleAI’s Implementation of AI for Science
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Science-Based AI Success Stories
100x - 1000x
Improved Productivity
$10M - $100M
Enabled in Potential Sales
$5M - $25M
Saved in Operating Costs
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Are You Ready to Accelerate Your Product Development?
Perhaps you have a data scientists team. Perhaps you have AI Infrastructure already in place. Or perhaps, you aren’t quite sure how to
get started on your AI Journey. No matter where you find your organization, NobleAI is a partner and force multiplier for your efforts,
giving your organization the ability to move fast even when data is scarce and resources are limited.
With NobleAI, chemical and materials product development teams don’t have to spend countless cycles and resources building
solutions from scratch.
03. NobleAI: Your Force Multiplier
In the face of a host of challenges for the chemical and materials industry - from supply chain complexity, to new
regulations, to sustainability demands, to the need to innovate faster while doing more with less - companies
cannot rely solely on traditional research and development methods. Embracing digital technologies, especially AI
for Science, in chemicals and materials development is needed now more than ever.
With Science-Based AI, there is a massive opportunity to overcome these challenges to accelerate product
innovation, improve sustainability and supply chain efficiency and maximize R&D resources. We invite you to work
with us to unlock innovation, to develop and bring to market better products faster than ever possible before.
Respectfully,
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94% of leaders surveyed by Deloitte say AI will be critical to
the success of their organization over the next five years.
— Deloitte Research Center for Energy & Industrials, 2024 chemical industry outlook
Sunil M. Sanghavi
CEO
NobleAI
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Contact Us
Learn how NobleAI can help you accelerate your
product development & sustainability goals with
Science-Based AI.
E-mail:
contact@noble.ai
www.noble.ai
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