"MLOps Podcast #193" features Pierre Salvy, Head of Engineering at Cambrium. He discusses using AI to design proteins, creating a vegan collagen for cosmetics, lab-grown meats, molecular cheese, and less harmful plastics. They also touch on the cost of experiments, ski experiences, and the challenges of transitioning to a managerial role.
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Quick takeaways
AI can be used to design proteins with specific properties, revolutionizing sustainability in cosmetics and potentially other industries.
Cambrium has successfully developed a vegan collagen called No-Bac, eliminating the need for animal-based collagen and promoting sustainability.
Large language models and protein programming are advancing protein engineering and enabling the creation of innovative materials.
Deep dives
Using AI to Design Proteins and Materials
The podcast episode explores the use of AI in designing proteins and materials. The guest, Pierre, discusses how his company, Cambria, is using generative AI and a protein programming language to create innovative materials. He explains that proteins are like a language with building blocks called amino acids, and AI can be used to predict protein shapes and functions. The discussion also touches on the cost of experiments in biotech, the challenges of digitalizing lab processes, and the potential for using AI in material design and sustainability.
Creating Vegan Collagen as a Cosmetics Product
Pierre shares how Cambria has developed a product called No-Bac, which is a vegan human collagen for use in cosmetics. Traditional collagen is derived from animals, but Cambria uses genetic engineering to produce collagen using yeast instead. This innovative approach eliminates the need for animal-based collagen and addresses sustainability concerns. Pierre highlights the importance of demystifying GMOs and genetic engineering in the biotech industry. The success of No-Bac demonstrates how biotech companies can make real change and provide sustainable alternatives in various industries.
Using LLMs and Protein Programming
The podcast discusses the role of large language models (LLMs) and protein programming in protein engineering. Pierre describes how LLMs are being used to generate proteins with specific functions and properties, such as removing wrinkles or regenerating plastic. He explains that LLMs can guide the design of proteins by sifting through vast numbers of possibilities. This technology has advanced protein engineering and enabled the creation of innovative materials. Pierre also highlights the importance of data management and the challenges of training scientists to adopt a data-driven mindset in lab practices.
Addressing Sustainability Challenges and Regulation
Pierre discusses the sustainability challenges in the biotech industry and the impact of regulations. He emphasizes the need to move past misconceptions about genetically modified organisms (GMOs) and highlights the positive contributions GMOs have made in various fields. The conversation touches on the constraints faced by biotech startups due to high costs, long development timelines, and regulatory barriers. Despite these challenges, Pierre explains how Cambria is focused on creating sustainable materials and driving innovation. He also comments on the need for regulatory frameworks that support biotech advancements while ensuring safety and environmental responsibility.
The Future of Biotech and Material Design
The podcast delves into the future of biotech and material design. Pierre envisions expanding Cambria's product range beyond cosmetics. He mentions the potential for replacing unsustainable materials like plastics, and the company's goal of creating new materials that have a positive impact on sustainability. Pierre highlights the importance of bridging the gap between specialty high-priced chemicals and low-priced commodities through intermediate markets. He discusses the challenges and opportunities in industries such as glues, concrete, and space applications. The podcast ends on a note of optimism about the potential of biotech to solve environmental challenges and drive positive change.
Differences between serving models for data scientists and researchers, the cost of experiments, and similarities between language models and protein AI models
MLOps podcast #193 with Pierre Salvy, Head of Engineering at Cambrium, LLM in Material Production co-hosted by Stephen Batifol.
// Abstract
Delve into the world of proteins, genetic engineering, and the intersection of AI and biotech. Pierre explains how his company is using advanced models to design proteins with specific properties, even creating a vegan collagen for cosmetics. By harnessing the potential of AI, they aim to revolutionize sustainability, uncovering a future of lab-grown meats, molecular cheese, and less harmful plastics, confronting regulatory barriers and decoding the syntax and grammar of proteins.
// Bio
Head of Engineering at Cambrium, a biotech company utilising genAI to design sustainable protein biomaterials for the future.
Pierre spent the last decade researching ways to make computers calculate better biological systems. This is a critical step to engineering more sustainable ways to make the products we use every day, which is their mission at Cambrium.
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https://mlops.pallet.xyz/jobs
// MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
Website: cambrium.bio
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Connect with Pierre on LinkedIn: https://www.linkedin.com/in/psalvy/
Timestamps:
[00:00] Pierre's preferred coffee
[00:10] Takeaways
[05:10] Please like, share, and subscribe to our MLOps channels!
[05:25] Weights and Biases ad
[07:52] Ski story
[09:54] Pierre's career trajectory
[13:35] From employee #2 to hiring a team
[14:42] From employee #2 to head of engineering
[15:50] Uncomfortable things to say essential for growth and effectiveness
[18:27] From biotech to engineering
[21:10] LLMs at Cambrium
[24:26] Slackbot
[25:43] Quick and Easy Solutions
[26:47] Products created at Cambrium
[31:56] Impact of EU Regulation on Cambrium
[35:39] 2nd Biotech Winter
[36:35] Cost of error vs service not working
[38:00] Protein Synthesis and Mutations
[40:03] Large-Scale System Engineering Challenges
[43:28] Expensive Factors in Experiments
[44:39] LLMs vs Protein Models
[47:03] Protein Design with LLMs
[49:43] Eco-Friendly Product Vision
[53:28] Space glue
[54:00] Wrap up
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