TL;DR:
- I’m an AI & Machine Learning consultant (12 years of experience with data).
- My website: www.weissnoa.com. TL;DR: research, machine learning, data science strategy, I worked with early stage startups as well as big companies like PayPal.
- Vegan for 10 years and counting
- I want to move to work full time on animal welfare projects if I can find such projects where my skill set has added value.
- I looked for promising problems that I think I might solve, I’ll list my top ones here (please give me feedback)
- I’m looking for funding to flesh these ideas out, implement them, and offer them to alternative protein companies
Ideas
1: Modeling of the extrusion process
What is this?
A physical machine where you put ingredients in, and plant-based meat comes out.
It’s widely used
The vast majority of plant-based meat solutions use this. It is also sometimes used for cultivated (lab-grown) meat.
It’s currently “voodoo”
Trial and error, mostly unpredictable.
It’s a classic problem for ML
Train a model to guess the result based on given ingredients.
In problems like this, the model often isn’t perfect but does help narrow down the search space significantly (for example, by recognizing that most sets of ingredients “obviously” won’t work)
2: Addressing bottlenecks in Alternative Protein companies using existing research
TL;DR:
- There are known bottle necks that are relevant for most alternative protein companies. For example: figuring out what stem cells are about to grow into as early as possible.
- There are existing solutions (in the form of published research) for these problems. For example, see this Nature article.
- These solutions are not ready for use (there’s a difference between an article and a production ready system).
- I hope I can help orgs integrate these solutions.
- After I do this for one org, scaling to other orgs will be much easier.
Some bottlenecks I might address
All bottlenecks here are known problems for alternative protein companies, according to the experts I spoke to, but please tell me if I’m wrong. For all problems here, there is at least one scientific paper that seems promising enough to explore (in my opinion).
- Identification of the beginning stages of neural stem cells differentiation into specific cell types
- Predicting cell response to different treatments
- Identify new potential cell cycle regulatory genes
If you’re an org that could use a solution for one or more of these problems, please get in touch!
Call to action
- Help me get funded to run this project
- Give me feedback on how to write a funding request for this project
Contact me
By messaging me here, or emailing [me at weissnoa dot com].
Thanks to Yonatan Cale for helping me with this post.
Hey Noa,
Thanks for writing this up!
As someone who's worked on similar stuff, I just wanted to pitch in with two thoughts (hopefully helpful!):
On extrusion modeling, I (& others) looked into something similar about 4-5 years ago and I personally I came away quite pessimistic for 2 reasons.i) The search space is practically a lot narrower than it seems (very limited by ingredients accessible and "suppliable" at scale).ii) Furthermore, an extrusion expert I spoke to thought that more of the variability probably came from ingredients rather than actual extrusion parameters so a model alone seemed unlikely to create "big" improvements to the texture / product quality.
Somewhat confirming this: I spoke to a senior researcher at a well known plant-based company + and an ex-one from a mainstream CPG company and they both confirmed that they'd tried something like this and came away from it without any real product improvements.
On the second idea, I have less to add but it may be worth checking out AMII's recent collab with New Harvest. More general hot take though: My (the low confidence) general impression has been that solving "big" fermentation / cultivated problems with an AI-ish approach has been somewhat bottlenecked by the ability to get good data and iterate (in other words, the "sensors" aren't great and limited). In-silico modeling is seemingly pretty far away too for most cell lines/platforms that I've heard folks talk about in recent years but unsure where that will go.
Other interesting things from an ML/AI perspective may be looking at areas like ingredient functionalization & processing for ingredient companies (ADM, Roquette etc.). The idea here would be to tweak processes to get better functionality or lower prices. There was some interest in this work 4-5 years ago but I haven't followed it much since.
Anyway, hope some of that is useful and that you find an interesting problem & funding!
Hi,
Thank you for this detailed reply! These are some very relevant facts. I know of some of the problems you mentioned, but the fact that others have tried and fail is new to me - I haven't been able to find anyone who attempted the same thing up until now.
I would love to talk to you about it f2f and get some more detail, if that's ok. Would you be willing to have a short call?