Thanks for the insight, I’m no expert on this topic so I’ve been going off conversations with friends in the space, RethinkX, and I take a first principles approach to solving problems.
I read the study and the conclusion seems to say the top problems are metabolic efficiency enhancements and the development of low-cost media from plant hydrolysates. But there are a lot of other engineering problems.
However I didn’t see any fundamental problems (physics based) that would force a floor on how good it can get. There were and are plenty of engineering problems with making batteries & solar cheaper as well (and AI better).
I also took at look at the forecasting articles, and they all seem to revolve around explicitly looking at cell based meat predictions and the bad predictions made by startups in the space.
“from what I recall I didn’t find it especially compelling. Are there any particular attributes or analyses that stood out to you, besides the reputation of its publisher?”
I read the entire report a few years ago, and I found it quite compelling. I’ve studied the s-curve adoption of many technologies and I’ve found the ’Seba Disruption Framework” to be very reliable. It’s not just their reputation, I’ve personally seen their predictions in other spaces be far more accurate than other prediction organizations.
I’m interested to know what you found particularly uncompelling about the report?
Let’s talk raw materials. The vast majority of the elemental components of meat can be sourced directly from the air using electricity. Carbon, hydrogen, oxygen, and nitrogen. Some minerals and other elements (Sulphur Iron, Zinc, Selenium) would need to be sourced, which would entail transportation to a factory for processing. I asked GPT4 to calculate the cost of the needed mined materials for one lb of steak.
Sulphur: Typically found at about 0.3% in meat.
Average cost: $65 per ton.
Cost in one pound of steak: 0.003 * 1/2000 * $65 ≈ $0.0000975
Iron: Around 0.007% in meat.
Average cost: $120 per ton.
Cost in one pound of steak: 0.00007 * 1/2000 * $120 ≈ $0.000042
Zinc: Around 0.0035% in meat.
Average cost: $2,500 per ton.
Cost in one pound of steak: 0.000035 * 1/2000 * $2,500 ≈ $0.04375
Selenium: Extremely trace amounts, around 0.000035% in meat.
Average cost: $65 per pound (Selenium is often priced per pound due to its rarity).
Cost in one pound of steak: 0.00000035 * $65 ≈ $0.00002275
Adding these up, the total elemental cost of Sulphur, Iron, Zinc, and Selenium in one pound of steak would be approximately $0.044.
Each pound of meat needs ~4.4¢ of mined material. Every other cost is in the production process.
They did similar calculations for the cost of lithium ion batteries, which were over 100X more expensive decades ago and are now approaching the material cost.
I agree this stuff doesn’t ensure public acceptance, but I’ve never seen public acceptance not change in the past with other disruptions. Most people in the original PTC studies put price as their #1 issue, and that’s the same answer I’ve gotten from anecdotal conversations (including conservatives). There’s also a page or two in the report that addresses public acceptance.
Also if this takes most of the meat demand, economics of scale dictate that animal meat costs will rise, further accelerating the S-curve disruption.
The time horizon they’ve predicted is cheaper than conventional meat by 2030, and ~80% cheaper by 2035.
Hi Michael, thanks for engaging; just flagging this will be my last reply on this thread :)
Quickly reviewing the RethinkX report, it seems like the dramatic changes forecast on very short timelines have not come to pass:
Precision fermentation beef is not currently ~$2/kg (Figure 11)
30% of the US beef ‘tissue’ market is not from cultured or precision fermentation (Figure 12)
US cattle population is forecast to decline ~80M but remains steady at 94M as of 2021
Similarly, US chicken populations remain stable
The cost curves in Fig 5 does not cite any source for the data, but I suspect they’re using the Mark Post’s ‘million dollar burger’ as a data point; this cost doesn’t reasonably represent a price estimate since the burger was never for sale or purchased at that price, but does induce a dramatically negative slope on the curve.
I take a first principles approach to solving problems.
I don’t really know what this means, or how it differs from, for example, knowledge of chemistry, a field which generally builds on ‘first principles’ in some sense. In any event, the resulting reasoning, which sets trivially low input costs, seems wrong. For example, this reasoning would not explain why the price of all organic chemicals is not roughly uniform and similarly extremely low, since most organics are simply carbon, hydrogen and oxygen. Furthermore, why would this reasoning not also apply to the animal-based chicken industry, ~eliminating their costs for feed and fuel?
I’ve never seen public acceptance not change in the past with other disruptions.
This seems circular: a technology wouldn’t be a disruption unless it was widely accepted. So, by definition, a disruptive technology is accepted by the public. This is also a result of survivorship bias—presumably some potentially ‘disruptive’ technologies did not result in disruption because they were not accepted by the public.
Thanks Jacob, I definitely appreciate your input too as I am no expert on the production of cellular meat or precision fermentation. I’m generally interested in reducing costs of living & reducing suffering.
That said here are my thoughts on what you said.
I entirely agree that their predictions in this space in the near term have proven inaccurate on the market. However the $2 figure might not be referring to sales costs, but the cost of production in a large state of the art factory.
Basically if an optimized factory was built with the best 2023 technology, could they get the cost of production below $2/Kg?
We’re in complete agreement about their 2023 timeline predictions, they were overly optimistic. What’s important though is if the overall cost curve over the next decade is going to take the shape they’ve predicted (exponential declines versus linear or logarithmic).
With input costs, cows & chickens are inefficient machines that require massive amounts of (water especially) input materials, land area, and maintenance. I agree the feed & fuel costs for animals could in theory be reduced by an order of magnitude, but animals will always be inefficient.
Importantly, if PF & cell based meats take market share from the most affordable meats first (ground beef & whatever chicken nuggets are made of), the animal meat sellers will encounter a negative feedback loop as they loose economies of scale and margins reduce.
By disruptions, I mean any system that is 5X or more better at doing something than the incumbent system.
You’re right that PF Meats are not—yet—a disruptive technology, I should have worded it better, but I the costs are declining by a consistent percentage each year. If the cost keeps declining exponentially according to Wrights Law, these predictions will come to pass.
At the end of the day, how much room for improvement is there in R&D and mass manufacturing in this space?
How much extra room can be created by AI enabled advancement, protein folding, robotics advancement, and rapidly lowering energy acquisition costs?
Thanks for the insight, I’m no expert on this topic so I’ve been going off conversations with friends in the space, RethinkX, and I take a first principles approach to solving problems.
I read the study and the conclusion seems to say the top problems are metabolic efficiency enhancements and the development of low-cost media from plant hydrolysates. But there are a lot of other engineering problems.
However I didn’t see any fundamental problems (physics based) that would force a floor on how good it can get. There were and are plenty of engineering problems with making batteries & solar cheaper as well (and AI better).
I also took at look at the forecasting articles, and they all seem to revolve around explicitly looking at cell based meat predictions and the bad predictions made by startups in the space.
It might be much better to forecast based on the historical price declines of precision fermentation per kg over the last several decades which this covers: https://rethinkdisruption.com/the-roadmap-to-disruption/
“from what I recall I didn’t find it especially compelling. Are there any particular attributes or analyses that stood out to you, besides the reputation of its publisher?”
I read the entire report a few years ago, and I found it quite compelling. I’ve studied the s-curve adoption of many technologies and I’ve found the ’Seba Disruption Framework” to be very reliable. It’s not just their reputation, I’ve personally seen their predictions in other spaces be far more accurate than other prediction organizations.
I’m interested to know what you found particularly uncompelling about the report?
Let’s talk raw materials. The vast majority of the elemental components of meat can be sourced directly from the air using electricity. Carbon, hydrogen, oxygen, and nitrogen. Some minerals and other elements (Sulphur Iron, Zinc, Selenium) would need to be sourced, which would entail transportation to a factory for processing. I asked GPT4 to calculate the cost of the needed mined materials for one lb of steak.
Sulphur: Typically found at about 0.3% in meat. Average cost: $65 per ton. Cost in one pound of steak: 0.003 * 1/2000 * $65 ≈ $0.0000975
Iron: Around 0.007% in meat. Average cost: $120 per ton. Cost in one pound of steak: 0.00007 * 1/2000 * $120 ≈ $0.000042
Zinc: Around 0.0035% in meat. Average cost: $2,500 per ton. Cost in one pound of steak: 0.000035 * 1/2000 * $2,500 ≈ $0.04375
Selenium: Extremely trace amounts, around 0.000035% in meat. Average cost: $65 per pound (Selenium is often priced per pound due to its rarity). Cost in one pound of steak: 0.00000035 * $65 ≈ $0.00002275
Adding these up, the total elemental cost of Sulphur, Iron, Zinc, and Selenium in one pound of steak would be approximately $0.044.
Each pound of meat needs ~4.4¢ of mined material. Every other cost is in the production process.
They did similar calculations for the cost of lithium ion batteries, which were over 100X more expensive decades ago and are now approaching the material cost.
I agree this stuff doesn’t ensure public acceptance, but I’ve never seen public acceptance not change in the past with other disruptions. Most people in the original PTC studies put price as their #1 issue, and that’s the same answer I’ve gotten from anecdotal conversations (including conservatives). There’s also a page or two in the report that addresses public acceptance.
Also if this takes most of the meat demand, economics of scale dictate that animal meat costs will rise, further accelerating the S-curve disruption.
The time horizon they’ve predicted is cheaper than conventional meat by 2030, and ~80% cheaper by 2035.
Hi Michael, thanks for engaging; just flagging this will be my last reply on this thread :)
Quickly reviewing the RethinkX report, it seems like the dramatic changes forecast on very short timelines have not come to pass:
Precision fermentation beef is not currently ~$2/kg (Figure 11)
30% of the US beef ‘tissue’ market is not from cultured or precision fermentation (Figure 12)
US cattle population is forecast to decline ~80M but remains steady at 94M as of 2021
Similarly, US chicken populations remain stable
The cost curves in Fig 5 does not cite any source for the data, but I suspect they’re using the Mark Post’s ‘million dollar burger’ as a data point; this cost doesn’t reasonably represent a price estimate since the burger was never for sale or purchased at that price, but does induce a dramatically negative slope on the curve.
I don’t really know what this means, or how it differs from, for example, knowledge of chemistry, a field which generally builds on ‘first principles’ in some sense. In any event, the resulting reasoning, which sets trivially low input costs, seems wrong. For example, this reasoning would not explain why the price of all organic chemicals is not roughly uniform and similarly extremely low, since most organics are simply carbon, hydrogen and oxygen. Furthermore, why would this reasoning not also apply to the animal-based chicken industry, ~eliminating their costs for feed and fuel?
This seems circular: a technology wouldn’t be a disruption unless it was widely accepted. So, by definition, a disruptive technology is accepted by the public. This is also a result of survivorship bias—presumably some potentially ‘disruptive’ technologies did not result in disruption because they were not accepted by the public.
Thanks Jacob, I definitely appreciate your input too as I am no expert on the production of cellular meat or precision fermentation. I’m generally interested in reducing costs of living & reducing suffering.
That said here are my thoughts on what you said.
I entirely agree that their predictions in this space in the near term have proven inaccurate on the market. However the $2 figure might not be referring to sales costs, but the cost of production in a large state of the art factory.
Basically if an optimized factory was built with the best 2023 technology, could they get the cost of production below $2/Kg?
We’re in complete agreement about their 2023 timeline predictions, they were overly optimistic. What’s important though is if the overall cost curve over the next decade is going to take the shape they’ve predicted (exponential declines versus linear or logarithmic).
With input costs, cows & chickens are inefficient machines that require massive amounts of (water especially) input materials, land area, and maintenance. I agree the feed & fuel costs for animals could in theory be reduced by an order of magnitude, but animals will always be inefficient.
Importantly, if PF & cell based meats take market share from the most affordable meats first (ground beef & whatever chicken nuggets are made of), the animal meat sellers will encounter a negative feedback loop as they loose economies of scale and margins reduce.
By disruptions, I mean any system that is 5X or more better at doing something than the incumbent system.
You’re right that PF Meats are not—yet—a disruptive technology, I should have worded it better, but I the costs are declining by a consistent percentage each year. If the cost keeps declining exponentially according to Wrights Law, these predictions will come to pass.
At the end of the day, how much room for improvement is there in R&D and mass manufacturing in this space?
How much extra room can be created by AI enabled advancement, protein folding, robotics advancement, and rapidly lowering energy acquisition costs?