calpaterson-com-gg1ovh.txt (13969B)
1 Cal Paterson | [1]Home [2]Services [3]About 2 3 Building LLMs is probably not going be a brilliant business 4 5 November 2024 6 7 The Netscapes of AI 8 9 image of early 20th century train advert for Watford Railways improved the 10 lives of millions - but investors were rewarded with a [4]dramatic bust 11 12 Large language models (LLMs) like Chat-GPT and Claude.ai are whizzy and cool. A 13 lot of people think that they are going to be The Future. Maybe they are — but 14 that doesn't mean that building them is going to be a profitable business. 15 16 In the 1960s, airlines were The Future. That is why old films have so many 17 swish shots of airports in them. Airlines though, turned out to be an 18 unavoidably rubbish business. I've flown on loads of airlines that have gone 19 bust: Monarch, WOW Air, Thomas Cook, Flybmi, Zoom. And those are all busts from 20 before coronavirus - times change but being an airline is always a bad idea. 21 22 That's odd, because other businesses, even ones which seem really stupid, are 23 much more profitable. Selling fizzy drinks is, surprisingly, an amazing 24 business. Perhaps the best. Coca-Cola's return on equity has rarely fallen 25 below 30% in any given year. That seems very unfair because being an airline is 26 hard work but making coke is pretty easy. It's even more galling because 27 Coca-Cola don't actually make the coke themselves - that is outsourced to 28 "bottling companies". They literally just sell it. 29 30 Industry structure - what makes a business good 31 32 If you were to believe LinkedIn you would think a great business is made with 33 efficiency, hard work, innovation or some other intrinsic reason to do with how 34 hardworking, or clever, the people in the business are. That simply is not the 35 case. 36 37 What makes a good business is industry structure. 38 39 Airlines - unfavourable industry structure 40 41 To be an airline is to be in an almost uniquely terrible market position. For 42 starters, there are only two makers of aeroplanes (Airbus and Boeing). For 43 reasons of training and staff efficiency, you have to commit to one or the 44 other, which gives the aeroplane makers very strong pricing power. 45 46 And buyers of airline tickets are incredibly fickle and have no loyalty. They 47 will switch from one "carrier" to another over even small differences in price. 48 Annoyingly, there are loads of other airlines and they're all running the same 49 routes as you! 50 51 Worse yet, starting a new airline is surprisingly easy. Aircraft hold their 52 value so banks will happily lend against them. There are loads of staff 53 available that new entrants can hire. So randos will continually enter your 54 market, often selling tickets below cost for quite a while before they go bust. 55 And to top it off, there are plenty of substitutes for air travel - from 56 government-subsidised high speed trains to Zoom calls. 57 58 Airlines that get more efficient, work harder or come up with innovations 59 aren't going to be able to "capture" the value of what they've done. If you 60 make more than the bare minimum to survive Airbus will notice that you're being 61 undercharged and you'll find that the next renewal on your service contract 62 eats up the difference. 63 64 Fizzy-drinks - very favourable industry structure 65 66 Being the Coca-Cola company is pretty great though. 67 68 Coke is just water, colourant, flavouring, caffeine and sweetener. Those are 69 all widely available and really cheap. And as I said, you don't even have to 70 combine them yourselves - bottling companies will do that for you for almost 71 nothing. 72 73 Handily, consumers are really picky about what goes in their mouth. The 74 unofficial motto of your main competitor is "Is Pepsi ok?". This is despite the 75 fact that they are identical in both taste and colour. And a significant 76 minority of people actually say no! 77 78 And it isn't easy for new competitors to enter the market. They can't call 79 their new drink "coke" due to trademarks. They have to call it something else. 80 And consumers will generally refuse it because drinking an alternative is 81 considered some kind of weird statement. 82 83 What is industry structure? 84 85 Classically, there are five basic parts ("forces") to a company's position: 86 87 1. The power of their suppliers to increase their prices 88 2. The power of their buyers to reduce your prices 89 3. The strength of direct competitors 90 4. The threat of any new entrants 91 5. The threat of substitutes 92 93 It's industry structure that makes a business profitable or not. Not 94 efficiency, not hard work and not innovation. 95 96 If none of the forces are very much against you, your business will do ok. If 97 they are all against you, you'll be in the position of the airlines. And if 98 they're all in your favour: brill, you're Coca-Cola. 99 100 The industry structure of LLM makers: OpenAI/Anthropic/Gemini/etc 101 102 So is the position of LLM makers any good? I'm afraid it's not good news. 103 104 LLM makers sometimes imply that their suppliers are cloud companies like Amazon 105 Web Services, Google Cloud, etc. That wouldn't be so bad because you could shop 106 around and make them compete to cut the huge cost of model training. 107 108 Really though, LLM makers have only one true supplier: NVIDIA. NVIDIA make the 109 [5]chips that all models are trained on - regardless of cloud vendor. And that 110 gives NVIDIA colossal, near total pricing power. NVIDIA are more powerful 111 relative to Anthropic or OpenAI than Airbus or Boeing could ever dream of 112 being. 113 114 How much power do buyers have over LLM token prices? So far, it seems fairly 115 high. Most LLM users seem willing to change from Chat-GPT to Claude, for 116 example. It doesn't seem like brand loyalty is being built up. And companies 117 that build AI into their businesses are starting to do so via abstraction 118 layers that allow them to switch model easily. That makes LLMs interchangeable 119 - which is bad for those who sell them. 120 121 What's the strength of direct competitors? Again, it is considerable. There are 122 loads of LLM vendors and pricing [6]appears competitive. Worst of all, Facebook 123 basically dump their model on the market for no cost. It's [7]reminiscent of 124 Internet Explorer - not exactly a great portent. 125 126 And it seems fairly easy for new entrants to build brand new models. That is 127 why there are so many LLM makers. Most of the techniques for making LLMs are 128 openly published in papers. Even bad models can gain customers if they are 129 cheap, which allows new entrants to gain a foothold. 130 131 The situation on substitutes is mixed. Instead of having Chat-GPT write some 132 text you could pay a person to do it instead. That is likely to be much more 133 expensive but also less likely to hallucinate, which might be important for 134 some use-cases (law is the field least likely to use LLMs). And then there is 135 the trend that [8]metadata tends to displace artificial intelligence once 136 particular application has been proved out - so as soon as you find a solid 137 use-case you stand to be replaced. 138 139 A single mildly positive point does not make a profitable business. LLM makers 140 look a lot more like Netscape - who invented graphical web browsers, then went 141 bust - than Google, who made something good that ran on top of the web 142 browsers. 143 144 How are they raising so much money? 145 146 If LLM makers seem cursed to an airline-style business destiny, how come they 147 are able to raise so much money? OpenAI [9]raised $6.6 billion at a valuation 148 of $157 billion less than two months ago. That might be the biggest VC round of 149 all time. 150 151 What do they know that I don't? It is a mystery - but let's consider the 152 options. 153 154 Perhaps they are hoping to develop their own chips to reduce their dependence 155 on NVIDIA. $6.6 billion is not enough to build a new fab but it might be enough 156 to get a new chip designed which allows them to migrate off NVIDIA. That would 157 save them paying so much money for GPU time. But, NVIDIA are actually one of 158 the investors in the round (although only a fairly small amount) - so it's 159 unlikely "develop an NVIDIA competitor" was on any of the pitch deck slides. 160 161 Perhaps OpenAI are hoping to build a strong brand so that customers won't 162 switch to competitors so easily. It's not impossible, there is proof the [10] 163 branding and lock-in can work in technology - but it seems difficult to manage 164 given that LLMs themselves generically have a textual interface - meaning that 165 there is no real API as such - you just send text, and it sends text back. 166 167 Can they do anything about new entrants? Possibly. If investing $6.6bn allows 168 them to develop a major improvement in their model then that would raise 169 everyone else's costs considerably and probably force some of their smaller 170 competitors out of the market. The trouble is that money is the most fungible 171 of all goods (that is the point, after all) and that $6.6bn is not all that 172 much of it. So this round wouldn't, by itself, be enough to dissuade others. I 173 used to work at a bank and I can tell you that individual bond raises can be a 174 lot more than $6.6bn. 175 176 It's worth saying that even companies that raise huge sums of money sometimes 177 turn out to have no viable business. WeWork ultimately raised over $10bn at a 178 valuation of $47bn before it was realised that their business simply did not 179 make sense. WeWork were valued at just $0.56bn in their most recent financial 180 restructuring - having lost well over 95% of what was invested. 181 182 Not all AI companies are doomed 183 184 If LLM makers aren't going to be good businesses, does that bode ill for The 185 Future? 186 187 Firstly, it does not mean the technology will be bad. Whether the technology 188 ends up being good or not is mostly unrelated to whether Open AI/Anthropic/ 189 Mistral/whoever makes any money off it. Container virtualisation technology is 190 pretty well developed even though Docker made almost nothing on it. Web 191 browsers are extremely advanced pieces of software even though making a browser 192 is such a bad business that most don't usually count it as a business at all. 193 And CRMs are terrible despite the fact that Salesforce is tremendously 194 successful. Technology success and business success are mostly unrelated. 195 196 And then: not all AI businesses are building models. Ideally, if I were running 197 an AI business I would avoid building a model at all costs. Building your own 198 models looks like an undifferentiated schlep. Using a tiny bit of some 199 expensively trained model that Anthropic has produced could be very cost 200 effective and might make some business idea work that wouldn't have 5 years 201 ago. 202 203 Beware software companies that aren't software companies 204 205 Software companies are really good businesses. You have no real suppliers, your 206 software is often unique (so no competitors) and the substitute is just users 207 doing the job themselves. For this reason, software companies tend have really 208 great margins. 209 210 The problem is that not all technology companies are software companies. If you 211 have a hugely powerful single supplier like NVIDIA then the economics of your 212 company are going to look less like Microsoft Office and more like [11]Pan-Am. 213 214 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 215 216 Contact/etc 217 218 Write to me at [12][email protected] about this article, especially if you 219 disagreed with it. 220 221 See [13]other things I've written or learn more about me on [14]my about page. 222 223 Get an alert when I write something new, by [15]email or [16]RSS[17] rss-logo. 224 225 I am on: 226 227 • [18]Bluesky 228 • [19]Mastodon 229 • [20]Twitter 230 • [21]Github 231 • and [22]Linkedin. 232 233 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 234 235 Other notes 236 237 The AI safety movement is a fantastic hypeman for LLMs as a technology. 238 Implying (pretty dubiously) that we are [23]10 minutes from midnight in some 239 kind of Ghost-in-The-Shell style AI crisis is in fact an extremely effective 240 form of product marketing. Perhaps that is why OpenAI and others employ so many 241 AI safety specialists. 242 243 The Coca-Cola company mainly sit back and rake in the megabucks - but they do 244 spend a little bit of their earnings on research. And a little bit of a lot is 245 still significant. It's interesting that coke's market research has discovered 246 that coke works better as a gender segregated product: Coke Zero is Diet Coke, 247 but for men. 248 249 If you want to read more about industry structure and market strategy, the 250 place to start is with Michael Porter. He reworked his famous essay [24]The 251 Five Forces that Shape Corporate Strategy in 2008. It's not the last word, but 252 it probably should be the first word you read if you want to learn more. And if 253 you like it, he has a lot more. 254 255 256 References: 257 258 [1] https://calpaterson.com/ 259 [2] https://calpaterson.com/services.html 260 [3] https://calpaterson.com/about.html 261 [4] https://en.wikipedia.org/wiki/Railway_Mania 262 [5] https://en.wikipedia.org/wiki/Hopper_(microarchitecture) 263 [6] https://a16z.com/llmflation-llm-inference-cost/ 264 [7] https://en.wikipedia.org/wiki/Browser_wars#First_browser_war_(1995%E2%80%932001) 265 [8] https://calpaterson.com/metadata.html 266 [9] https://www.reuters.com/technology/artificial-intelligence/openai-closes-66-billion-funding-haul-valuation-157-billion-with-investment-2024-10-02/ 267 [10] https://calpaterson.com/amazon-premium.html 268 [11] https://en.wikipedia.org/wiki/Pan_Am 269 [12] mailto:[email protected] 270 [13] https://calpaterson.com/ 271 [14] https://calpaterson.com/about.html 272 [15] https://calpatersonltd.eo.page/calpaterson 273 [16] https://calpaterson.com/calpaterson.rss 274 [17] https://calpaterson.com/calpaterson.rss 275 [18] https://bsky.app/profile/calpaterson.bsky.social 276 [19] https://fosstodon.org/@calpaterson 277 [20] https://twitter.com/cal_paterson 278 [21] https://github.com/calpaterson/ 279 [22] https://www.linkedin.com/in/calpaterson 280 [23] https://en.wikipedia.org/wiki/Doomsday_Clock 281 [24] https://hbr.org/2008/01/the-five-competitive-forces-that-shape-strategy