What We’re Reading (Week Ending 21 April 2024) - 21 Apr 2024
Reading helps us learn about the world and it is a really important aspect of investing. The late Charlie Munger even went so far as to say that “I don’t think you can get to be a really good investor over a broad range without doing a massive amount of reading.” We (the co-founders of Compounder Fund) read widely across a range of topics, including investing, business, technology, and the world in general. We want to regularly share the best articles we’ve come across recently. Here they are (for the week ending 21 April 2024):
1. The Anguish of Central Banking – Arthur F. Burns
Why, in particular, have central bankers, whose main business one might suppose is to fight inflation, been so ineffective in dealing with this worldwide problem?
To me, as a former central banker, the last of these questions is especially intriguing. One of the time-honored functions of a central bank is to protect the integrity of its nation’s currency, both domestically and internationally. In monetary policy central bankers have a potent means for fostering stability of the general price level. By training, if not also by temperament, they are inclined to lay great stress on price stability, and their abhorrence of inflation is continually reinforced by contacts with one another and with like-minded members of the private financial community. And yet, despite their antipathy to inflation and the powerful weapons they could wield against it, central bankers have failed so utterly in this mission in recent years. In this paradox lies the anguish of central banking…
…Analyses of the inflation that the United States has experienced over the past fifteen years frequently proceed in three stages. First are considered the factors that launched inflation in the mid-1960s, particularly the governmental fine tuning inspired by the New Economics and the loose financing of the war in Vietnam. Next are considered the factors that led to subsequent strengthening of inflationary forces, including further policy errors, the devaluations of the dollar in 1971 and 1973, the worldwide economic boom of 1972-73, the crop failures and resulting surge in world food prices in 1973-74, the extraordinary increases in oil prices that became effective in 1974, and the sharp deceleration of productivity growth from the late 1960s onward. Finally, attention is turned to the process whereby protracted experience with inflation has led to widespread expectations that it will continue in the future, so that inflation has acquired a momentum of its own.
I have no quarrel with analyses of this type. They are distinctly helpful in explaining the American inflation and, with changes here and there, that in other nations also. At the same time, I believe that such analyses overlook a more fundamental factor: the persistent inflationary bias that has emerged from the philosophic and political currents that have been transforming economic life in the United States and elsewhere since the 1930s. The essence of the unique inflation of our times and the reason central bankers have been ineffective in dealing with it can be understood only in terms of those currents of thought and the political environment they have created…
…the period from World War II to the mid-1960s was marked not only by a dampening of the business cycle but also by persistent increases in the prosperity of American families…
…This experience of economic progress strengthened the public’s expectations of progress. What had once been a quiet personal feeling that the long future would be better than the past, particularly for one’s children, was transformed during the postwar years into an articulate and widespread expectation of steady improvement in living standards—indeed, into a feeling of entitlement to annual increases in real income.
But the rapid rise in national affluence did not create a mood of contentment. On the contrary, the 1960s were years of social turmoil in the United States, as they were in other industrial democracies…
…In the innocence of the day, many Americans came to believe that all of the new or newly discovered ills of society should be addressed promptly by the federal government. And in the innocence of the day, the administration in office attempted to respond to the growing demands for social and economic reform while waging war in Vietnam on a rising scale. Under the rubric of the New Economics, a more activist policy was adopted for the purpose of increasing the rate of economic growth and reducing the level of unemployment…
…The interplay of governmental action and private demands had an internal dynamic that led to their concurrent escalation. When the government undertook in the mid-1960s to address such “unfinished tasks” as reducing frictional unemployment, eliminating poverty, widening the benefits of prosperity, and improving the quality of life, it awakened new ranges of expectation and demand. Once it was established that the key function of government was to solve problems and relieve hardships—not only for society at large but also for troubled industries, regions, occupations, or social groups—a great and growing body of problems and hardships became candidates for governmental solution…
…Many results of this interaction of government and citizen activism proved wholesome. Their cumulative effect, however, was to impart a strong inflationary bias to the American economy. The proliferation of government programs led to progressively higher tax burdens on both individuals and corporations. Even so, the willingness of government to levy taxes fell distinctly short of its propensity to spend. Since 1950, the federal budget has been in balance in only five years. Since 1970, a deficit has occurred in every year. Not only that, but the deficits have been mounting in size. Budget deficits have thus become a chronic condition of federal finance; they have been incurred when business conditions were poor and also when business was booming. But when the government runs a budget deficit, it pumps more money into the pocketbooks of people than it withdraws from their pocketbooks; the demand for goods and services therefore tends to increase all around. That is the way the inflation that has been raging since the mid-1960s first got started and later kept being nourished.
The pursuit of costly social reforms often went hand in hand with the pursuit of full employment. In fact, much of the expanding range of government spending was prompted by the commitment to full employment. Inflation came to be widely viewed as a temporary phenomenon—or, provided it remained mild, as an acceptable condition. “Maximum” or “full” employment, after all, had become the nation’s major economic goal— not stability of the price level. That inflation ultimately brings on recession and otherwise nullifies many of the benefits sought through social legislation was largely ignored…
…And so I finally come to the role of central bankers in the inflationary process. The worldwide philosophic and political trends on which I have been dwelling inevitably affected their attitudes and actions. In most countries, the central bank is an instrumentality of the executive branch of government—carrying out monetary policy according to the wishes of the head of government or the ministry of finance. Some industrial democracies, to be sure, have substantially independent central banks, and that is certainly the case in the United States. Viewed in the abstract, the Federal Reserve System had the power to abort the inflation at its incipient stage fifteen years ago or at any later point, and it has the power to end it today. At any time within that period, it could have restricted the money supply and created sufficient strains in financial and industrial markets to terminate inflation with little delay. It did not do so because the Federal Reserve was itself caught up in the philosophic and political currents that were transforming American life and culture…
…Facing these political realities, the Federal Reserve was still willing to step hard on the monetary brake at times—as in 1966, 1969, and 1974—but its restrictive stance was not maintained long enough to end inflation. By and large, monetary policy came to be governed by the principle of undernourishing the inflationary process while still accommodating a good part of the pressures in the marketplace. The central banks of other industrial countries, functioning as they did in a basically similar political environment, appear to have behaved in much the same fashion.
In describing as I just have the anguish of central banking in a modern democracy, I do not mean to suggest that central bankers are free from responsibility for the inflation that is our common inheritance. After all, every central bank has some room for discretion, and the range is considerable in the more independent central banks. As the Federal Reserve, for example, kept testing and probing the limits of its freedom to undernourish the inflation, it repeatedly evoked violent criticism from both the Executive Branch and the Congress and therefore had to devote much of its energy to warding off legislation that could destroy any hope of ending inflation. This testing process necessarily involved political judgments, and the Federal Reserve may at times have overestimated the risks attaching to additional monetary restraint…
…Monetary theory is a controversial area. It does not provide central bankers with decision rules that are at once firm and dependable. To be sure, every central banker has learned from the world’s experience that an expanding economy requires expanding supplies of money and credit, that excessive creation of money will over the longer run cause or validate inflation, and that declining interest rates will tend to stimulate economic expansion while rising interest rates will tend to restrict it; but this knowledge stops short of mathematical precision…
…It is clear, therefore, that central bankers can make errors—or encounter surprises—at practically every stage of the process of making monetary policy. In some respects, their capacity to err has become larger in our age of inflation. They are accustomed, as are students of finance generally, to think of high and rising market interest rates as a restraining force on economic expansion. That rule of experience, however, tends to break down once expectations of inflation become widespread in a country. At such a time, lenders expect to be paid back in cheaper currency, and they are therefore apt to demand higher interest rates. Since borrowers have similar expectations, they are willing to comply. An “inflation premium” thus gets built into nominal interest rates. In principle, no matter how high the nominal interest rate may be, as long as it stays below or only slightly above the inflation rate, it very likely will have perverse effects on the economy; that is, it will run up costs of doing business but do little or nothing to restrain overall spending. In practice, since inflationary expectations, and therefore the real interest rates implied by any given nominal rate, vary among individuals, central bankers cannot be sure of the magnitude of the inflation premium that is built into nominal rates. In many countries, however, these rates have at times in recent years been so clearly below the ongoing inflation rate that one can hardly escape the impression that, however high or outrageous the nominal rates may appear to observers accustomed to judging them by a historical yardstick, they have utterly failed to accomplish the restraint that central bankers sought to achieve. In other words, inflation has often taken the sting out of interest rates— especially, as in the United States, where interest payments can be deducted for income tax purposes…
…There is a profound difference between the effects of mistaken judgments by a central bank in our age of inflation and the effects of such judgments a generation or two ago. In earlier times, when a central bank permitted excessive creation of money and credit in times of prosperity, the price level would indeed tend to rise. But the resulting inflation was confined to the expansion phase of the business cycle; it did not persist or gather force beyond that phase. Therefore, people generally took it for granted that the advance of prices would be followed by a decline once a business recession got under way. That is no longer the case.
Nowadays, businessmen, farmers, bankers, trade union leaders, factory workers, and housewives generally proceed on the expectation that inflation will continue in the future, whether economic activity is booming or receding. Once such a psychology has become dominant in a country, the influence of a central bank error that intensified inflation may stretch out over years, even after a business recession has set in. For in our modern environment, any rise in the general price level tends to develop a momentum of its own. It stimulates higher wage demands, which are accommodated by employers who feel they can recover the additional costs through higher prices; it results in labor agreements in key industries that call for substantial wage increases in later years without regard to the state of business then; and through the use of indexing formulas, it leads to automatic increases in other wages as well as in social security payments, various other pensions, and welfare benefits, in rents on many properties, and in the prices of many commodities acquired under long-term contracts…
…If my analysis of central banking in the modern environment is anywhere near the mark, two conclusions immediately follow. First, central banks have indeed been participants in the inflationary process in which the industrial countries have been enmeshed, but their role has been subsidiary. Second, while the making of monetary policy requires continuing scrutiny and can stand considerable improvement, we would look in vain to technical reforms as a way of eliminating the inflationary bias of industrial countries. What is unique about our inflation is its stubborn persistence, not the behavior of central bankers. This persistence reflects the fundamental forces on which I dwelt earlier in this address—namely, the philosophic and political currents of thought that have impinged on economic life since the Great Depression and particularly since the mid-1960s…
…The precise therapy that can serve a nation best is not easy to identify, and what will work well in one country may work poorly in another. In the case of the American inflation, which has become a major threat to the well-being of much of the world as well as of the American people, it would seem wise to me at this juncture of history for the government to adopt a basic program consisting of four parts. The first of these would be a legislative revision of the federal budgetary process that would make it more difficult to run budget deficits and that would serve as the initial step toward a constitutional amendment directed to the same end. The second part would be a commitment to a comprehensive plan for dismantling regulations that have been impeding the competitive process and for modifying others that have been running up costs and prices unnecessarily. The third part would be a binding endorsement of restrictive monetary policies until the rate of inflation has become substantially lower. And the fourth part would consist of legislation scheduling reductions of business taxes in each of the next five years—the reduction to be quite small in the first two years but to become substantial in later years. This sort of tax legislation would release powerful forces to improve the nation’s productivity and thereby exert downward pressure on prices; and it would also help in the more immediate future to ease the difficult adjustments forced on many businesses and their employees by the adoption of the first three parts of the suggested program.
2. Two Things I’m Not Worried About – Ben Carlson
Here are two things a lot of other people are worried about but not me:
Stock market concentration. Here’s a chart from Goldman Sachs that shows by one measure, the U.S. stock market is as concentrated as it has ever been:
To which my reply is: So what?
Yes, the top 10 stocks make up more than one-third of the S&P 500. All this tells me is that the biggest and best companies are doing really well. Is that a bad thing?
Stock markets around the globe are far more concentrated than the U.S. stock market. Emerging markets rose to their highest level since June 2022 yesterday. Out of an index that covers 20+ countries, a single stock (Taiwan Semiconductor) accounted for 70% of the move.
Stock market returns over the long run have always been dominated but a small minority of the biggest, best-performing companies…
… Bloomberg is out with a new report that sounds the alarm on U.S. government debt levels:
With uncertainty about so many of the variables, Bloomberg Economics has run a million simulations to assess the fragility of the debt outlook. In 88% of the simulations, the results show the debt-to-GDP ratio is on an unsustainable path — defined as an increase over the next decade.
In the end, it may take a crisis — perhaps a disorderly rout in the Treasuries market triggered by sovereign US credit-rating downgrades, or a panic over the depletion of the Medicare or Social Security trust funds — to force action. That’s playing with fire.
I’ll believe it when I see it.
People have been sounding the alarm on government debt in this country for decades. There has been no panic. No financial crisis. No debt default…
… Interest expense relative to the size of the economy has shot higher in recent years from the combination of more debt and higher rates:
But we’re still well below the highs from the 1980s and 1990s. And when you look at the absolute numbers here, going from 1.5% of GDP to 3% of GDP isn’t exactly the end of the world…
…Debt-to-GDP is now as high as it was in World War II:
That seems scary until you realize in Japan, debt-to-GDP is closer to 300%. I’m not saying we should test our limits but there is no pre-set line in the sand on these things.
3. The inequity method of accounting – Sujeet Indap
The fundamental bargain of M&A seems pretty simple. At the closing of a deal, the buyer pays the seller, and gets a business in return.
It hasn’t been so straightforward for the family who agreed in 2022 to sell its California supermarket Save Mart to the private equity firm Kingswood Capital Management, which valued the grocery chain at $245mn.
Three months after the papers were signed, Kingswood demanded that Save Mart’s prior owners, the Piccinini family, fork back over $109mn after already surrendering the company. In effect, Kingswood wanted to receive a net $77mn payment to take over Save Mart.
And thanks to some ballsy lawyering and nebulous bookkeeping, it seems the PE firm might actually succeed, its gambit upheld by a controversial arbitration ruling in September 2023…
…When Kingswood signed the deal for Save Mart, it was really acquiring two separate businesses. One was the Save Mart grocery chain, comprised of 200 stores and more than $4bn in annual revenue. Save Mart separately held a majority stake in Superstore Industries (SSI), a successful food wholesaler/distributor that had two other owners…
…The two sides agreed that Save Mart’s equity stake in SSI, the joint venture, would be valued at $90mn, a significant step up from the ~$22.5mn value that Save Mart had assigned the investment on its books.
The increase reflected SSI’s valuable land portfolio, according to one person familiar with the transaction. And it enables Kingswood to lower SSI’s tax basis should it ever want to sell SSI, according to a person involved in the transaction.
Those seem reasonable enough. Still, the accounting of SSI’s value is what laid the foundation for this dispute.
For context, a company’s investments can be recorded on its balance sheet in three ways: cost method, equity method, and full consolidation.
Save Mart selected the equity method for its SSI stake.
To explain a bit further: Let’s imagine a company with $100 of asset value and $60 in liabilities, which leaves it with an equity value of $40. Say this company has a 50-per-cent owner, meaning it owns $20 in equity. The owner’s balance sheet would list that $20 as a single line item, called “equity in unconsolidated affiliates”. That account would grow with the subsidiary’s proportional net income, and decrease with any net losses or dividends.
Save Mart’s stake in SSI was listed as a single line on its balance sheet — worth $22.5mn…
…In March 2022, Kingswood and Save Mart closed their deal with the PE firm sending payments based on the family’s proposed accounting. That then set off a final round of post-closing negotiations, where Kingswood got 90 days to argue with the Piccinini’s maths…
…But Kingswood dropped in one massive adjustment with the boilerplate.
It added back $109mn of gross SSI debt, and asserted that the figure counted as official “Indebtedness”. And it argued it should be paid back for all that additional debt.
The PE firm pointed to the language in the deal contract, and said the definition of “Indebtedness” included any Save Mart “group” debt…
…Arbitrator Joseph Slights III, a lawyer in private practice who was formerly a Delaware Vice Chancellor, did not ultimately buy any of what the Piccinnis were selling.
He wrote in the arbitration decision: “Delaware law is more contractarian than most, and Delaware courts will enforce the letter of the parties’ contract without regard for whether they have struck a good deal or bad deal . . . the result is not absurd or commercially unreasonable.”…
…The Piccinnis, understandably, believe writing a cheque for $109mn is indeed “absurd” and “commercially unreasonable”. They have accused Kingswood of “bad faith” and “gamesmanship” in their court papers.
They will now appeal to the Delaware Supreme Court, pointing to a 2017 decision that said in a post-closing adjustment dispute, the legal system should aim to uphold the broader spirit of the contract instead of narrow contract definitions…
…Kingswood had believed, all along prior to signing and closing, that the gross SSI debt belonged on Save Mart’s main balance sheet. But they decided to keep quiet about that until after the deal closed.
One implication is that they were happy to close on the Piccininis’ terms, and winning on the SSI debt issue would be a bonus, given that there was no guarantee of winning the arbitration.
The firm’s equity check on the $240mn transaction was just $60mn (see the sources and uses table above). If Kingswood is eventually paid the $109mn, it will receive nearly two times their equity contribution by weaponising accounting and legal technicalities.
4. Don’t Be Afraid – Michael Batnick
All-time highs are interesting in the emotions they elicit. Some people might be euphoric as their accounts reach dollar amounts never seen before. Others might fear this is as good as it’s going to get and worry about a trap-door scenario.
Your emotional state might also depend on your asset allocation. If you’re sitting on a large cash pile, it’s understandable that you might be hesitant to go “all in” at a record price. It might not “feel” right.
The good news is the data doesn’t support those feelings. On average since 1970, the S&P 500 has done better 1, 3, and 5 years after making an all-time high than picking a random day.
5. An Interview with Google Cloud CEO Thomas Kurian About Google’s Enterprise AI Strategy – Ben Thompson and Thomas Kurian
You did mention that, “People are moving out of proof-of-concept into actually doing products”. Is that actually happening? What are the actual use cases that companies are actually rolling out broadly as opposed to doing experiments on what might be possible?
TK: Broad-brush, Ben, we can break it into four major categories. One category is streamlining internal processes within the organization, streamlining internal processes. In finance, you want to automate accounts receivable, collections, and cashflow prediction. In human resources, you want to automate your human help desk as well as improve the efficiency with which you can do benefits matching, for example. In procurement and supply chain, you want for example, look at all my suppliers, their contracts with me and tell me which ones have indemnification and warranty protection, so I can drive more volume to those that give me indemnification and warranties and less to those that don’t, for example. These are all practical cases we have customers live in deployment with.
Second is transforming the customer experience. Transforming the customer experiences, how you market, how you merchandise, how you do commerce, how you do sales and service. An example is what Mercedes-Benz CEO Ola Källenius talked about how they’re building a completely new experience for the way that they market and sell and service their vehicles.
Third is that some people are integrating it into their products, and when I say re-imagining their products, re-imagining their core products using AI. We had two examples of companies who are in the devices space. One is Samsung and the other one is Oppo, and they’re re-imagining the actual device itself using AI with all the multimodality that we provide.
There are quite a few companies now re-thinking that if a model can change the way that I see it, that I can process multimodal information. For example, in media we have people saying, “If your model can read as much information as it can, can it take a long movie and shrink it into highlights? Can I take a sports recording of the NCAA basketball final and say, ‘find me all the highlights by this particular player’?” and not have to have a human being sit there and splice the video, but have it do it and I can create the highlights reel really quickly. So there are lots of people re-imagining the product offerings that they have.
And finally, there are some people saying, “With the cost efficiency of this, I can change how I enter a brand new market because, for example, I can do personalized offers in a market where I may not have a physical presence, but I can do much higher conversion rate for customers with online marketing and advertising because now I can do highly tailored campaigns because the cost of creating the content is much lower.” So broad-brush, streamline the core processes and back office, transform the customer experience and it doesn’t mean call centers or chatbots, it can be actually transferring the product itself, transforming the nature of the product you build and enter new markets.
Is it fair to say then when you talk about, “Moving from proof-of-concept to actual production”, or maybe that’s not the words you used, but people are saying, “Okay, we’re going to build this” because this stuff’s not showing up yet, in the real world. Is it the case that, “We see that this could be valuable, now we’re in”, and that’s why you’re emphasizing the platform choice now because they’ve committed to AI broadly, and now it’s like, “Where are we going to build it”?
TK: We have people experimenting, but we also have people actually live deployment and directing traffic. Orange, the telecom company, was talking about how many customers they’re handling online, Discover Financial was talking about how their agents are actually using AI search and AI tools to discover information from policy and procedure documents live. So there are people actually literally running true traffic through these systems and actually using them to handle real customer workload.
Are you seeing the case in a lot of in customers, or maybe you’re hearing from potential customers, that AI is rolling out, if that’s the right word, in an employee arbitrage situation? Where there’s individual employees that are taking on themselves to use these tools and they are personally benefiting from the increased productivity — maybe they’re doing less work or maybe they’re getting more done — and the companies want to capture that more systematically. Is that a theme that you’re seeing?
TK: We’re seeing three flavors. Flavor one is a company has, we’re going to try eight or nine, what they call customer journeys or use cases, we’re going to pick the three that we see as the maximum return, meaning value and value does not mean cost savings always. It could be, for example, we have one who is handling 1 million calls a day through our customer service system. Now a million calls a day, if you think about it, Ben, an average person can do about 250 calls a day, that’s a certain volume in an eight-hour day. If you handled a million, that is a lot of people, so the reality is that several of them were not being answered and people never called because the wait time was so long. So in that case, it was not about cost savings, it’s the fact that they’re getting able to reach many more customers than they could do before. So that’s one. One part is people saying, “I have a bunch of scenarios, I’m going to pick the three”, and in many cases, they’re actually augmenting something they’re doing or doing something they couldn’t do before, that’s scenario one.
Scenario two was I have, for example, there’s a large insurance company that’s working with us. Today, when they do claims and risk calculation, it takes a long time to handle the claims and the risk, particularly the risk calculation, because there’s thousands of pages of documents, there’s a lot of spreadsheets going back and forth. They put it into Gemini and it was able to run the calculations much, much more quickly. So second is I’m picking a very high value use case for my organization, which is the core function, and I’m going to implement it because I can get a real competitive advantage. In their case, it’s the fact that they can both get more accurate scoring on the risk and they can also do a much more accurate job, faster job in responding.
And the third scenario is what you said. “Hey, we’ve got a bunch of people, we’re going to give it to a certain number of developers”. For example, our coding tool, “They are going to test it, they say it helps me generate much better unit tests, it helps me write better quality code”. Wayfair’s CTO was talking about what their experience is, and then they say, “Let’s go broadly”, so all three patterns are being seen…
…Do you see AI, though, in all this talk about, “You need to choose a platform? Sure, our platform’s going to be open, you can use it anywhere” — but do you see this as a wedge to be like, “Okay, this is a reboot broadly for the industry as far as cloud goes, and sure, your data may be in AWS, or in Azure, or whatever it might be, but if you have a platform going forward, you should start with us”? Then maybe we’ll look up in ten, fifteen years, and all the center of gravity shifted to wherever the platforms are?
TK: For sure. I mean, it’s a change in the way that people make purchase decisions, right? Ten years ago, you were worried about commodity computing, and you were like, “Who’s going to give me the lowest cost for compute, and the lowest cost for storage, and the lowest cost for networking?”. Now the basis of competition has changed and we have a very strong position, given our capability both at the top, meaning offering a platform, offering models, et cetera, and building products that have long integrated models.
Just as an example, Ben, integrating a model into a product is not as easy as people think; Gmail has been doing that since 2015. On any daily basis, there are over 500 million operations a day that we run and to do it well, when a partner talked about the fact that 75% of people who generate an image for slides actually end up presenting it, it’s because we have paid a lot of attention over the years on how to integrate it.
So we play at the top of the stack, and we have the infrastructure and scale to do it really well from a cost, performance, and global scale that changes the nature of the competition. So we definitely see this, as you said, as a reset moment for how customers thinking of choosing their cloud decision.
If you’re talking about a lot of choices about models, and customers were over-indexed on choosing the correct model, that implies that models are maybe a commodity, and that we’ve seen with GPT-4 prices are down something like 90% since release. Is that a trend you anticipate continuing, and is it something that you want to push and actually accelerate?
TK: Models — whether they’re a commodity or not, time will tell, these are very early innings. All we’re pointing out is every month, there’s a new model from a new player, and the existing models get better on many different dimensions. It’s like trying to pick a phone based on a camera, and the camera’s changing every two weeks, right? Is that the basis on which you want to make your selection?
Well, but if you make that basis, then you might be locked into the operating system.
TK: That’s right, and so that’s why we say you should choose an open platform, and you should be able to use a collection of different models, because it’s changing, and don’t lock into a particular operating system at a time when the applications on top of it are changing, to use your analogy.
Why is your platform open as compared to others? Microsoft has announced you can use other models, not just OpenAI models. Amazon is sort of, to the extent you can ascertain a strategy, it’s like, “Look, we’re not committing to anything, you could do whatever you want.” Why do you feel comfortable saying, “No, we’re the open one,” and they’re not?
TK: Well, first of all, the completeness of our platform; Vertex has a lot more services than you can get with the other platforms. Secondly, in order to improve a platform, you have to have your own model, because there’s a bunch of things you do when you engineer services with that model.
I’ll give you a really basic example. You use a model, you decide to ground the answers. Grounding improves quality, but can also introduce latency. How do you make sure that when you’re grounding, you’re not serially post-processing a model’s answer to add latency? Unless you have your own model, you wouldn’t even get to that. So because we have our own model, we’re able to engineer these things, but we make them available as services with other models, so you can use enterprise grounding as a very specific example. There are lots of customers using it with Mistral and with Llama and with Anthropic.
Second thing, we are not just offering models, but we’re actually helping the third party go to customers with us. I met a lot of customers today jointly with [CEO] Dario [Amodei] from Anthropic, and it’s a commitment to make sure we’re not just giving you our infrastructure, we’re not just training, integrating a model into Vertex, we’re not just making it a first-class model, but we’re actually bringing it to clients together.
I think that’s what we mean by open. One of the other players has no models of their own, so naturally they’re offering a bunch of models, and the other player has outsourced their model development to a third party…
…How important is that million context window in the story you are telling? My perception is, there’s a lot of stuff you could do if you build a lot of infrastructure around it, whether it be RAG or other implementations, but it feels like with Gemini 1.5 there are jack-of-all-trades possibilities that seem to open up to a much greater extent, and there’s a bit where, you had that compliance bit, the statements of work and they had to compare it to the 100-page compliance document. I got some comments like, “Maybe companies shouldn’t have 100-page compliance notebooks or whatever it might be”, but the reality is, that’s the case, the world has that. My perception of the keynote is, that was the killer feature, that seemed to undergird everything. Was that the correct perception?
TK: Yeah, there are two reasons. Just to be perfectly clear, Ben, the long context window allows you to do three things that are important. First of all, when you look at high definition video, for example, and other modalities, and just imagine you’re dumping a high definition video in and you want to create out of the NCAA final, which just happened, the highlight reel but you don’t want to specify every attribute about what you want spliced into the highlight reel. The model has to digest it and because it has to process it, it’s a fairly dense representation of the video because there are objects, there are people moving, there are actions, like I’m throwing a pass. They could be, I have my name on the back of my t-shirt, there could be a score like, “When did they change from 24 to 26 points? Did they score three pointers?”, so there are many, many, many dimensions. So reasoning becomes a lot better when you can take a lot more context, that’s one, and it’s particularly true of modality.
The second is, today people don’t use models to maintain state or memory, meaning they ask it a question, the next time they think, “Hey, it may not remember”, so when you’re able to maintain a longer context, you can maintain more state, and therefore you can do richer and richer things rather than just talk back-and-forth with a very simplistic interface. You see what I mean?
The third thing is, there are certainly complex scenarios, it’s the unfortunate reality, there’s lots of policies and procedure books that are even longer than what we showed, and so there are scenarios like that that we have to be able to deal with. But in the longer term, the real breakthrough is the following. Context length, if you can decouple the capabilities of the model and the latency to serve a model from the context length, then you can fundamentally change how quickly you can scale a model.
Is this ultimately, from your perspective, a question of infrastructure, and that just leans into Google’s biggest advantage?
TK: It’s a question of global infrastructure, but also optimizations at every layer in the infrastructure, which we can co-engineer with DeepMind…
…Sundar Pichai mentioned in his video greeting, he emphasized the number of AI startups, and particularly AI unicorns using Google Cloud. To go back to the reboot idea, do you view the AI Era as a restart in terms of capturing the next generation of companies? I mean, obviously, AWS had a huge advantage here as far as general cloud computing, the entire mobile app ecosystem was by and large built on AWS. In the enterprise era, you have to deal with what’s there, what they’ve already dealt with, you have to have the integrations. Do you see yourself as having this as a big focus, “We’re going to own this era of startups”?
TK: Yes. And by the way, every one of those startups is being pursued by the other two, and the fact that 90% of the unicorns and 60% of all AI-funded startups, up in each case by ten points in eight months, and they are the most discerning ones. I mean, just to be frank, the unicorns, for them, it is the really biggest cost of goods sold in their P&L.
So what’s the driver there?
TK: The efficiency of our infrastructure.
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have a vested interest in Alphabet (parent of Google), Amazon (parent of AWS), Microsoft, and TSMC. Holdings are subject to change at any time.
