What We’re Reading (Week Ending 02 June 2024)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general. 

Here are the articles for the week ending 02 June 2024:

1. Pierre Andurand on a Shortage of Cocoa, Surging Copper and the Outlook for Oil – Tracy Alloway, Joe Weisenthal, and Pierre Andurand

Tracy (03:29):

So maybe to begin with, talk to us about how you got interested in cocoa because my understanding is you put a big trade on a long position earlier this year, it paid off massively. But this isn’t a sort of normal type of trade for you. This is something that was a little bit different.

Pierre (03:48):

Yes. Well, generally my background is more in energy trading, but I’ve traded quite a bit of metals as well, a little bit of agricultural products.

But I have one analyst who was very good and told me in January, ‘Pierre, you should look at cocoa.’ So I’m like ‘Okay, I don’t know anything about it, tell me.’

And he gave me a really good presentation that was really interesting. So then we really digged in really deep together to really understand the fundamental market. And basically we have a massive supply shortage this year.

I mean, we see production down 17% relative to last year. Most analysts out there have it down 11%, but that’s because they tend to be very conservative. They have lots of clients and they don’t want to worry the world. So they come with relatively conservative estimates.

But really tracking the export from the main exporters, mainly Ivory Coast and Ghana, that represent together about 60% of [the] world’s production. We see basically Ivory Coast exports down 30% year to date, I mean season to date and Ghana down 41%.

So just those two countries together since the start of the season, which is the 1st of October, are down 800,000 tons. And now we have what we call the mid-crop that is starting, but that represents only 20% of the balance of the season for West Africa.

And that’s not going to be enough to really change the deficit that we have this year. So we have a deficit of 800,000 tons from those two countries. And then looking at all the other countries we have, I think there some slightly positive, some are slightly negative, but basically we get to a deficit of 800,000 tons this year. And so that’s the first time we have such, you know, a decline in supply and that’s very hard to make it fit.

So at first you eat into current inventories until you run out of inventories and then the price can go anywhere.

So when we look at, okay, what makes the price of cocoa, right? It’s always about supply versus demand. But what has been capping the price between $2,500 a ton and $3,000 a ton, it was not demand because demand is extremely inelastic. I mean you can study that historically when you have a recession or not, when prices go up a lot or not. I mean demand generally goes up.

And that’s because the amount of in dollar terms that people consume in cocoa is very small. I mean, I did a back of the envelope calculation the other day. I mean at basically $10,000 a ton, even though it’s four times the more recent historical prices, out of a market of 5 million tons of demand per year, you have like 8 billion people on the planet, so on average it means that people consume 1.7 grams of cocoa per day, which at $10,000 a ton represents 1.70 cents per day. Okay, that’s the average person. Many people eat nothing and a few eat 10 times that amount…

…Pierre (06:56):

But let’s say if you eat even one full tablet, so 125 grams a day every single day for the whole year, which is quite a lot, of a high content real cocoa because your milk and milk chocolate, you have less than 10% cocoa in it.

So the price can go up 10 times, your tablet is only going to double in price. It’s not going to react very much to the cocoa price. But if you take a high content, high chocolate content bar, like a tablet, 125 grams, that means that you probably have [a] maximum of 50 grams of cocoa beans equivalent in it. I mean it’s probably a lot less.

Then you get to an expense of $14 per month at current prices, which is an increase of $10 per month relative to when we had a more normal price. So it means that demand, like for more reasonable chocolate lovers, that increase in [the] price in cocoa just corresponds to $2 to $5 per month.

So people are not going to eat less chocolate because of that. So it means that prices really are capped by the amount of supply you get. So if you can’t get enough supply, the price can go up a lot until we get more supply.

And when do we get more supply? Well, that in part [is] due to the weather, if you have much better weather then you might get more supply of cocoa beans the next year. But we have some issues that are also structural.

So when we look at the reasons for this large decline in production this year, I mean a lot of the reasons are actually structural. I mean we can look at four reasons why cocoa bean production has gone down a lot this year.

First I should give a little bit of background of why cocoa is so concentrated in West Africa. I mean it’s mainly because it requires very specific temperature, rainfall and humidity conditions. And that’s why most of the production is concentrated around a certain latitude — so 70% in West Africa and then you have 21% in mainly Latin America and 5% in Asia and Oceania.

So the main reasons why we lost a lot of production this year is number one weather. So some of it [is] due to El Nino, we had basically a period of time when it was too hot and a period of time when we had way too much rain.

Second is climate change. So climate change is every year shifting the weather patterns generally unfavorably for cocoa productions. Then you have two diseases, you have one called the Black Spot disease that comes from the fungus and it occurs mainly during the rainy season. It’s spread by rain splash, so basically it can’t grow when it’s dry.

And then you have a virus called the Swollen Shoot disease. It’s not a new disease. It was discovered in 1936. It’s transmitted by mealybugs, but it decreases cocoa yields a lot. So basically a tree that has that Swollen Shoot disease loses 25% yield within the first year and 50% within two years, and the tree dies within three to four years. And we’ve had actually a spread of that disease over the last year.

And then also we had less usage of fertilizers, mainly in the Ivory Coast, due to high fertilizer prices and also shortages due to the Russian invasion of Ukraine. So everything is linked. So some of it might be solved if we get better weather. I mean for next year we should have La Nina and not El Nino, so that should help at the margin.

But we still have issues with climate change. We still have issues with Black Spot disease and Swollen Shoot disease and there’s no indication that we get more usage of fertilizers in [the] Ivory Coast because actually the farmers are still getting relatively low prices and they’re still struggling to make ends meet. So a lot of those supply issues are actually structural…

…Joe (12:09):

So what did your analyst see? Or how was your analyst able to see something in the supply and demand situation that he felt, and you felt, was not being identified by the analysts who cover this closely?

Pierre (12:23):

I think it’s mainly an understanding of how much prices have to move to balance the market. You know, sometimes people can trade that market for like 20 years. They’ve been used to a range of prices and they believe, okay, the top of the range is the high price for example.

But they don’t really ask themselves what makes that price, right?. And sometimes taking a step back can help. I mean what makes the price is mainly the fact that in the past you would have the supply response if prices were going up. But if now you don’t get the supply response, or the supply response takes four or five years, then you need to have a demand response.

And a lot of people look at prices in nominal terms. So you hear people saying ‘Oh, we are at all time high prices in cocoa, but that’s because they look at prices in nominal terms. [The] previous high in 1977 was $5,500 something dollars a ton of 1977 dollars, which is equivalent to $28,000 a ton of today’s dollars.

So we are still very far from previous highs. And so you have to look at a bit more history and understand in the past how prices reacted to a shortage, how long it took to recover the product shortage to actually solve itself. And what’s different today.

So there’s a ratio that we look at that most people look at, it’s actually the inventory to grindings ratio. So it’s a measure of inventory to demand, what we call grinding is basically industrial companies that take the cocoa beans and they want to make chocolate with it. So it’s a process and some of them make the end product chocolate directly. Some of them sell back the product to other chocolate makers.

And so basically a typical grinder would take cocoa beans and make cocoa butter and powder with it. And the prices of both those elements also went up even more than cocoa beans, which means that actually we probably had some destocking everywhere in the chain.

So it looks like demand, when we look at the chocolate makers, the end demand for chocolate didn’t go down at all, it looks to be flat on the year. Grindings look to be down three, three and half percent this year, despite the fact that the end demand is the same in volume, which means that they’ve been destocking cocoa beans actually.

And so we had destocking everywhere — at the end chocolate level, at the cocoa beans, at the cocoa butter and cocoa powder level. So we had this destocking everywhere on the chain and now we have the largest deficit ever on top of two previous years of deficit. And it looks like next year we will have a deficit.

So we’re in a situation where we might actually run out of inventories completely. I mean this year we think we will end up with an inventory to grinding ratio — so inventory at the end of the season — of 21%. For the last 10 years we’ve been between 35% and 40% roughly. At the previous peak in 1977 we were at 19% and that’s what drove us to $28,000 a ton, of todays’s dollars.

If we have another deficit next year, then we might go down to 13%. So I don’t think it’s actually possible. That’s when you really have real shortage of cocoa beans, you can’t get it and that’s when the price can really explode. And so understanding that you have to slow down demand and we know that demand can’t really be slowed.

So that’s when you can have an explosion [in price]. And remember that these commodity futures, you need to have, they’re actually physically settled. So if somebody wants to take delivery, they have to converge with the price of the physical. If you have no physical, somebody wants to take delivery, the price can go anywhere.

So it’s a dangerous commodity too short, right? If you have no physical against it. And actually sometimes we read news that the funds have been pushing cocoa prices. It’s actually completely untrue because the funds have been selling since February. They actually went from a length of 175,000 lots, so that’s 1.75 million tons of cocoa lengths, I think it was around like September last year in average, or a bit earlier, to 28,000 lots to 280,000 tons at the moment.

So they sold more than 80% of their length actually. And the people who’ve been buying the futures from the funds, it’s producers because they’re producing a lot less than they expected.

So what has been happening in the cocoa market is that you had a reduction of what we call the open interest, where both the longs would use their length and the shorts would use their shorts. And then we get into a market where you have less liquidity because you have less exposure, you have less longs and less shorts, and then the volatility increases.

So in the past when people were comfortable being, let’s say, having a 100 lots position now because it moves more than 10 times more than in the past, we’re going to have like a 10 lots position, right? So the market became more — due to the fact that we had a massive move and we have a massive deficit, so everybody’s reducing their positions and because of the increased volatility, we have less activity. And that’s what makes the point more volatile as well.

2. The World’s Most Secret Book About Making a Fortune in Mining – Swen Lorenz

For years, I have been trying to find a copy of an ultra-rare book published in 2008.

It told the inside story of a few mining entrepreneurs who built a company from zero and sold it for a staggering USD 2,500,000,000 (2.5 BILLION) in cash just 674 days later. That’s a quick fortune earned, if ever there was one!

The company was listed on the stock market, and public investors were taken along for some of the ride. In 2006/07, this was the single best British company to own stock of.

Somehow, though, the company’s insiders seem to have regretted publishing their detailed account. The book strangely disappeared from the market shortly after it was published. Curiously, there is ample evidence that an active effort was made to erase the book from history…

…The book in question is “UraMin – A team enriched. How to build a junior uranium mining company“.

Junior mines are companies that are still looking for resources, rather than producing the resource. As most of my readers will know, they are among the most speculative ventures one can invest in. About 99% of them make most investors lose their entire investment. The remaining 1% regularly end up making investors 10, 20, or even 100 times their money.

UraMin was primarily the brainchild of Stephen Dattels, a Canadian mining entrepreneur with a decade-long track record. The book describes the genesis of UraMin from his own perspective and that of his two partners, Ian Stalker and Neil Herbert. It was, for all intents and purposes, a real insiders’ account of the incredible success story.

UraMin produced oodles of capital gains. It was a lucrative investment not just for its pre-IPO investors, but also for those who bought into it through shares acquired on the open market post-IPO…

…It’s no surprise that the book starts with describing just how “Down and Out” the market for uranium-related investments was at the time.

At the turn of 2004/05, you would have been hard-pressed to find any investors interested in uranium. The price for the metal had been in a 26-year (!) bear market. From it 1977 peak, it had been downhill ever since. There were barely any publicly listed companies operating in the uranium industry.

You would have struggled to find anyone who even understood what the metal was used for, and how it was used.

Or as Ian Stalkers, the CEO of UraMin, is quoted in the book:

“A meeting with potential investors could literally take hours. … First, it required a full explanation of what uranium is used for (it isn’t used for ‘bombs’), a run-through of the fuel cycle (enrichment and so on), the safety record of nuclear reactors, long-term disposal issues and the balance of supply and demand. We were lucky if we managed to talk for 10 minutes about the company.”

It was not an opportunity that the mass of investors would have jumped at when it was first presented.

  • However, all the clues were there. At the end of 2004/05, three crucial developments had already taken place, all pointing towards an imminent reversal of fortunes:
  • The price of uranium had started to creep up. It went from USD 10/lb in early 2003 to USD 20/lb by the end of the following year (which was still far below the late-1970s high of USD 115/lb).
  • Existing stockpiles of the metal, which had soared during the 1990s because of a decommissioning of Soviet nuclear missiles, had dwindled to virtually zero. The oversupply that had depressed the price for so long was gone.
  • A soaring oil price, which at the time was up more than 10 times compared to its early-2000s low, provided increasing demand for cheap nuclear energy. It was only a matter of time before investment would flow towards the much cheaper source of energy.

Subsequently, the uranium price went through the roof…

…Put more bluntly, there are occasions when a management team has to concede that everyone is better off if it puts the company up for sale – which is difficult because it usually leads to the entire management team and board losing their jobs!

Also, who wants to leave a party when things are the most fun? Making the decision to call it quits and focus on maximising a buyout price for a company is an extraordinarily hard decision to take. However, it is quite regularly the one decision that a board really should have the guts and the sense of realism to take.

I wasn’t surprised to read that Dattels and his colleagues had that rare quality of knowing when to quit:

“The trend towards a smaller group of larger uranium companies had significant repercussions for UraMin, something that its management realised early on. “The sector was not a large one – it had already seen several significant mergers and more were rumoured,” notes Neil Herbert. “Despite the rapid progress we had made, we were in danger of becoming a relatively small operator.

On 19 February 2007, Reuters reported that UraMin was planning a strategic review of its assets in light of the recent consolidation of the sector.

In effect, analysts believed, the company had just put itself up for sale.”

Companies can put themselves up for sale by hiring an investment bank and making a public announcement, or they can de facto put themselves up for sale by feeding information into their industry’s rumour mill.

Steve Dattels decided that “we should take the initiative and evaluate the merger possibilities rather than wait for the telephone call.”

UraMin hired advisors and went through an official process of allowing prospective acquirers access to its internal information.

Following the process of inviting bids, the company came to an agreement with French nuclear power company, AREVA. In June 2007, UraMin’s management team agreed to a takeover offer that valued the company at USD 2.5bn. The entire purchase price was payable in cash.

Investors who had bought in at the bottom of GBp 50 per share made 8 times their money within just 12 months.

One of the earliest institutional backers of the venture reportedly made 22 times their money in just 24 months.

3. Why Utilities Are Lighting Up the Stock Market – Jason Zweig

As Bespoke Investment Group, a research firm, pointed out this week, three of this year’s five best-performing stocks in the S&P 500 are utilities: Vistra, Constellation Energy and NRG Energy. Vistra, up 143%, has even outperformed the king of AI itself, Nvidia; Constellation, up 85%, is barely behind it…

…The business of providing electricity hasn’t grown in the past couple of decades as conservation and more-efficient technology have reduced consumption. The U.S. generated slightly less electricity in 2021 than it had in 2007, according to the federal Energy Information Administration—even though the economy grew more than 3% annually over that period.

Now, however, the need for energy is finally expanding. On their April 23 earnings-announcement call, executives at NextEra estimated that electricity demand from data centers alone would grow 15% a year through the end of the decade.

AI isn’t the only reason utilities have heated up so fast. The rapid increase in demand for electricity nationwide comes from three main sources, says Maria Pope, CEO of Portland General Electric, Oregon’s biggest utility.

One is the revival of domestic manufacturing after decades of moving offshore. Another is the boom in semiconductor production, boosted by government support. But the expansion of data centers, “driven by the insatiable appetite of AI,” is the fastest-growing source of industrial demand, says Pope.

Jay Rhame, chief executive of Reaves Asset Management, which manages about $3 billion in utility stocks, thinks the only historical parallel is the boom in electricity generation that followed the widespread adoption of air conditioning in the 1960s and 1970s.

4. Adobe CEO Shantanu Narayen is confident we’ll all adapt to AI – Nilay Patel and Shantanu Narayen

If you are Microsoft or Google or someone else, one of the reasons this paradigm shift excites you is because it lets you get past some gatekeepers in mobile, it lets you create some new business models, it lets you invent some new products maybe that shift some usage in another way. I look at that for them and I say: Okay, I understand it. I don’t quite see that paradigm shift for Adobe. Do you see that we’re going to have to invent a new business model for Adobe the way that some of the other companies see it?

I think any technology shift has the same profound impact in terms of being a tailwind. If you think about what Microsoft does with productivity, and if you think about what Adobe does with creativity, one can argue that creativity is actually going to be more relevant to every skill moving forward. So I do think it has the same amount of profound implication for Adobe. And we’ve innovated in a dramatic way. We like to break up what we are doing with AI in terms of what we do at the interface layer, which is what people use to accomplish something; what we’re doing with foundation models; and what models are we creating for ourselves that are the underlying brain of the things that we are attempting to do, and what’s the data? I think Adobe has innovated across all three. And in our different clouds — we can touch on this later — Creative Cloud, Document Cloud, and Experience Cloud, we’re actually monetizing in different ways, too. So I am really proud of both the innovation on the product side and the experimentation on the business model side.

The reason I asked that question that way, and right at the top, is generative AI. So much of the excitement around it is letting people who maybe don’t have an affinity for creative tools or an artistic ability make art. It further democratizes the ability to generate culture, however you wish to define culture. For one set of companies, that’s not their business, and you can see that expands their market in some way. The tools can do more things. Their users have more capabilities. The features get added.

For Adobe, that first step has always been serving the creative professional, and that set of customers actually feels under threat. They don’t feel more empowered. I’m just wondering how you see that, in the broadest possible sense. I am the world’s foremost, “What is a photo?” philosophical handwringer, and then I use AI Denoise in Lightroom without a second’s hesitation, and I think it’s magic. There’s something there that is very big, and I’m wondering if you see that as just a moment we’re all going to go through or something that fundamentally changes your business.

Whether you’re a student, whether you’re a business professional, or whether you’re a creative, we like to say at Adobe that you have a story to tell. The reality is that there are way more stories that people want to tell than skills that exist to be able to tell that story with the soul that they want and the emotion that they want. I think generative AI is going to attract a whole new set of people who previously perhaps didn’t invest the time and energy into using the tools to be able to tell that story. So, I think it’s going to be tremendously additive in terms of the number of people who now say, “Wow, it has further democratized the ability for us to tell that story,” and so, on the creative side, whether you’re ideating, whether you’re trying to take some picture and fix it but you don’t quite know how to do it.

When people have looked at things like Generative Fill, their jaws drop. What’s amazing to us is when, despite decades of innovation in Photoshop, something like Generative Fill captures the imagination of the community — and the adoption of that feature has been dramatically higher than any other feature that we’ve introduced in Photoshop. When layers first came out, people looked at it, and their jaws dropped. It just speaks to how much more we can do for our customers to be able to get them to tell their story. I think it’s going to be dramatically expansive…

I want you to talk about the distribution side. This is the part that I think is under the most pressure. Content creation is getting easier and more democratic. However you feel about AI, it is easier to make a picture or a video than it’s ever been before. On the distribution side, the web is being choked by a flood of AI content. The social platforms, which are closed distribution, are also being flooded with AI content. How do you think about Adobe living in that world? How do you think about the distribution problem? Because it seems like the problem we all have to solve.

You’re absolutely right in that, as the internet has evolved, there’s what you might consider open platforms and closed platforms. But we produce content for all of that. You pointed out that, whether it’s YouTube, TikTok, or just the open internet, we can help you create content for all of that. I don’t know that I’d use the word “choked.” I used the word “explosion” of content certainly, and “flooded” also is a word that you used. It’s a consequence. It’s a consequence of the access. And I do think that for all the companies that are in that business, even for companies that are doing commerce, I think there are a couple of key hypotheses that when they do, they become lasting platforms. The first is transparency of optics of what they are doing with that data and how they’re using that data. What’s the monetization model, and how are they sharing whatever content is being distributed through their sites with the people who are making those platforms incredibly successful?

I don’t know that I worry about that a lot, honestly. I think most of the creators I’ve spoken to like a proliferation of channels because they fundamentally believe that their content will be differentiated on those channels, and getting exposure to the broadest set of eyeballs is what they aspire to. So I haven’t had a lot of conversations with creators where they are telling us, as Adobe, that they don’t like the fact that there are more platforms on which they have the ability to create content. They do recognize that it’s harder, then, for them to differentiate themselves and stand out. Ironically, that’s an opportunity for Adobe because the question is, for that piece of content, how do you differentiate yourself in the era of AI if there’s going to be more and more lookalikes, and how do you have that piece of content have soul? And that’s the challenge for a creative.

How do you think about the other tension embedded in that, which is that you can go to a number of image generators, and if someone is distinctive enough, you can say, “Make me an image in the style of X,” and that can be trained upon and immediately lifted, and that distinction goes to zero pretty fast. Is that a tension that you’re thinking about?

Given the role that Adobe plays in the content creation business, I think we take both the innovation angle and the responsibility angle very seriously. And I know you’ve had conversations with Dana [Rao, Adobe counsel] and others about what we are doing with content credentials and what we are doing with the Fair Act. If you look at Photoshop, we’re also taking a very thoughtful approach about saying when you upload a picture for which you want to do a structure match or style match, you bear the responsibility of saying you have access to that IP and license to that IP in order to do that.

So I can interpret your questions in one of two ways. One is: how do we look at all of the different image generators that have happened? In that case, we are both creating our own image generator, but at the NAB Show, we showed how we can support other third parties. It was really critical for us to sequence this by first creating our own image model. Both because we had one that was designed to be commercially safe. It respected the rights of the creative community because we have to champion it. But if others have decided that they are going to use a different model but want to use our interfaces, then with the appropriate permissions and policies, we will support that as well.

And so I interpret your questions in those two ways, which is we’re taking responsibility in terms of when we provide something ourselves, how are we making sure that we recognize IP because it is important, and it’s people’s IP. I think at some point, the courts will opine on this, but we’ve taken a very designed-to-be commercially safe approach where we recognize the creator’s IP. Others have not. And the question might be, well, why are you supporting them in some of our products? And a lot of our customers are saying, “Well, we will take the responsibility, but please integrate this in our interfaces,” and that’s something that we are pushing as third-party models.

It bears mentioning that literally today, as we’re speaking, an additional set of newspapers has sued OpenAI for copyright infringement. And that seems like the thing that is burbling along underneath this entire revolution is, yeah, the courts are going to have to help us figure this out. That seems like the very real answer. I did have a long conversation with Dana [Rao] about that. I don’t want to sit in the weeds of that. I’m just wondering for you as the CEO of Adobe, where is your level of risk? How risky do you think this is right now for your company?

I think the approach that we’ve taken has shown just tremendous leadership by saying … Look at our own content. We have a stock business where we have rights to train the models based on our stock business. We have Behance, and Behance is the creative professional social site for people sharing their images. While that’s owned by Adobe, we did not train our Firefly image models based on that because that was not the agreement that we had with people who do it.

I think we’ve taken a very responsible way, so I feel really good about what we are doing. I feel really good about how we are indemnifying customers. I feel really good about how we are doing custom models where we allow a person in the media business or the CPG business to say, “We will upload our content to you Adobe, and we will create a custom model for us that only we can use, what we have rights for.” So, we have done a great job. I think other companies, to your point, are not completely transparent yet about what data they use and [if] they scrape the internet, and that will play out in the industry. But I like the approach that we’ve taken, and I like the way in which we’ve engaged with our community on this.

It’s an election year. There are a lot of concerns about misinformation and disinformation with AI. The AI systems hallucinate a lot. It’s just real. It’s the reality of the products that exist today. As the CEO of Adobe, is there a red line of capability that you won’t let your AI tools cross right now?

To your point, I think it’s something like 50 percent of the world’s population over a 12-month period is going to the polls, including the US and other major democracies in the world. And so, we’ve been actively working with all these governments. For any piece of content that’s being created, how does somebody put their digital signature on what the provenance of that content was? Where did it get created? Where did it get consumed? We’ve done an amazing job of partnering with so many companies in the camera space, in the distribution of content space, in the PC space to all say we need to do it. We’ve also now, I think, made the switch associated with, how do you visually identify that there is this watermark or this digital signature about where the content came from?

I think the unsolved problem to some degree is how do you, as a society, get consumers to say, “I’m not going to trust any piece of content until I see that content credential”? We’ve had nutrition labels on food for a long time — this is the nutrition label on a piece of content. Not everybody reads the nutrition label before they eat whatever they’re eating, so I think it’s a similar thing, but I think we’ve done a good job of acting responsibly. We’ve done a great job of partnering with other people. The infrastructure is there. Now it’s the change management with society and people saying, “If I’m going to go see a piece of video, I want to know the provenance of that.” The technology exists. Will people want to do that? And I think that’s—

The thing everyone says about this idea is, well, Photoshop existed. You could have done this in Photoshop. What’s the difference? That’s you. You’ve been here through all these debates. I’m going to tell you what you are describing to me sounds a little bit naive. No one’s going to look at the picture of Mark Zuckerberg with the beard and say, “Where’s the nutrition label on that?” They’re going to say, “Look at this cool picture.” And then Zuck is going to lean into the meme and post a picture of his razor. That’s what’s happening. And that’s innocent. A bunch of extremely polarized voters in a superheated election cycle is not going to look at a nutrition label. It just doesn’t seem realistic. Are you saying that because it’s convenient to say, or do you just hope that we can get there?

I actually acknowledge that the last step in this process is getting the consumer to care and getting the consumer to care [about] pieces of information that are important. To your point again, you had a couple of examples where some of them are in fun and in jest and everybody knows they’re in fun and jest and it doesn’t matter. Whereas others are pieces of information. But there is precedence to this. When we all transacted business on the internet, we said we want to see that HTTPS. We want to know that my credit card information is being kept securely. And I agree with you. I think it’s an unsolved problem in terms of when consumers will care and what percentage of consumers will care. So, I think our job is the infrastructure, which we’ve done. Our job is educating, which we are doing. But there is a missing step in all of this. We are going into this with our eyes open, and if there are ideas that you have on what else we can do, we’re all ears…

Let’s talk about PDF. PDF is an open standard. You can make a PDF pretty much anywhere all the time. You’ve built a huge business around managing these documents. And the next turn of it is, as you described, “Let an AI summarize a bunch of documents, have an archive of documents that you can treat almost like a wiki, and pull a bunch of intelligence out of it.” The challenge is that the AI is hallucinating. The future of the PDF seems like training data for an AI. And the thing that makes that really happen is the AIs have to be rock-solid reliable. Do you think we’re there yet?

It’s getting better, but no. Even the fact that we use the word hallucinate. The incredible thing about technology right now is we use these really creative words that become part of the lexicon in terms of what happens. But I think we’ve been thoughtful in Acrobat about how we get customer value, and it’s different because when you’re doing a summary of it and you can point back to the links in that document from which that information was gleaned, I think there are ways in which you provide the right checks and balances. So, this is not about creation when you’re summarizing and you’re trying to provide insight and you’re correlating it with other documents. It will get better, and it’ll get better through customer usage. But it’s a subset of the problem of all hallucinations that we have in images. And so I think in PDF, while we’re doing research fundamentally in all of that, I think the problems that we’re trying to solve immediately are summarization — being able to use that content and then create a presentation or use it in an email or use it in a campaign. And so I think for those use cases, the technology is fairly advanced.

There’s a thing I think about all the time. An AI researcher told you this a few years ago. If you just pull the average document off the average website, the document is useless. It’s machine-generated. It’s a status update for an IoT sensor on top of a light pole. That is the vast majority statistically of all the documents on the internet. When you think about how much machine-generated documentation any business makes, the AI problem amps it up. Now I’m having an AI write an email to you; you’re having an AI summarize the email for you. We might need to do a transaction or get a signature. My lawyer will auto-generate some AI-written form or contract. Your AI will read it and say it’s fine. Is there a part where the PDF just drops out of that because it really is just machines talking to each other to complete a transaction and the document isn’t important anymore?

Well, I think this is so nascent that we’ll have different kinds of experiences. I’ll push back first a little — the world’s information is in PDF. And so if we think about knowledge management of the universe as we know it today, I think the job that Adobe and our partners did to capture the world’s information and archive it [has] been a huge societal benefit that exists. So you’re right in that there are a lot of documents that are transient that perhaps don’t have that fundamental value. But I did want to say that societies and cultures are also represented in PDF documents. And that part is important. I think — to your other question associated with “where do you eliminate people even being part of a process and let your computer talk to my computer to figure out this deal” — you are going to see that for things that don’t matter, and judgment will always be about which ones of those matter. If I’m making a big financial investment, does that matter? If I’m just getting an NDA signed, does that matter? But you are going to see more automation I think in that particular respect. I think you’re right.

The PDF to me represents a classic paradigm of computing. We’re generating documents. We’re signing documents. There are documents. There are files and folders. You move into the mobile era, and the entire concept of a file system gets abstracted. And maybe kids, they don’t even know what file systems are, but they still know what PDFs are. You make the next turn. And this is just to bring things back to where we started. You say AI is a paradigm shift, and now you’re just going to talk to a chatbot and that is the interface for your computer, and we’ve abstracted one whole other set of things away. You don’t even know how the computer is getting the task done. It’s just happening. The computer might be using other computers on your behalf. Does that represent a new application model for you? I’ll give you the example: I think most desktop applications have moved to the web. That’s how we distribute many new applications. Photoshop and Premiere are the big stalwarts of big, heavy desktop applications at this point in time. Does the chatbox represent, “Okay, we need yet another new application model”?

I think you are going to see some fundamental innovation. And the way I would answer that question is first abstracting the entire world’s information. It doesn’t matter whether it was in a file on your machine, whether it was somewhere on the internet, and being able to have access to it and through search, find the information that you want. You’re absolutely right that the power of AI will allow all of this world’s information to come together in one massive repository that you can get insight from. I think there’s always going to be a role though for permanence in that. And I think the role of PDF in that permanence aspect of what you’re trying to share or store or do some action with or conduct business with, I think that role of permanence will also play an important role. And so I think we’re going to innovate in both those spaces, which is how do you allow the world’s information to appear as one big blob on which you can perform queries or do something interesting? But then how do you make it permanent, and what does that permanence look like, and what’s the application of that permanence? Whether it’s for me alone or for a conversation that you and I had, which records that for posterity?

I think both of these will evolve. And it’s areas that — how does that document become intelligent? Instead of just having data, it has process and workflow associated with it. And I think there’s a power associated with that as well. I think we’ll push in both of these areas right now.

Do you think that happens on people’s desktops? Do you think it happens in cloud computing centers? Where does that happen?

Both and on mobile devices. Look at a product like Lightroom. You talked about Denoising and Lightroom earlier. When Lightroom works exactly the same across all these surfaces, that power in terms of people saying, oh my God, it’s exactly the same. So I think the boundaries of what’s on your personal computer and what’s on a mobile device and what’s in the cloud will certainly blur because you don’t want to be tethered to a device or a computer to get access to whatever you want. And we’ve already started to see that power, and I think it’ll increase because you can just describe it. It may not have that permanent structure that we talked about, but it’ll get created for you on the fly, which is, I think, really powerful.

Do you see any limits to desktop chip architectures where you’re saying, “Okay, we want to do inference at scale. We’re going to end up relying on a cloud more because inference at scale on a mobile device will make people’s phones explode”? Do you see any technical limitations?

It’s actually just the opposite. We had a great meeting with Qualcomm the other day, and we talked to Nvidia and AMD and Qualcomm. I think a lot of the training, that’s the focus that’s happening on the cloud. That’s the infrastructure. I think the inference is going to increasingly get offloaded. If you want a model for yourself based on your information, I think even today with a billion parameters, there’s no reason why that just doesn’t get downloaded to your phone or downloaded to your PC. Because otherwise, all that compute power that we have in our hands or on our desktop is really not being used. I think the models are more nascent in terms of how you can download it and offload that processing. But that’s definitely going to happen without a doubt. In fact, it’s already happening, and we’re partnering with the companies that I talked about to figure out how that power of Photoshop can actually then be on your mobile device and on your desktop. But we’re a little early in that because we’re still trying to learn, and the model’s getting on the server.

5. The S&P 500 vs. the U.S. Economy – Ben Carlson

The S&P 500 is a big part of the U.S. economy but there are plenty of differences between the stock market and the economy.

For instance, the technology sector has an outsized impact on S&P 500 earnings growth over time:..

…Depending on the time frame, the tech sector can make up the majority of both earnings gains and losses. The same is true of sales:…

…The BEA estimates tech’s contribution to GDP to be 10%.1 That’s still close to $3 trillion but the economy is far more diversified and spread out than the stock market.

A decent chunk of sales for S&P 500 companies also comes from outside our borders:…

…The S&P 500 is a U.S. index but it is comprised of global corporations…

…S&P 500 companies are enormous but the majority of firms with $100 million or more in sales are private companies:…

…S&P 500 companies account for roughly 1 in 5 jobs in the United States:…

…But these corporations are insanely efficient and profitable, accounting for half of the profits in America:


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