The way I see it, artificial intelligence (or AI), really leapt into the zeitgeist in late-2022 or early-2023 with the public introduction of DALL-E2 and ChatGPT. Since then, developments in AI have progressed at a breathtaking pace.

We’re thick in the action of the latest earnings season for the US stock market – for the third quarter of 2026 – and I thought it would be useful to collate some of the interesting commentary I’ve come across in earnings conference calls, from the leaders of technology companies that I follow or have a vested interest in, on the topic of AI and how the technology could impact their industry and the business world writ large. This is an ongoing series. For the older commentary:

• 2023 Q1 – here and here
• 2023 Q2 – here and here
• 2023 Q3 – here and here
• 2023 Q4 – here and here
• 2024 Q1 – here and here
• 2024 Q2 – here and here
• 2024 Q3 – here and here
• 2024 Q4 – here, here, and here
• 2025 Q1 – here and here
• 2025 Q2 – here and here
• 2025 Q3 – here, here, and here
• 2025 Q4 – here, here, here, and here
• 2026 Q1 – here, here, here, and here
• 2026 Q2 – here, here, here, and here

With that, here are the latest commentary, in no particular order:

ASML (NASDAQ: ASML)

ASML’s management has completed value-based pricing conversations with key customers but the outcomes will not be visible in 2026; most of ASML’s expected growth in 2026 is coming from memory net system sales with, specifically DRAM, with 75% growth; management expects the ratio between logic and memory to shift towards memory, but logic demand remains strong; management expects ASML’s advanced logic business to increase by over 25% in 2026; management expects the logic business to be larger than the memory business in 2027

[Question] We also talked last quarter about higher value-based pricing and the contribution that might play on the gross margin. How is that showing up as part of the outlook? 

[Answer] We completed those conversations. So that’s been done with the key customers. The effect of that is not really visible in 2026. It will start to become visible partly in the course of 2027. The full impact of that you will start to see in 2028 and beyond…

…Turning to end use, this year, we expect logic net system sales to grow around 10% and memory net system sales to grow around 75%. The growth in memory is driven by the combination of capacity expansion of our customers and the increasing adoption of EUV on advanced DRAM nodes…

…We are still on trend where memory become more and more important, 75% increase, which is of course significant. You start to see the results of this huge memory investment. That, by the way, is mostly DRAM, to be clear. We continue to see that moving forward. I think we have said in the past that the ratio between logic and memory will most probably increase towards memory. Still, I would say that logic is also very strong. To be able to predict exactly where this is going to land is difficult because I like to stress that we see also a very strong demand on the logic side, because of course, as you know, the two are very much coupled when it comes to delivering AI capacity to the market…

…Logic went up around 10%, but the advanced logic piece, included in there is far better. So that grew over 25%, is expected to grow over 25% in this year. You are right, memory is getting closer to logic, but logic remains very important. When we look at 2027, memory comes close. But I still believe that logic will outweigh memory in the total book of business for next year.

ASML’s customers are seeing their demand rising both in the short and long-term; management thinks ASML’s customers have very good visibility into their demand; ASML’s customers think they will be in a supply-shortage until at least 2028, and so they are building up capacity faster; the faster capacity build up by ASML’s customers are leading to more demand for ASML in the short-term across its product portfolio, especially for EUV machines; ASML has already taken in a lot of orders for 2028 and there are even orders for 2029 and 2030; the higher visibility that ASML’s customers have on their demand has given ASML better visibility too; management thinks the demand they are seeing is real and not inflated by buying-behaviour from customers; customers that put an order with ASML have to make 2 serious commitments; management has not accepted the 2029 and 2030 orders because they are still understanding the overall demand picture for that time frame; management does not see ASML’s customers’ clean room constraints being a major factor on the company’s demand; the interest management is seeing from customers for 2029 and 2030 comes equally from DRAM and logic; the DRAM customers talking to ASML for 2029 and 2030 are from the US and Korea (so Micron, SK Hynix, Samsung)

We did indeed spend a lot of time with our customers and all of them are commenting that they see their demand increasing on the short term but also extending in time. I think that their visibility is very good at this point of time. Today they expect that their supply will not meet the demand at least until 2028. So this is a very, very strong demand on their side. And of course this means that they want to build up more capacity faster. So they are accelerating their plans. They are announcing new fabs. For us this translates on the short term into more demand, as Roger mentioned. Overall, basically for our holistic product portfolio and on the long-term increased visibility for our demand, especially with EUV. So a lot of our discussions with our customers now are shifting in fact beyond 2027. A lot of order intake for 2028. But also some strong interest to already place orders for 2029 and sometimes even 2030. ..

…Because they have very high visibility on what is needed in the future. And as a result we also have this very high visibility…

…[Question] Do you worry that customers are pulling in orders or giving you bigger forecasts just to secure a slot?

[Answer] When it comes to the demand we are referring to, the increased demand we are referring to, I think we are very much capable to validate that demand with some more detailed plan our customers are sharing with us in term of fab construction, release, et cetera. I think that when we talk about demand, when we refer to demand in those discussion, we really refer to demand we believe is real and not inflated by any potential buying behavior from our customer…

…If you put an order with ASML, that’s not a frivolous piece of paper that you put your name under. It comes with two serious commitments. One serious commitment is a commitment to make a down payment. As I qualified it before, it’s a down payment that is enough to hurt, right? So that’s one element. Secondly, a PO is a real commitment on both sides of the equation, and it also means that if you want to get rid of that commitment, that’s not going to be easy. That comes at a price, not just the down payment, but more than that. Therefore, before customers sign a PO with ASML, they’ve made up their mind, and they’re not doing this frivolously…

…Customers are requesting us, and therefore we have not yet accepted those, is that we want to make sure that we have a good picture of what the overall demand in 2029 and 2030 looks like that customers are currently signaling, and mirror that against the capacity expansion as we see it at that point in time. We want to do that because we don’t want now to accept orders from customer A, B, and C, and then to tell customer D, who hasn’t given orders yet for 2029 and 2030, “Sorry, we’re sold out.” That would be totally inappropriate for customers that have been business partners for us for a very long period of time. We’re now really using this period of time to mirror, to get a good understanding, what is the total demand that our customers are signaling for the 2029, 2030 timeframe? What does it look like?…

…If we look at the longer term, as I said before, beyond those little move or those tactical move, we have confirmed that the number our customer are giving us are really lined up with their plan.  In fact, in many cases, when the supply is tight, we make sure before we fully allocate a tool to a customer that the space will be there, the facility also will be there, so that we don’t ship a tool that will be waiting for weeks for a customer to use it, because, of course, other customer will be very disappointed with that. We do a lot of work to make sure that in all the plans we have at ASML, we don’t have delay of more than a few days or weeks, I would say, in shipping our product. Short answer is, I think, no. We don’t see our customer clean room constraint being a major factor on our demand…

…[Question] Just to understand the discussions that you have on 2029 and 2030, if it is more because you seem to be very positive at the moment on memory. If it is very balanced between memory and logic, or if it is still memory manufacturer who are giving you some visibility on 2028– 2029, sorry, and 2030.

[Answer] You need both memory and logic to get some AI chips. I think we have discussion with both customers because they get the same message from their own customer. I think today, DRAM is a bit more aggressive on the buildup of those capacity. But yeah, we have discussion with both. I think we see equal interest, equal, I would say, demand trajectory for both DRAM and logic, because we need both basically to get the product out…

…[Question] DRAM, is it at the same time the U.S., Korea, and even China, or is it more concentrated from a geographic standpoint?

[Answer] We are mostly talking about EUV in this case. So this excludes China.

ASML’s management has been planning for a 30% increase in capacity in each of 2027 and 2028, but management is also clear that the planned capacity increase is not enough to meet demand; ASML’s management is looking to increase capacity in 2028 beyond the 30% that had been planned; ASML’s Installed Base business is able to help its customers increase manufacturing capacity; management will be introducing the NXE:3800F EUV machine in 2027 that will also help customers increase manufacturing capacity; ASML’s customers are asking the company to increase capacity; management will soon be introducing the next generation DUV system that will also help customers increase manufacturing capacity; management does not see Carl Zeiss as a bottleneck for ASML’s capacity expansion; the capacity-increases that management has in mind are already validated with ASML’s supply chain

Last quarter, we talked about 30% more capacity next year, and also the aspiration to have another 30% increase in 2028. A lot of focus there. But to be honest, it’s becoming very clear that 30% in 2027, 30% in 2028 will not allow us to meet our customer demand. So we have to do more and we are looking basically at ways, especially in 2028 and beyond, to further extend our capacity…

…In addition to increasing unit shipments that Christophe talked about, one important driver obviously is the Installed Base business that we’ve talked about quite a bit. So of course that is a major driver. It’s something that customers really like. Because what it does, it gives you within your existing footprint, you get pretty fast incremental capacity there. So that’s been very successful so far and we expect that to continue to be quite successful on a go forward basis. We’re also very aggressively developing upgrades. So we will get more and more upgrades on our installed base available to our customers. So in that way, we try to help customers in getting instantaneous access to more capacity…

….We talked in the past about the NXE:3800F, which gets you from the 230 wafers per hour that we have today to 260 wafers per hour. That will be introduced in 2027. That will be in small quantities. But obviously for 2028 and beyond you will see that really helping to increase the capacity of our customers…

… [Question] What then would you say are the key things that you want to focus on for the rest of the year but also in preparation for next year?

[Answer] I think it’s very clear, it’s more capacity. As we discussed today, our customers are asking us every single day to get more tools…

…We also plan to introduce the next generation critical Deep UV immersion, running at 330 wafers per hour. These new products will provide incrementally more wafer capacity to the industry as they ramp in the coming years…

…We do not see Zeiss today as a bottleneck for the capacity expansion we are discussing, even beyond the 30% we mentioned for 2028. We have done, in the recent years, many work with all the supply chain to make sure that the supply chain will not be an issue for us…

…Every number we share with you is the result of us having validated that the supply chain can, of course, follow those numbers. 

ASML’s customers are starting to use the company’s high-NA EUV machine for high-volume manufacturing; TSMC has asked ASML to co-lead a consortium to introduce a 12-inch reticle for high-NA EUV; the 12-inch reticle is slated for introduction in 2031 and to enter production in 2033; management thinks the existence of the 12-inch reticle project is a sign that the entire ecosystem wants to more and more adoption of high-NA EUV; TSMC will introduce high-NA EUV in 2030 for high-volume manufacturing; all of ASML’s other major customers are also in the consortium; Samsung will be using high-NA EUV in high-volume manufacturing in 2028; Intel continues to use high-NA EUV in high-volume manufacturing, and the performance of the high-NA EUV system meets or exceeds comparable layers pattern using low-NA EUV; management now expects to see adoption of high-NA EUV increase node-on-node moving forward

The High NA program started more than ten years ago. We are all very happy to see that our customers are now about to start using the tool in high-volume manufacturing…

…So TSMC has asked us to lead with them a consortium basically to bring a 12-inch reticle to the industry. This is what is happening sometime in the first half of the next decade. But it’s also the sign of how important High NA has become in their plan. That’s also why they have basically confirmed that they will also introduce High NA around 2030 in high-volume manufacturing. So this is a very important announcement because it shows basically that over time, customers are looking at using High NA more. This is why they want to use the 12-inch reticle. Now you have noticed that all other major customers also joined that consortium…

…To further ensure chip makers can fully leverage the advantage of High-NA EUV, we also, in collaboration with TSMC, began an industry-wide initiative to develop larger formats EUV photomask. This collaborative effort aims to establish a 12-inch mask pilot line by 2031 and enter production in 2033… 

…I think the announcement, and the drive of TSMC first on the 12-inch critical mask, is very interesting there. Because the first signal it gives is that, in the mind of the customer, there will be more and more use of High-NA. Because if it was not the case, no one will really bother to go to 12-inch mask on High-NA. The 12-inch mask drive and very wide adoption by customer in the consortium, is just a sign that everyone has in mind over time to develop basically more and more adoption of High-NA…

…Samsung has also announced that they will be using High NA in high-volume manufacturing starting in 2028. And Intel, I think we talked about that before, they continue to run the system in high-volume manufacturing, increasing the number of layers. Of course, we look now at a significant amount of wafers being run there…

…Intel announced that it has exposed more than 1 million wafers using its High-NA EUV systems, with performance that meets or exceeds comparable layers pattern using low-NA EUV…

…With availability across the existing High-NA EUV fleet approaching 90%, we now expect to see adoption increase node and node moving forward. 

ASML’s management sees very strong demand in China for domestic consumption for 2026 and beyond; management sees ASML’s Chinese customers all wanting to work with the company; management thinks the likelihood of strong competition for ASML in China is still low; management thinks China is still a fair distance away from being able to compete with ASML, even though there have been rumours for 25 years that China is on the cusp of being able to compete with ASML

If you look at what China needs in terms of mainstream logic, in terms of memory, there is very strong demand in China for their domestic consumption. If you look at the fabs that are being built in China, there is a lot coming online there. Therefore, we would expect the demand in China to be strong. This year, 20%. I would argue that also for 2027 and beyond, based on the intrinsic drivers, it seems that the demand situation in China remains very strong…

…Where we are today, I think, with our Chinese customer, is that they all want to work with us. I think this is very clear. I won’t give any market share number, but you can imagine it’s extremely high, especially on immersion. Therefore, as long as we have a good market access, as long as our customer can trust they can work with us, I think that the likelihood of a major competition in China is still pretty low…

…If they were to not have access to some of our tools, then you get a lot more motivation. But it’s still a very, very long way to go. I think that we have been having this discussion about China having a tool to compete with us for the last 25 years, and every other years, we get the news that this is coming. If you stick to fact, I think the fact this year are not different from the fact a year ago or even five years ago. So I think that the progress is not very strong.

Intuitive Surgical (NASDAQ: ISRG)

Intuitive Surgical’s management is developing AI capabilities on da Vinci 5, including a voice user interface, and an automated fourth-arm control; management thinks the AI capabilities will improve efficiency and outcomes, but the technologies must earn the trust of the ecosystem before they can be scaled; the da Vinci 5 has multiple programs with advanced visualisation amd AI features that can add revenue per procedure

Our teams continue to develop additional digital and AI capabilities on da Vinci 5, including a voice-activated user interface and automated fourth-arm control to further enhance efficiency and the user experience. AI-controlled motion in surgery has the potential to improve efficiency and outcomes, but it is early and must earn the confidence of regulators, surgeons, care teams, and patients before we deploy it at scale…

…Another area that we are very excited about when it comes to da Vinci. We have multiple programs going there with advanced visualization technology around hyperspectral imaging, fluorescing molecules, and some AI features that we do think will bring that incremental value, and we are going to be able to add some revenue per procedure as a result.

Meta Platforms (NASDAQ: META)

The vision of Meta’s management for personal superintelligence is for every person to have an extremely capable personal agent that helps them achieve their unique goals in life; Meta launched its personal agent product, Muse, recently and in 1.5 months, more than 10 million people have set up Muse personal agents; Muse has been #1 in the App Store nearly every day; management thinks Muse’s engagement and retention are off to a strong start, with 25% of people who have set up Muse using it every day; the longer people use Muse, the better their retention; Muse’s retention appears to be at least 2x better than where other AI apps started at; the most common use case for Muse so far is shopping, with an average purchase size of more than $200; payment technology company Plaid said Muse has shopping activity never seen before on other services; Muse’s shopping volumes in the first week were much higher than management expected; other common Muse use cases are personal productivity and connecting to other personal services; Muse has state-of-the-art privacy and security; management intends to implement Muse Confidential VM (virtual machine) soon, so that even Meta cannot see users’ content; the introduction of Muse Wonder, Meta’s latest frontier model, has improved Muse’s quality, engagement, and retention; management believes Muse will perform better over time as Meta releases better models; management is seeing that businesses are very excited about enabling agentic commerce; management has been positively surprised by how many businesses want to connect with Muse

We have been discussing our vision for personal superintelligence for more than a year now. We want to help every person have an extremely capable personal agent that understands your goals and can help you achieve them and improve your life in whatever ways you want — whether that’s improving your relationships, helping you save time, save money, build a business, create new things, or anything else that you can dream of. Muse is the product form of this vision…

… In just a month and a half, more than 10 million people in the US and Canada have set up Muse personal agents. Growth continues to be strong and we have been #1 in the App Store almost every day. Engagement and retention are also off to a strong start. About 25% of people who have set up Muse use it on any given day. For our earliest adopters, the longer that they use Muse, the better that retention seems to get. To put this in perspective, this is more than twice the level that Threads started at or where we believe that other AI apps started at as well. 

The most common use case for Muse is shopping, with more than a quarter of people who are using Muse engaging in this with an average purchase size over $200. Plaid told us they hadn’t seen activity like they’re seeing with their connector on any other service before. And in the first week we had to work with Stripe to raise credit limits since the volumes were above what any of us expected. Beyond shopping, the most common connectors are for personal productivity and connecting Muse to your other services like email and calendar. This shows the importance of the Muse Secure VM that we’ve built to provide state-of-the-art privacy and security, and we’re looking forward to following up soon with the Muse Confidential VM, which will make it so that even Meta cannot see your content.

We have also seen that Muse Wonder improves quality, engagement, and retention further, which suggests that as we continue to improve intelligence, Muse will perform better and better over time…

…[Question] When you think about the friction points around agentic commerce, how do you guys as a company think about solving for friction that’s rising where there are aggregators or suppliers that don’t want agents to interact with their platforms or their services and how you think about lowering that friction or creating the right balance between the existing services that consumers access today relative to how this might all be changed or altered by agentic behavior over the medium to long term? 

[Answer] Right now what we’re seeing is that, overwhelmingly, businesses are very excited about enabling this because they recognize that it’s going to be a new opportunity for them not only to increase the sales and the quality of the experience for existing customers but also potentially to bring in new customers… We’ve been very positively surprised by how quickly, I think a huge amount of businesses have wanted to not only figure out how to make it so that Muse can use their services more effectively but have reached out to us to integrate around it.   

Meta’s management sees Muse entering an operational phase that involves scaling the product, growing revenue, and optimising compute costs; management expects Muse to have billions of users; management wants to create a large Muse network as quickly as possible because they think a scaled network will get more done for users; management expects the average revenue per user for Muse to eventually exceed the few hundred dollars per year seen for American users of Meta’s family of apps; management expects Muse to be free for most users and monetisation will come from (1) transaction-based fees from free users, (2) subscriptions from users who want better models and/or more tokens, (3) subscriptions from businesses who want more features, and (4) connecting Muse to improve personalisation and quality of content and advertising across Meta; Muse is very compute-intensive currently but management expects to improve its cost efficiency by 10x in the next year; management thinks Muse will become highly profitable if compute efficiency improves over the next few years; there are at least 500 million small businesses using Meta’s family of apps, and management thinks Muse can help these businesses; Muse is currently powered by Muse Spark, and Muse Wonder is available only on the paid tier; management wants to introduce a more efficient version of Muse Wonder for Muse; management recently previewed the Personal Agent Protocol, an open standard for Muse and Meta business agents; management sees a few ways to improve Muse’s compute efficiency, including (1) leverage off-peak and spare compute capacity, and (2) using smaller modles; management expects to introduce monetisation to Muse faster than Meta’s normal playbook

Now that Muse has clear product-market fit, we’re entering a new phase and a more operational phase that is focused on scaling it. The goals of this next phase play to many of Meta’s strengths. We need to do three things: scale the product, grow revenue, and optimize compute costs. We expect to grow Muse to serve billions of people…

…We think that billions of Muses in a network at scale will be able to get more done for people and businesses by working together. So we’d like to create a large scale Muse network as quickly as possible…

…The average revenue per American user for our existing Family of Apps users is several hundreds of dollars annually, and we expect that Muse will reach an even higher level over time due to the amount of commerce that we already see taking place. This will take some time, but we’re starting to work on this now…

…For most people, the product should be free and we will build commerce tools so we get paid a fee based on the transactions that we help facilitate. We expect this will be paid for by businesses. For people who want the most advanced models or to use extra tokens, they subscribe directly and pay. For business owners who want additional features to use Muse to grow their businesses or for companies that want people to use Muse for work, they will be able to subscribe directly and pay as well. And for those who want Muse to help improve the personalization and quality of their content and ads across Meta, they will be able to connect to those experiences as well…

…On the compute side, we are building out the capacity to serve more than a billion people over the next few years. In the near term, Muse is very compute-intensive to run. But we expect to improve its cost efficiency by more than 10x in the next year, which will enable it to be profitable once the revenue lines are at scale. If compute efficiency continues improving quickly for another few years, which we think is highly likely, then Muse will be highly profitable over multiple years…

…We also see a significant opportunity to extend Muse to small businesses. Based on a recent user survey, we estimate that at least 500 million self-identified small businesses use Meta’s family of apps to reach customers and generate revenue. Muse could help these businesses acquire customers and operate more efficiently, while helping people complete transactions. Over time, consumer and business agents could connect and transact directly, creating opportunities around paid usage, commerce, and business services…

…We launched Muse first on Muse Spark, and that’s what is currently the default across the free tier. And we rolled out Muse Wonder, and people can access that in the paid tier today. And we know that it performs a lot better, so we’re working on getting a more efficient version of Muse Wonder that we’ll be able to roll out more broadly…

…Earlier this month, we previewed the Personal Agent Protocol, an open standard across Muse and Meta business agents that we are developing with industry partners like Sierra, Walmart, Stripe, Shopify, et cetera. The protocol is intended to define how a consumer’s personal agent can interact securely and reliably with the business’ agent and preserve appropriate controls for both the business and customers…

…I think there are a couple of dimensions of achieving that efficiency. I think some of the more nearer-term pieces include things like leveraging offpeak or spare computing capacity to run some sets of jobs, using smaller models. There’s a lot of work to be done across different inference efficiency initiatives, like all in service effectively of higher GPU utilization and other product efficiency work we can do also. And I think over the longer term, I think this is a place where we expect that we’re going to be able to, over time as LLMs scale, get more tasks done with fewer tokens and also rely on AI models themselves to help us improve the efficiency of the software that we use to run the model…

…We are going to work on monetization somewhat sooner on this than our normal playbook for a couple of reasons. One is just the size of the numbers that we’re talking about in terms of both the costs and the opportunity, I think make it kind of important to make progress on that in order to be able to scale it. The other is just that such a large part of what people are doing is commerce. And to your question, that does include travel, too, I think we might consider travel a different case, but travel is actually one of the other top use cases for Muse, is basically people planning that out and planning different kinds of things that they would get than they might get through our Family of Apps. 

Meta’s management is building the Meta Enterprise Platform to serve as much high-margin inference demand as possible to leverage on the large fixed costs that come with training frontier models; management thinks that traditional enterprise companies do not have AI usage locked down yet

Since training is a large fixed cost, now that we have leading models, we want to serve as much high-margin inference demand as possible. That is why we are building the Meta Enterprise Platform, led by CJ Desai. Muse Wonder and even more advanced models that we are training can serve additional high-margin services beyond the Muse network, including our API, Muse Code, and other enterprise services…

… AI is creating huge amounts of disruption in enterprise today. And we don’t — from what we can see, we really don’t believe that traditional enterprise companies have this locked down. 

Meta’s management sees the business having many good uses for its compute capacity; management believes that building multiple ways to deploy advanced models will increase the chances that one or some of them will significantly outperform management’s expectations; Meta has yet to reach the limit on effectively applying compute to accelerate its core business

A fundamental feature of our business is that we have many good uses for this compute. It is difficult to forecast the exact growth rates for the Muse network, for our enterprise platform, and for how Muse Wonder and beyond will accelerate our core business. But through building out multiple ways to deploy these advanced models, we increase the chances that one or more of them significantly outperforms our expectations. Beyond serving other businesses, we have not yet found the limit of how effectively we can apply compute to accelerating our own core business. 

Meta’s management is using Muse Wonder, the company’s latest frontier model, to improve its ability to autonomously improve the company’s recommendations and advertising systems; management expects an increasing rate of improvement in Meta’s systems as the company builds better models; Muse Wonder is state-of-the-art across many dimensions important for personal super intelligence; management thinks Muse Wonder is proof of the importance of Meta training its own models; Muse Wonder has led Meta AI’s engagement per person to more than double since April; the introduction of Muse Wonder, Meta’s latest frontier model, has improved Muse’s quality, engagement, and retention; management believes Muse will perform better over time as Meta releases better models; management plans to focus on pushing the frontier with Meta’s models as well as distilling the frontier models into smaller, efficient product models for personal agents; Meta is already working on models larger than Muse Wonder that are impressive and capable; Meta is already working on smaller models that will deliver similar intelligence to Muse Wonder more efficiently

We have implemented an eval with Muse Wonder to improve how effectively it can autonomously improve our recommendations and ads systems. And as our upcoming models get even more advanced, I expect that we’re going to see an increasing rate of improvement in these systems…

… Muse Wonder is state-of-the-art across many dimensions that matter for personal superintelligence. This validates the importance of training models ourselves to deliver the best experience. In addition to Muse, we’ve also seen that engagement per person in Meta AI has more than doubled since April when we started rolling out our new models…

…We have also seen that Muse Wonder improves quality, engagement, and retention further, which suggests that as we continue to improve intelligence, Muse will perform better and better over time…

…We plan to focus on both pushing the frontier of intelligence and distilling those models into much smaller and more efficient product models that will be optimized for personal agents. My view is that we will be able to build superintelligence through scaling, so we are methodically working our way up the ladder there. We are already working on larger models after Muse Wonder, and they’re going to be very impressive and capable. We’re also working on new smaller models that are coming out soon that will deliver Muse Wonder-level intelligence more efficiently. 

Meta has been shipping many models in the last few months

I’ve been very pleased with our pace of execution here. In the last few months we’ve shipped Muse Spark 1.2 and 1.3, Muse Code, two open weights models with Muse Glimmer and Muse Spark Open, and also Muse Voice. 

Meta’s management has refocused Reality Labs on delivering personal superintelligence; the Muse agent will soon appear in Meta Glasses; management expects Muse to be the most important experience within Meta Glasses; management sees Muse as being a central pillar of the Meta Glasses business; management does not want to make a large profit on the sale of the Meta Glasses hardware; management wants to make profit on Meta Glasses through subscriptions to Muse; Reality Labs will now be shipping new devices only if it can achieve major breakthroughs; Reality Labs recently introduced the Meta VR Glasses, which is the first ever VR experience in a pair of glasses; management expects Reality Labs’ operating loss to be $15 billion in 2027 (was $19 billion in 2025) and to trend towards profitability from there

Our work on personal superintelligence is now also the focus of Reality Labs. Muse is coming to Meta Glasses starting next month, and that will be an important step towards this. People already love many features of the glasses already — music, calling, capturing moments, hearing assistance, and more — but over time we expect Muse and having your personal superintelligence with you throughout the day will be the most important part of the experience. Muse is also central to the business model for the glasses. Again, our mission and strategy are to serve everyone here. We believe in putting the power of this technology in everyone’s hands. So we have priced our devices not to make a large profit on the hardware, but to build a large software and superintelligence business on top of them over time. Glasses sales continue to grow rapidly, and now with Muse, we expect that paid subscriptions will increase and that this business will begin improving meaningfully from here.

I also shared at Connect that we are changing our approach to virtual reality to only ship new devices when we have major breakthroughs like we had with the Meta VR Glasses this year — which of course are the first VR experience ever in a pair of glasses…

…We expect that the P&L of Reality Labs to improve from here, with operating loss coming down to around $15B next year and trending towards profitability from there. 

Meta continues to see gains from its content recommendation initiatives; global time spent per user on Instagram is at an all-time high and was up double-digits year-on-year in 2026 Q3; time spent on Facebook Reels reached all-time highs globally and in the US, and both were up double-digits year-on-year in 2026 Q3; Meta’s upgraded model architecture that ranks sequences of Reels at a time helped grow time spent on Instagram Reels by over 4% in 2026 Q3; 45% of all recommended content on Instagram Reels is now less than one day old, up from 34% in 2026 Q2; Facebook Reels watch time in the US increased by 1% from a doubling of the amount of history the ranking model can consider; Meta has used LLM-based content-understanding systems to improve engagement with Instagram search results by 1% in 2026 Q3; management has started moving Meta’s content-understanding models into the Muse family; the Muse family of models has reduced per-unit content processing costs by more than 80% across Meta’s apps

On the first, we continue to see significant gains from our content recommendation initiatives. On Instagram, global time spent per user reached an all-time high and grew double-digits year-over-year in Q3, with strength across both Reels and Feed. On Facebook, Reels time spent reached all-time highs both globally and in the US, with both growing double-digits year-over-year…

…Engagement gains across our services continue to be driven by improvements we’re making to the relevance, personalization and timeliness of the content we recommend. Investments into our recommendations engine across retrieval and ranking have continued to yield positive results on Instagram and Facebook.

For instance, on Instagram Reels, our relevance launches in Q3 increased Reels time spent by over 4%, driven in part by our upgraded model architecture that ranks sequences of Reels at a time instead of evaluating each Reel independently, as well as improvements we made to add richer watch time signals. On Facebook Feed and Reels, we completed the global launch of a new generative retrieval architecture which, inspired by LLMs, labels pieces of content with semantic representations and generates potential recommendations, helping our systems surface relevant new posts before they’ve accumulated significant engagement. This new architecture is now rolled out to roughly one-quarter of unconnected Feed views and half of Reels views and increased Reels watch time by 1%…

…Nearly 45% of recommended Instagram Reels are now less than one day old, up more than 11 percentage points from Q2. On Facebook Reels, we doubled the amount of history our ranking model can consider, driving a 1% increase in Reels watch time in the US…

…We continue to process public Instagram posts each day through LLM-based content-understanding systems. These signals have improved the engagement with Instagram search results by 1% through the end of this quarter. This quarter, we also began moving our content-understanding models onto our first-party Muse model family. In offline evaluations, these models are outperforming our prior production models and are reducing per-unit content processing costs by more than 80% across Instagram, Threads, Facebook, and ads. Beyond improving quality, owning more of this stack gives us greater flexibility to develop models around the signals that matter the most for personalization.   

Meta’s management introduced Meta Generative Recommender, which uses LLMs to reason about ad content and user preferences simultaneously, in 2026 Q2; management launched the same approach to generative retrieval on Facebook Feed in 2026 Q3, driving a 2% increase in advertising conversions across targeted segments; management has expanded Meta’s GEM (Generative Ads Model) model to additional surfaces, driving a 1.7% increase in conversions for offsite conversion campaigns and a 9.6% increase in app ad conversions; improvements to Andromeda in 2026 Q3 increased conversions by 1.4% on Facebook

Last quarter, we introduced Meta Generative Recommender, which uses LLMs to reason across ad content and user preferences to predict the best ad for each person. In Q3, we launched this approach to generative retrieval on Facebook Feed, driving a nearly 2% increase in conversions across targeted segments. In addition, we expanded our GEM model for ads ranking to additional surfaces, driving a 1.7% increase in conversions for offsite conversion campaigns and a 9.6% increase in app ad conversions…

…In Q3, improvements to Andromeda such as scaling model complexity and throughput increased conversions by 1.4% on Facebook. 

Advertisers who adopt Meta AI business assistant’s recommendations had 5% more conversions at the same cost per conversion and increased their advertising investment by 9%; management will be rolling out more features to Meta AI business assistant; maple syrup producer Simply Organic Maple used Meta AI business assistant for campaign messaging and saw a 57% increase in purchases and a 36% reduction in cost per purchase

Meta AI business assistant is becoming a more proactive and capable partner for advertisers. We estimate that advertisers who adopted its recommendations drove almost 5% more conversions at the same cost per conversion and increased their advertising investment by 9% compared with similar non-adopters. We are rolling out additional capabilities, including creative insights, stronger business context and more agentic actions. These features will allow marketers to plan, create and optimize campaigns, as well as schedule tasks and alerts, through a conversational experience with approvals and previews that keep them in control…

…Simply Organic Maple, a family-run maple syrup producer in Vermont, used Meta AI business assistant to improve its campaign messaging. After the business assistant recommended testing longer, more descriptive advertising copy, the business saw a 57% increase in purchases and a 36% reduction in cost per purchase. Its strongest revised ad delivered a 3x return on ad spend, a 52% improvement from the original.  

10 million small businesses are now using at least one of Meta’s Gen AI advertising creative tools (was 9 million in 2026 Q2)

In Q3, nearly 10 million advertisers used at least one of these tools. Advertiser adoption of our video generation features grew 25% quarter-over-quarter, driven in part by ready-made videos that reduce generation time to just a few seconds from a single image upload. 

Guidance for capex in 2026 has been raised to $135 billion to $145 billion (previous guidance was $130 billion to $145 billion) or growth of 87%-100% (2025 capex was $72.22 billion); management expects to continue aggressively investing in AI infrastructure in 2027; management thinks Meta’s AI investments are already delivering substantial incremental advertising revenue; management thinks Meta’s AI investments for MSL (Meta Superintelligence Labs) can unlock significant new revenue opportunities while strengthening the core business, but the monetisation will take time; management expects to sustain strong overall revenue growth in 2027

We anticipate 2026 capital expenditures, including principal payments on finance leases, to be in the range of $135-145 billion, narrowed from our prior outlook of $130-145 billion. 

Looking beyond 2026, we are still developing our budget and capacity plans for next year, but we expect to continue investing aggressively to support both our core business and emerging AI initiatives. Our current capacity and what is scheduled to come online gives us the flexibility to allocate resources across model training, core business growth, and the development and support of new products. Our AI investments are already delivering substantial incremental advertising revenue through stronger engagement, better recommendations, and more efficient monetization. Building on this progress, our MSL investments are creating the technology and infrastructure needed to unlock significant new revenue opportunities and strengthen capabilities across the business. While these investments will take longer to generate returns than those in our core business, the breadth of monetization opportunities and internal efficiencies gives us confidence in their long-term potential. 

Looking ahead, although we are not providing a full-year 2027 revenue outlook, the benefits our AI investments are delivering to the core business, combined with emerging opportunities from model advances and product launches, position us to sustain strong overall revenue growth throughout 2027.

Meta’s management sees 3 broad themes for how its core advertising business can continue improving; the 1st theme is around traditional machine learning, where management sees a robust and healthy pipeline of improvements to be made; the 2nd theme is around incorporating LLMs into Meta’s ranking and recommendation engines; the 3rd theme is around generative AI tools found in the Advantage+ suite that make it easier for advertisers to quickly and seamlessly generate creatives

I think our ads business has been benefiting for now many years from our ongoing investments in both kind of what we would have called traditional AI machine learning models and then, of course from the sort of more recent generation of models. I would say that there are three themes there that I think are worth outlining. 

The first is just the kind of traditional roadmap of performance improvements that we have in the pipeline based — that is what I would describe more as business-as-usual machine learning work. That continues to be a robust and healthy pipeline. And as we are looking into 2027, again we’re not providing an outlook, but I would say that our investments and product improvements across both engagement and ads initiatives give us confidence that we have meaningful runway to grow our core business throughout 2027…

… The second theme I would say is that we are excited about some of the new research bets that we have as we move into sort of a more LLM-oriented AI infrastructure to help us more deeply reason about people’s preferences and what they’re interested in both across organic content and recommendations, and we expect that we will be able to unlock benefits to our ranking and recommendations engine from that research, too…

…The third thing is that we expect that generative AI tools which have already very valuable for advertisers will continue to grow in terms of the features that we make available to advertisers primarily through the Advantage+ suite but features that make it easier for advertisers to quickly and seamlessly generate, whether it is creative or take an image and generate video or generate sound, all, I think in service of making the ads increasingly personalized for the person that they’re being served to.  

Taiwan Semiconductor Manufacturing Company (NYSE: TSM)

TSMC’s capital expenditure is always in anticipation of growth in future years; management has maintained capex guidance for 2026 at US$60 billion to US$64 billion; TSMC’s capex in the last 3 years was ~US$100 billion, and management continues to expect the next 3 years to have much higher capex (previous guidance was for it to be “much higher”); the majority of TSMC’s capex is for long-term demand and management is also looking for revenue growth to outpace capex growth; management expects TSMC’s business to continue to be supported by leading-edge nodes, including 2nm; management now thinks the AI accelerators business is likely to have a CAGR for 2024-2029 of even higher than the high-50% (previous expectation was for even stronger CAGR for for 2024-2029 than the high-end of the mid-to-high-50% CAGR communicated in the 2026 Q1 earnings call)

At TSMC, a higher level of capital expenditures is always correlated with higher growth opportunities in the following years. Given the continued robust multi-year demand from our customers, including the emerging agentic AI market, we reiterate our full year 2026 capital budget to be between $60 billion and $64 billion. We continue to expect our CapEx investment from 2026 to 2028 to be even more significantly higher than the past three years as we continue to invest heavily to support our customers’ growth…

…The majority of the CapEx is always related to the long-term demand. That will be the composition going forward. Capital intensity-wise, as we always said, if do our job right, the increase in revenue will outpace the increase in CapEx, and that is still the case from what we are looking at…

…Moving into fourth quarter 2026, we expect our business to be supported by continued strong demand for our leading-edge process technologies, including the steep ramp-up of our 2 nm technology…

…[Question] Any update on your AI CAGR growth? I recall previously we talking about like a high 50%.

[Answer] All I can say right now is the demand is extremely robust, okay? We did not see any sign of slowdown. Whether it is a high 50 CAGR, it does not matter. It probably will be higher…

…There is no ceiling for TSMC’s profitability, but a dramatic increase will not happen overnight either.

TSMC’s management thinks recent developments in the AI market are very positive for AI’s long-term demand, in particular, the rise of agentic AI; management thinks there’s great adoption of open source AI, which will lower the barrier to AI usage and lead to more demand for leading-edge silicon; management sees agentic AI and networking driving further silicon demand, in the form of CPUs, and networking chips; management thinks the value of semiconductors is set to increase in the future because of the entire AI trend; management thinks AI-related demand is structural and will last for multiple years; management thinks TSMC is well-positioned to capture the full AI-related demand since all AI players are working with the company; management has not included CPU demand in their assessment of TSMC’s AI-revenue CAGR

The AI market continues to be very strong. Recent developments are very positive to AI’s long-term demand outlook. We observe increasing AI demand fueled by the rising adoption of agentic AI as we transition from chatbot to AI assistance. In addition, we are observing great adoption of open source AI models. This will drive greater efficiency and help lower the barrier to future AI usage, and result in more and more demand for leading-edge silicon. Thus, AI-related demand is being supported by strong underlying demand for AI accelerators. In addition, the emergence of agentic AI CPUs and the continued demand for networking chips are driving further silicon demand. Therefore, semiconductor will remain essential in the AI mega trend. The value of semiconductors in the global supply chain is set to continue to increase in our view. This will create more value opportunities for our customers to capture and more value opportunities for TSMC as well.

No matter which approach is taken, you will require use of the most advanced semiconductor process technology. With our technology leadership, manufacturing excellence, global capacity expansion, and customer trust, we are well-positioned to capture the full multi-year structural AI-related demand. Therefore, all the AI players are working with TSMC…

…[Question] On the agentic AI demand on the CPU. So I wonder, according to our previous framework, demand forecast framework, the mid to high 50s growth including the CPU or not, and if we heard our clients increase the CPU forecast significantly, when is the next time we refresh our AI demand growth numbers?

[Answer] It is not included in our AI demands calculation. The reason is very simple, because we cannot identify which CPU user in the conventional server CPU or AI server CPU. Also, it depends on our customer’s application and their own allocation. So, no. So far today, we stick to our initial very narrow definition on the AI’s demand.

When planning for TSMC’s manufacturing capacity, management collaborates closely with its customers, and customers’ customers, and now they are even checking on the development progress of data centers and power supplies in the USA; management thinks the cloud service providers (CSPs) have been well-prepared; management has a very good idea of the multi-year product roadmap and production plans of TSMC’s customers and continue to hold strong conviction in the AI mega trend; management is moving at full speed to increase TSMC’s capacity, with TSMC expanding at a record pace; TSMC has nearly 20 fabs in progress worldwide, with 13 leading-edge and advanced packaging fabs in Taiwan to be built over the next several years; management intends to capture every piece of business possible; management thinks the demand for TSMC is still higher than supply and they are working very hard to close the gap

To address the structured increase in the long-term semiconductor market demand profile, TSMC collaborate closely with our customers, yet our customer’s customer to plan for our capacity. In addition, we are now going one step further and sending our own teams of people to check on the data center build-out progress and power supply situation in the U.S. The feedback is so far so good, and the CSPs has been well-prepared. Internally, TSMC employed a disciplined capacity planning system to assess the market demand from both a top-down and bottom-up approach. This is a continuous and ongoing process. Given the fundamental complexity of leading-edge technologies and the design in and lead time involved, we already have a very good idea of customers’ multi-year product roadmap and production plans. Thus, we continue to hold strong conviction in the AI mega trend.

We are moving full speed ahead to increase our capacity to meet our assessed demand, and stepping up our CapEx investment to support our customers’ future growth. TSMC is expanding at unprecedented pace with a nearly 20 fabs worldwide in progress. We are building 13 leading-edge and advanced packaging fab in Taiwan over the next several years, and another five to six fabs overseas…

…We have no intention to leave food on the table for others, and we want to capture every piece of business possible…

…We have a very sophisticated capacity planning process, and we also have a very disciplined on our consideration. Let me share with you, we put every possibility we can, talking about the CSPs, CapEx, data center build-out, financial, power supply, and also other component supply, et cetera, into our consideration. We make our own judgment, and then based on our assessment the demand, we still think the demand is higher than the supply, and we are working very hard to narrow the gap.

TSMC’s management will only be utilising ASML’s high-NA EUV lithography systems in 2030 because they think that is when the technology will be sufficiently mature with a good cost curve; management is confident that TSMC’s relatively late adoption of high-NA EUV compared to competitors will not disadvantage TSMC

[Question] You did touch upon it, the High NA agreement with ASML from 2030 onwards. I’m just curious, historically, TSMC was more ahead of the curve with the EUV adoption. It looks like by the time you adopt High NA EUV, it would be 2030, 2031, but some of your competitors would already been using it by then. Do you see that as a disadvantage, or you’re not worried about competition getting ahead with High NA EUV?

[Answer] We always evaluate a new tool, and if we want to put into the mass production, it got to be the best technology with a very reasonable cost, and most important is the best maturity. Okay? We say in 2030 we will start to use it because we also think at that time, High NA will be mature, and we are also working very closely with our ASML to establish a 12 in photomask by 2031. At that time, we think that High NA’s cost will be reasonable and for TSMC to make it into the mass production. This is a very good tool, let me emphasize that. In the smaller geometry, it definitely has some advantage. Whether that our technology, because we are using it later than our competitor, so disadvantage to TSMC? No, because we have confidence that we are still the best company to offer the most advanced technology to our customers.

TSMC’s management thinks the company’s advanced packaging technology is very competitive; management is willing to be the backup plan for some customers that are using Intel’s EMIB-T advanced packaging technology

[Question] If some customer, they initially choose to use Intel’s EMIB-T, and for some reason cannot get to sufficient demand, are you also support customers for the CoWoS version or capacity.

[Answer] I still think that TSMC’s advanced assembly, or they say packaging technology, are very, very competitive. But the most important thing is that we using that one to help us help our customer’s product can be introduced in the market smoothly. That’s our number one priority. We have to offer them the best technology with enough capacity. So far, let me share with you today’s situation. We are in the real-world production of 5x reticle size. I don’t believe that anybody can do that today except at TSMC, and the yield is excellent. So our customer are very satisfied with the result. We are working on the 9x reticle size and moving into the 14x reticle size. Of course, we are also working on the CoWoS, and to make sure that in the future we can offer a reasonable cost reduction. But so far, the CoWoS is still the number one choice for our customer. As time goes by, yes, our competitor offer a very competitive solution. Still, I want to say that today’s situation, we are the only one that makes sure that the advanced packaging is a 5x reticle size, and still, we are very competitive. I want to emphasize that…  Let me say that, yes, we will be. Number one priority I already indicate that TSMC’s customer’s product can be introduced into the market smoothly.

TSMC’s management thinks the learning curve for the company with the new technology nodes is actually better now with the current situation of having both smartphone and AI HPC (high-performance computing) applications drive demand for the new nodes

[Question] In the past a new node is mostly ramped with smaller die size and simpler design. But today we have both the smartphone and also with the AI and HPC applications coming in. Does that increase the complexity of the node process architecture, make the learning curve more challenging or difficult, and therefore the implication to the margin?

[Answer] Today’s situation actually is a little bit different from previous years. Yes, we now have a very strong demand from smartphone and also AI HPC applications. So the smaller die size per se or the big die size in the accelerator, they happen at the same time. This is to TSMC’s advantage, let me say that. Because we are good. We have been prepared for this kind of thing, and happy to working with us. So the learning curve, yes, but we are doing a reasonable job, and so the customer are very happy today.

TSMC’s management thinks the shortage of power supply in the USA for AI data centers does not drive additional demand for the company’s backside power rail solution

[Question] Could this tighter and tighter power grid surprise make your customer actually accelerating adoption of your Super Power Rail product for the better performance power?

[Answer] Whether this kind of situation change our customers’ behavior and move more into the backside power rail? Answer is no. Whether you use the backside power, those kind of metallization scheme is based on your need for your product. Okay? Some of the accelerator might be using it, some of the product like mobile phones, they don’t use it. So it depends on customer’s product.

Tesla (NASDAQ: TSLA)

Tesla’s management sees Full Self-Driving (FSD) software as the  biggest driver of demand for the company’s vehicles; management thinks there’s no competitor to Tesla’s FSD; FSD is approved in many countries in Europe, but Tesla is pushing for an EU-wide approval; management thinks an EU-wide approval could happen in the next few months; more than 75% of Tesla vehicle deliveries in North America in 2026 Q3 included a paid FSD subscription at the time of delivery, up 20% from 2026 Q2; every Tesla car delivery comes with a free month of FSD, but vehicle owners are still signing up for the paid subscription; FSD now has 1.7 million paid customers globally, and more than 50% of them are paid subscriptions; management wants to sell certain cars in Europe with some FSD benefits before a broader approval in Europe is obtained; Tesla is building AI-based mapping and navigation into FSD v.15 (version 15) and it will be very personalised, and will also tap on the collective intelligence of all Tesla cars; management thinks FSD is an incredibly hard problem to solve for other vehicle manufacturers; management is seeing many customers walk into Tesla’s showrooms and ask for an FSD-drive, instead of any specific car model; management thinks Tesla’s FSD is much better than what any other Chinese car company can deliver; FSD is already approaching $1 billion in ARR (annualised recurring revenue)

Obviously, we are going to be ramping, and we are ramping production meaningfully. The biggest driver for demand is Full Self-Driving. Today, there is really no competitor for FSD in any car that you can buy…

…We are pushing very hard for FSD approval in additional markets. We are now approved in many countries in Europe, and we are hoping for an EU-wide approval. It is hard to predict, but maybe within a few months, but I would be surprised if it takes longer than Q1. Obviously, that is not a timeframe we control, but we do anticipate being fully approved throughout Europe and many other countries…

…In Q3, over 75% of deliveries in North America included a sign-up for paid FSD subscription at the time of delivery, which is approximately 20% higher than Q2. Overall, the FSD attach rate continued to improve, reaching over 1.7 million paid customers globally, of which for the first time, 50% is based on subscriptions. Given the strength of FSD in the U.S., we are taking extra steps to sell certain cars in Europe with some benefits to try and get more fleet out there before a broader FSD approval is obtained…

…One thing which I’d also like to make sure it’s clear when I say in North America that 75% attach rate at the time of delivery, this is every car which we’re delivering comes with a month of free FSD subscription. Still, people are signing up even though they have that free available…

…We are building our own maps, but not the same way as OpenStreetMap. We are building an entirely new architecture with essentially AI-based mapping and navigation. It’s going to be super awesome. It’s going to be integrated with voice. You can talk to it, ask for different routes. It’s going to learn your personalized preferences, plus also the fleet preferences. The collective intelligence of all the cars are going to flow into making the maps and navigation be super cool. You’ll see the start and end of trips already use this technology pretty soon as part of the V15 release. Over the next several months, it’s just going to take over all of the navigation functions, parking, destination handling, and just will know you better than you know yourself in some regard for the driving task…

…It’s easy to get to the first 90% and make a cool-looking demo. But when you get in the long tail of this problem, it’s so long that people don’t realize anyone with their sane mind should not attempt to solve this problem. It’s so difficult, and so long tail. Especially to get to a safety point where you can drive safely for millions of miles with no injuries and so on, that’s going to be extremely hard. As we release unsupervised FSD to the broader customer fleet, it’s just going to be I don’t think anyone can match it in several years…

…Especially in our showrooms here in the U.S., customers are now coming in and saying, “Can we get into an FSD drive?” They’re not asking for 3/Y or Cybertruck. They’re saying, “Can we get an FSD drive?” That has become the key driver because what it does is it actually opens up a lot more flexibility for different parts of the population wherein they had issues driving conveniently before. Now they’re getting their freedom back by being able to use FSD…

…The leapfrog which we have in terms of this technology is not there with any of the other Chinese OEMs today. We are working very diligently to try and get broader FSD approval in China. It is hard but for certain cars, we have been able to have FSD operating and whoever has tried it there, they understand how much better it is as compared to any of the competition. In fact, I do not know if you have seen this, there have been some competitor CEOs who have come and done FSD drives here in the U.S., and they themselves have been blown up as to what FSD is capable of doing…

…[Question] Are you at some point going to disclose for us the annual recurring revenues that FSD represents. I did my own math, and I’m thinking it’s probably now approaching $1 billion of ARR. Is that the right order of magnitude?

[Answer] I think the numbers which you shared are correct. As it scales further, we will start sharing more metrics around FSD, not just the revenue, but also other key metrics around it.

Robotaxi’s fully autonomous miles driven are scaling rapidly on a weekly basis; management thinks no other company can match Tesla’s scale with autonomous vehicles; Tesla’s Cybercab fleet in Austin has grown by 10x since launch a month ago; Cybercabs are in use at scale in Austin, Texas; Robotaxi’s unsupervised miles increased by 8x in 2026 Q3; management is preparing for a broader Cybercab launch in other markets; management thinks Cybercab provides the best Robotaxi experience, but they will augment the Robotaxi fleet with other vehicles over time; management’s ambition with Robotaxi is to take over every part of terrestrial transportation, not just transporting people, and so they are preparing a huge investment cycle for the business; management launched Cybercab with the help of data from Tesla’s other vehicle platforms; management is seeing very good scaling in Cybercab’s AI capabilities; Cybercab will be launched in Dallas in November; management thinks consumer vehicles with FSD can become part of the Robotaxi fleet in 2027 Q2; management is trying to get the Cybercab to customers by the end of 2026; management sees most Cybercabs as being for Tesla’s internal use to deliver transport-as-a-service; the Robotaxi service is still not at the $0.30 per mile cost-target management has, but they see a path to get to the target; management has released a safety report on unsupervised Robotaxis in China, and the data is hard to refute by any regulator; management thinks Robotaxi can start moving the needle in Tesla’s financials by 2027 Q2; Tesla’s engineers think scaling the Cybercab is going to be relatively easy; the Cybercab has 50% less parts than any other Tesla vehicle so that’s 50% less things that can go wrong; the listed Cybercab capacity of 125,000 units a year is not near the actual capacity of that vehicle line; there are still software challenges for the Robotaxi service; management thinks Tesla will end up doing most of the passenger miles on in any country it is allowed to operate freely

We are seeing the Robotaxi miles driven or fully autonomous miles driven scale exponentially, meaning scaling very rapidly. It would be hard to overstate at this point, it really is an extremely fast week-over-week growth in autonomous miles. I do not think there is any company in the world that can match our scale with autonomous vehicles as we continue to ramp. The Cybercab fleet in Austin, for example, has grown by a factor of 10 since launch about a month ago…

…Come into Austin and you’ll see Cybercabs in use at scale in Austin. As I think a lot of people saw with the Austin City Limits concert recently…

…Accumulative unsupervised miles 8x in the quarter, as we had weekly double-digit growth throughout the quarter. We’re taking all the learnings from our Austin expansion to help us prepare for broader Cybercab launch in other markets. Our priority is progressing the density and expansion of the network through vehicles that provide the best experience, like the Cybercab. We will also continue to augment the fleet with other variants over time to address the terrestrial transportation needs of the total population. I’d like to stress that what we are trying to do is literally take over every part of terrestrial transportation. Not just getting people. We’re starting with getting people from one place to the other, but we want to basically own this transportation of any kind on Earth. We are in a huge investment cycle to set us up for the future…

…We launched Cybercab this quarter, which is very exciting. We achieved that by mostly learning from data from the other vehicle platforms. For example, Model Y, Model 3, et cetera. All of the data helped make the Cybercab without requiring a ridiculous amount of vehicles to produce the data. We are seeing very good scaling in terms of Cybercab’s AI capabilities. We launched in Austin, but that’s only because we had some cabs, and we want to swarm Austin with Cybercabs everywhere. There’s no fundamental reason that we are limited to Austin. In fact, next month we’ll be launching in Dallas…

…The software for Cybercabs and Model Y is the same. Pretty soon we will be able to release the same software as part of the V15 release to customers. The only additional requirement is to make sure that, for example, the customer Model Ys can be part of the geo-fences and the fleet management that Tesla has for it to be fully autonomous. We suspect somewhere around Q2 next year is when we can turn on some of the first customer vehicles to be part of the Robotaxi fleet…

…We are trying to get Cybercabs to customers by the end of this year, 2026. Obviously, we are producing them in our line in Texas, but all of those are currently going to our own internal Robotaxi fleet. As Tesla grows, we will mainly deliver fully designed autonomous vehicles to our customers. Cybercab will be the first…

…The vast majority of the Cybercab stuff will be essentially Tesla-owned and transport as a service…

…Week by week, as Elon was talking about, we look at the miles and how many paid rides are happening. Are we at our goal of $0.30 today? No. Do we see a path to get to that? Yes, we do. It is all about scaling operations. What you will see over the next few months is that today, Cybercab, which is the primary Robotaxi product, is available only in Austin. We do plan to bring it out in some other cities before the end of this year. As we add more Cybercabs, we are also learning from the operational experience of managing a fleet, pick-up and drop-off, cleaning, all those things. All those costs are being dialed in, and that is why, like I said before, we definitely see a path to get to our $0.30 target…

…We are actively working with the regulators in China because I do not know if you saw this, but we have released our safety report on FSD before, but we have also released our unsupervised, our Robotaxi safety report. We just think this is the right way to get people into a safe environment because you know the amount of accidents which happen because of driver that was not being alert. This is the only way we can ensure that there are less casualties in the world. Any regulator who looks at the data, it would be very hard for them to refute it…

…[Question] I am curious if there is a way you can triangulate that for us into revenue and maybe profitability of the Robotaxi business. If you sustain, let us say, 15% week-over-week growth in these miles, you will probably cross 10 million miles by the end of the year. How many miles would you need to generate gross profit?

[Answer] I would say it’s not going to move the needle this quarter. But if you say maybe, I think it starts to become noticeable probably in Q2 and then probably a big deal by Q3 or Q4 of next year…

…[Question] How do you expect the ramp-up curve to be on the Cybercab line?

[Answer] I would give kudos to the engineering team. They have designed a product because not only do I talk to the engineers, I also talk to their manufacturing guys. They think this is one of the easiest product for them to scale in terms of manufacturing. Scaling would not be that much of a challenge… We have 50% less parts than any other vehicle we’ve ever built, so that’s 50% less things to go wrong. We’ve definitely been bursting the Cybercab line to see how fast we can run it. I think the listed capacity is more of a rate at which we’re capable of running today, but the actual capacity of that vehicle line is significantly higher…

…[Question] A follow-up on Robotaxi. It does seem like you’ve hit an inflection point here in Austin over the last month or so since you launched the Cybercab. Would you generally say the bottlenecks at this point to growth are more regulatory-driven as you think about expanding into new geographies, and that you’ve kind of gotten through most of the hurdles on the software side?

[Answer] For example, we had initially had the Robotaxi service from 6:00 A.M. to 9:00 P.M., then we expanded to 10:00 P.M., 11:00 P.M. Now it’s going to be pretty soon 2:00 A.M. So we are slowly expanding the availability of Robotaxi, and that is driven by the capability of the AI software. We just want to make sure that there’s not a single safety incident. That is our operating principle. Even if there’s the slightest possible risk at all, we don’t take on that risk. So we are very risk-averse in that sense, as in we want zero injuries or anything bad happening. That is the driving principle. We will see that over the rest of this year, we’ll unlock 24/7 operation, go to higher speed roads. We think all of that is necessary to scale and offer a great product to a lot of users. That’s why we wanted to both do the breadth-first of doing multiple cities. We do six cities now. We are also doing the depth of having a lot of vehicles in a single city, which is in Austin. We’ll expand to more weather conditions, day and night conditions, highways and high speeds, and all of that will be done hopefully by the end of this year, at which point you will see a lot more scaling, a lot more cities being covered by Robotaxi. So it’s not purely regulatory or something like that. It is technology-driven, but we do see that pretty quickly become regulatory, perhaps in Q1, Q2 timeframes…

…Unless we are stopped by governments, which is certainly a possibility, if they are trying to protect a domestic industry. I think Tesla will end up doing a majority of all passenger miles on Earth in any country where it is allowed to operate freely.

Tesla has started early production on the high-volume Optimus line in Fremont; management thinks the ramp of Optimus’ manufacturing will depend on the slowest or unluckiest component involved in the manufacturing process; Tesla already has the vast majority of a million units per line production line landed in Fremont, but management thinks it will take a year or more to get to that annual production rate; management is still tweaking Optimus’ design, and AI software, and believe they will be done by the end of 2027, which is when Optimus can be delivered outside of Tesla; management thinks Optimus can get the training data needed only by Tesla manufacturing 10,000-20,0000 of the robots and having them do self-play; management is building the Optimus Academy for the Optimus robots to practice tasks and these data can be used to improve Optimus’ capabilities; management is convinced that Optimus will be the biggest product on Earth; management thinks there’s no other general-purpose humanoid robot that is close to Optimus; management thinks Tesla can release a video of Optimus doing things it was not pre-programmed to do in about 1-2 months’ time; management thinks a lot of humanoid robot demonstrations are pre-programmed, and the robots are not really using any advanced AI or SI (superintelligence); management thinks Tesla will integrate the Tesla AI 5 chip into Optimus in April 2027; management thinks the AI 5 chip will improve Optimus by an order of magnitude because AI 5 has an order of magnitude more compute than AI 4; management thinks Optimus’ initial and most valuable customers will be industrial companies; the hand of the Optimus robot remains one of the toughest problems for Tesla to solve; management is already building Optimus robots for training purposes even when the hands are not perfected; management thinks there will eventually be more humanoid robots on Earth than humans; Tesla is building a new Optimus factory in Fremont that will have a much larger capacity than the Austin factory

Regarding Optimus, we’ve started what I’d call early production on our high-volume line in Fremont. I want to elaborate on this point because I have said this before, that the growth of Optimus, it’s an S curve, but the initial part of the S curve has a shallow slope and is somewhat bumpy because it is such a radically new product. The way to think about it is there’s 10,000 things that have to go right for production of the robot, and it’ll move as fast as the slowest, least lucky of the 10,000. We do have the vast majority of a million unit per line production line landed in Fremont right now. I would expect that it takes us probably at least a year, maybe a little longer, to get to that annualized rate, to get to 20,000 units a week…

…There’s still some things we need to tweak about the design because you need to deliver a robot that is safe and reliable and has long duration. It can’t wear out after a month. There’s still quite a lot of work to do with regard to the AI and the robot for it to be truly useful for open-ended tasks. Like I said, I would expect that the AI, the electromechanical design, and the reliability and usage duration, the usage life of the robot, I do expect these issues to be solved around the end of next year. That’s the time to expect when we’re delivering Optimus to companies outside of Tesla…

…There’s a lot of things we have to get right about the AI architecture that we’re still working on. We’re making good progress, but that needs to be sorted out. Really, in order for Optimus to get the training data we need, we actually need to make a lot of Optimi. We need to make, I think, on the order of 10,000 or 20,000 bots and then have them do self-play. We’re building out an Optimus Academy, where Optimus can practice doing a very wide range of tasks. Then we can use that data in sort of a flywheel to make it better and better at these various tasks. A big difference with Optimus versus the cars is we don’t have this vast fleet of cars from which we can gather training data. With Optimus, we have to bootstrap it by making the robots and having them do self-play, which is really how a human learns to navigate the world…

…I remain convinced that Optimus will be the biggest product on Earth, and humanoid robots in general will be the biggest product on Earth…

….To the best of my knowledge, there is no one that is even close to Tesla with respect to a general-purpose humanoid robot…

…I think we may be ready to release an Optimus video in a month or so. I want to make sure that when we release this video, that it is not like a canned demo that. When you see these humanoid robot demonstrations, some of them look very impressive, but they are not really using any kind of advanced AI or SI. They are pre-programmed deterministic tasks, and if you actually try to use that humanoid robot in the real world, you would have a lot of trouble. It would not work, basically. So I want to release a video where it is Optimus doing things that are not pre-programmed. I think that is maybe a month or 2 for that to have a demo that you can believe what you see type of thing.

There is another milestone that I think important we want to get to, which is to integrate the Tesla AI 5 chip into Optimus, which, if things go according to plan, will be in approximately April of next year. That is a giant improvement in capability with an order of magnitude more operations per second. It is an order of magnitude more compute, AI 5 versus AI 4. That will help Optimus a lot because the degrees of freedom that a humanoid robot has to deal with are far greater than what a car has to deal with. It is a bit of a struggle to squeeze everything needed to operate with all the degrees of freedom of Optimus and the wide range of tasks. If you think of a humanoid robot is going to do 1,000 times more things than a car would do. That is some very big number, basically. I think the additional compute of AI 5 will make a big difference…

…In terms of the initial customers for Optimus, I think it probably would be things that are industrial applications at first. Things like dangerous repetitive tasks, things that people really don’t want to do, and that you want done basically 24/7. So, around the clock stuff. That is going to be the highest value for Optimus in the beginning. As we scale production, of course, it would be something that people can buy for their home. But the highest value use, I think, will be heavy industry, dangerous tasks, or things that may cause repetitive stress injuries, and that you want done 24/7…

…[Question] A quick follow-up on Optimus. I know you mentioned that we could see a video soon, that there’s quite a bit of progress, but you’re still making some refinements. I guess, just generally speaking, where do you see most of the design changes still happening going forward? Is it still the hand that’s an issue? Anything you can call out there?

[Answer] It is mostly the hand, and just the fine-tuning of the hand design, and the fingers especially. It is a hard problem, because humans have self-repair. Our body repairs itself, but robots don’t. Our fingers are kind of squishy and have lots of sensors in our skin. It is hard to make a hand that can handle lots of wear and tear. But it is still squishy enough to pick up delicate objects, and has all the sensors and doesn’t damage the sensors when you do repeated actions. There is a lot of little things that you realize actually what an incredible thing the human hand is at the end of the day. So it is mostly from an electromechanical standpoint, the hand. There are other things that are improving as well throughout the robot, but that is the main thing…

…[Question] Can you talk about the strategy around ramping Optimus production just a little bit to start training, even if the hands aren’t fully baked with the final design? It seems like there’s a lot that you could end up doing in terms of the training cycle and maturing some of the simulation technology, even without perfected hands.

[Answer] That’s what we’re doing, is we’re building robots that do not have perfected hands, and we are making progress with Optimus training and ironing out all aspects of the supply chain and the production system. We’re doing all these things in parallel, like this giant production line at our Fremont factory, massive supply chain, and then fine-tuning the design and engineering simultaneously with the AI software. All these things are happening simultaneously.

…I think at some point there will be more humanoid robots on Earth than there are humans…

…You should know that not only the Fremont factory, we’ve also started constructing a factory here in Austin, which would be able to do a lot more robots as compared to the Fremont one.

The research fab for Tesla’s Terafab project is progressing quickly; the research fab will commission machinery int 2027 H1 and management hope to start manufacturing in May/June 2027; management’s aim is to manufacture useful chip volume around 2028 Q3; management thinks Terafab will be the most valuable building in the world; management thinks Terafab will be necessary for the scaling of Optimus, as it can address bottlenecks across the semiconductor value chain; management thinks TeraFab will need significant capital to meet the goal of reaching useful chip volume around 2028 Q3, in the order of $100 billion over the long term; Tesla has already placed most of the orders for the first set of equipment for TeraFab

Regarding the Terafab, the Austin-based research fab is progressing quickly. We’ll begin commissioning machinery in the first half of next year, and hopefully, if things go well, we’ll make our first test chip just to see if we can make any chip at all around May or June. Our aspiration is to be making some kind of useful chip at volume around Q3 of 2028. As I’ve said publicly on X, the Terafab I think will be the most valuable building in the world and will probably have an economic value that will place it in the top 20 of countries. So it’s an epic project. This will be an incredibly important asset, if not a necessary asset, in order to scale, especially Optimus, as we can address bottlenecks in semiconductors, whether it’s memory, packaging, logic, or whatever the case may be…

…[Question] You mentioned that you had an an aspirational goal of 2Q 2028. Do you have a sense on how much capital needs to be invested to get there? Also what kind of milestones we should be on the lookout for on the way there?

[Answer] It’s going to be some pretty significant capital. It’s certainly in the tens of billions for Terafab. We’ve got to figure out what the relative split is between SpaceX and Tesla in terms of who pays for what at Terafab. But it’s not going to be less than tens of billions in capital equipment up through early 2028. Then it’ll probably be north of $100 billion long term…

…The first set of equipment for the fab which Tesla is building, we’ve actually already placed most of the orders.

Tesla’s energy business is seeing extreme demand from data centers, and this is driving improvements in selling prices and margins

On the energy business, we had our second-best quarter of deployments of 13.7 gigawatt hour of energy storage… the business is witnessing extreme demand from data centers, and we are doing our best to increase production, and accordingly, we’ll see improvements in ASP and further improvements in margins as we move forward.

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