Snowflake’s overarching platform is called the Data Cloud. This infrastructure unlocks the ability to affordably store, organize, query and learn from data sources at gigantic scale. It offers these services with elastic compute capabilities to allow for flexible scaling up and down of usage. The architecture naturally separates the functions of data storage and consumption, unlike legacy data warehouse solutions. That means data consumption capacity is untethered from public computing resources. This removes the computing capacity bottleneck and enhances the scalability of data storage.

Under this framework, I can store as much data as I want without the requirement for immediate processing. That processing utilizes computing capacity. In Snowflake’s case, the storage is done in a centralized data repository in the Snowflake Data Cloud. It’s processed only as needed. Data is utilized virtually, which removes the need for dedicated hardware. This scalable (or “elastic”) reality limits waste and cost. Snowflake does all of this for clients in a managed fashion to minimize client talent and infrastructure needs. There are a few key products to know & track:

The Snowflake Data Warehouse is where structured data is stored and (on command) processed. Structured data is formatted data. It’s utilized for record keeping and report creation. Data can be easily fetched via structured query language (SQL).

Snowflake Data Lake does what the warehouse does for unstructured data. Unstructured data is unformatted and used to uncover new insights and patterns.

“We announced support for unstructured data over 2 years ago. Now, about 40% of our customers are processing unstructured data on Snowflake. And we've added more than 1,000 customers in this category over the last 6 months.” – CEO Sridhar Ramaswamy

“Snowpark” is its application-building platform. It frees developers to work with data in any source code language. With it, developers can process and visualize data (through Snowpark functions) and build apps (through Snowpark Native Apps). Snowpark is their data-equipped playground to build new things. GenAI models are voracious data consumers. Snowpark Container Services allow GenAI models to run closer to the data that they require. This enhances performance and expedites model training. Movement of apps, workloads and developer attention from Apache Spark to Snowflake is a key source of growth here.

Snowflake data sharing is its secure product for, as the name indicates, sharing data among the rest of Snowflake’s participating users. As more opt in, a compelling network effect of relevant data builds and Snowflake’s value proposition deepens.

Miscellaneous tools:

Snowflake’s revenue model is consumption-based in nature. This means visibility compared to SaaS business models is not as strong. It also means customers can more easily scale down (or up) usage when times are bad (or good).

The margin cuts were related to updated plans to invest $50 million in graphics processing units (GPUs) and its purchase of TruEra AI Observability. TruEra optimizes large language model (LLM) building by guiding best practices for data usage, while delivering anomaly detection and model hallucination minimization (fewer wrong answers). This should help sharpen Snowflake’s efficiency-first, cost-minimizing model-building niche. Snowflake added 35 employees as part of the purchase.

Snow trades for about 150x this year’s EBITDA and 240x this year’s EPS. EBITDA and EPS are both set to materially fall Y/Y, before resuming expected rapid growth next year.

Ramaswamy’s 3 priorities are: to listen and learn from customers, perfect SNOW’s go-to-market processes, and to accelerate product innovation and development. He spent the most time talking about the last two items. From a go-to-market point of view, the company is implementing sales processes and dedicated workloads (like for AI or data engineering) to drive product-market fit. Ramaswamy thinks steady progress has already been made; at the same time, he also thinks there’s “more to gain” in terms of efficiency to drive “further revenue growth.”

Snowflake leadership has recently been critical of their own pace of innovation. They bluntly told the world that they needed to move faster, and signs of this happening are already emerging. Its mid-sized language model (MLM) called Arctic outperforms much larger models, such as Meta’s older Llama 2 on some benchmarks. This was built in 90 days and for an “eighth of the training cost vs. similarly-sized peer models.” Arctic was purpose-built for enterprise data and open-sourced to allow users to easily build models and apps. This, like for all open-source models, means 3rd party developers will improve Arctic over time through their own work. Arctic ranks highly in standard query language (SQL) generation and code following.

We can’t get through an innovation section without talking about AI. Sorry… I don’t (do) make the rules. Cortex AI is what Snowflake calls its “AI layer.” It’s a slew of GenAI-powered tools to (as Snowflake always says) bring AI, application-building and analytics right “to a customer’s data.” Cortex can summarize and derive meaning from seemingly unstructured text, help beginners write SQL, gauge human sentiment from jumbled data and help with sharpening pattern recognition to tighten forecasting. 750 customers are now using it. 

“A cool thing about Cortex AI, in the context of our consumption model, is that our customers don't have to make big investments to see what value they're going to get because they don't have to make commitments to how many GPUs they rent. They just use Cortex AI, for example, right from SQL. And this means they can focus on value creation.” – CEO Sridhar Ramaswamy

Snowflake is currently finishing up its Iceberg table support, which will roll-out later in the year. These are open-sourced data storage offerings, often with lower storage costs, open-source integration flexibility and more data control. The proliferation here is leading to data storage and duplication revenue headwinds, with storage making up about 10% of Snowflake’s total business. Iceberg is creating more open access to data for enterprises. While this is a near-term headwind as some data is moved from Snowflake to Iceberg tables, leadership continues to think it will be a future accelerant. Clients who adopt these open source tables routinely have 90%+ of their data already outside of Snowflake.  They will now see less friction associated with using all of Snow’s other applications and services for larger sums of their data. Storage is only 10% of revenue. This process will hurt that 10%, but may help the other 90% over the longer term.

33% of Snow’s customers are now sharing data with the rest of the ecosystem in some capacity vs. 24% Y/Y and 28% Q/Q. This creates a compelling network effect where Snow’s products become more uniquely valuable and potential clients are more incentivized to sign on. This quarter, the network effect, through a partnership with Fiserv, led to it winning 20 clients.

This was a fine quarter. There were some pros and cons. The Q1 outperformance on the top line was certainly the highlight, and the smaller annual top line raise is likely just prudence regarding some baked-in assumptions. The innovation engine is accelerating and rapid RPO growth is a good hint for faster revenue growth in the future. Conversely, the margin cuts were quite material as it leans into CapEx to support its GenAI ambitions. This is likely the correct decision for the long haul, but as one of the most expensive stocks on the planet, investors should be able to demand investment and continued margin expansion.

Palo Alto is a cyber security company competing across endpoint, cloud and network use cases. Most of its platform is made up of integrated M&A, while it competes with pretty much everyone besides identity brokers in the space. The network security suite is called Strata; the endpoint security suite is called Cortex (not the same as Snowflake’s Cortex product above); the cloud security suite is called Prisma. 13% of its customers now use all 3 platforms, with 51% using 2 of them. There’s a legacy network hardware portion of this business and next generation endpoint, cloud and network portions too. For other cybersecurity disruptors in endpoint and network, the next generation portion of this company is the read-through.

Please note that the Q2 2024 GAAP net income margin line excludes a one-time tax benefit.

PANW trades for 57x this year’s earnings with EPS expected to grow by 25% Y/Y this year and 11.4% Y/Y next year.

More of the same here. Between nation-state adversaries exploiting zero day (new) vulnerabilities and sophisticated attacks on large enterprises, the need for cybersecurity tools continues to rise. The new SEC disclosure mandates are merely adding to this momentum by highlighting the companies that are taking these real threats seriously… and those that aren’t. GenAI is lowering the bar for hackers to conduct detailed, intricate breaches and making rapid remediation all the more important. GenAI is also pushing companies to rapidly migrate their data and assets to cloud environments that can support next-gen apps and use cases. That heightens the need for strong protection. Across endpoint, cloud and network security, the demand environment remains robust. There was no mention of budget fatigue like last quarter, but instead commentary surrounding healthy budgets for Palo Alto’s products.

As a reminder, last quarter PANW embraced what it calls “platformization.” This simply refers to pushing clients to embrace the full suites within all three of its platforms. The company had been waiting for contracts with competing point solution vendors to pursue these cross-selling opportunities. Now, it is proactively offering free trials to these clients while contracts unfold. This offers proof of concept and shrinks the sales cycle. PANW also believes this platformization process will help it stand out from legacy firewall vendors and firms with less complete offerings. It’s how companies “can keep pace with the volume of threats” to gain a more holistic view of operational security. 

The team talked up its product leadership in 23 different subsections of its markets and wants to more proactively promote this holistic leadership to customers to further drive differentiation. The words platform and platformization appeared a combined total of 81 times in their earnings remarks. Maybe they’re trying to tell us something. Just maybe. To date, PANW has completed 900 platformizations, with its sights set on 1,600 more.

The IDC published a study highlighting the impact of PANW platformization. Per that research firm, the process directly lowers annual cost by 10% for customers and boosts efficiency by 30%-40%.

There are some financial positives and negatives stemming from this evolution over the next 18 months and beyond. First, the good. A big piece of platformization is pushing clients to its NGS products like cloud detection and response (CDR) and Extended Security Intelligence and Automation Management (XSIAM). When it lands a non-platformized customer, initial ARR is somewhere between $200,000-$300,000. For platformized customers, depending on how many of the 3 pillars they’re using (Cortext, Prisma, Strata) that jumps to $2,000,000-$14,000,000. The impact is massive.

On the other hand, this process will also lead to billings weakness for another 15-18 months through fiscal year 2025. Why? Billings happen when payments are made. Clients are embracing deferred payment contracts as part of platformization in lieu of upfront compensation as they “grapple with the higher cost of money.” Adding to this billings headwind are the aforementioned free trials that PANW is offering to clients of other vendors.

There are a few other places to look for signs of forward-looking demand, excluding this noise. Bookings is a demand metric that credits PANW for deferred payment contracts while remaining performance obligations (RPO) do too (as bookings are part of RPO). RPO rose 23% Y/Y compared to the slow 3.1% Y/Y billings growth. This is a concession that the team is happy to make, considering it thinks this evolution will materially extend its growth runway.

This is where Palo Alto competes most closely with CrowdStrike, SentinelOne and Microsoft Defender. Endpoint is bolstered by extended detection and response (XDR), which infuses third party data sources into endpoint detection to augment coverage. It’s where PANW’s extended security orchestration, automation and response (XSOAR) lives, which helps guide best practices for incident response while ranking severity of threats. It’s where its attack surface management product (called Cortex Xpanse) lives to obsessively seek out and uncover any vulnerabilities.

What do all of these products need to actually provide value? Data… and lots of it. That’s where the firm’s Extended Security Intelligence and Automation Management (XSIAM) comes in handy. Cybersecurity firms love acronyms. XSIAM is mainly used for Cortex, although it is an important piece of some cloud security tools too. XSIAM is essentially security information and event management (SIEM) 2.0. SIEM aggregates security data to help organize threats, while XSIAM enhances this with more automation. The process of collecting and organizing security data uplifts every single product in this bucket. And that’s probably why Cortex ARR continues to accelerate and why XSIAM bookings crossed $400 million just 18 months into launch.

SASE stands for Secure Access Service Edge, which combines its suite of network security tools. It prevents unauthorized access to data, abuse of networks by bad actors (like phishing attacks to overwhelm networks with traffic) and broad visibility into health and performance of a network. More tools here include URL filtering and data loss prevention/protection (DLP). It’s where PANW hangs its hat on a “zero trust” security approach. As a review, zero trust means a bad actor cannot penetrate the most vulnerable part of a digital ecosystem and move freely within it thereafter. Zero trust ensures consistent and complex validation of these permissions at every turn. This is a key place (among several) where network and cloud security tie closely together.

This quarter, PANW debuted “SASE 3.0.” This enhances app speed by a factor of 5 by using GenAI to better contextualize and model user journeys. It introduced LLM data classification to more deeply tag data bases with granular context. It also added browser-level network protection; the team thinks it’s “becoming clear that the browser offers a better way to secure devices.” SASE ARR rose by 50% Y/Y for the 6th consecutive quarter.

Palo Alto bought IBM’s QRadar product for $500 million. It will also pay an earn-out over “multiple years based on successful migration of QRadar on-premise customers to XSIAM.” PANW will become IBM’s preferred cybersecurity partner and IBM will platformize on Palo Alto’s three product suites too.

Good quarter. It’s hard to call this quarter amazing, despite the small raises. Those raises were compared to estimates that had fallen materially in the last three months. But the quarter not being overly punished also makes sense. The NGS ARR guidance boost was likely loved by analysts, as it shows what the growth engine can look like as it moves beyond this somewhat hectic transition. 

This remains a pricey company at 57x earnings and a PEG north of 2x. That could easily be justified if you see this platformization shift proving successful. Cybersecurity is among the most resilient, least discretionary, fastest growth, longest runway sectors on the planet. That means winners in the space will likely get a premium for quite some time. If you don’t see this transition working and PANW being one of those winners for a very long time, then the stock is probably overpriced today. That’s the current debate; I’m on the fence; Pelosi loves it.

It’s no secret: I’ve been deeply impressed by the last several DKNG quarters. Consolidation has begun to pick up with players like Sports Illustrated shutting down; a two-headed monster in DraftKings and FanDuel seems to be emerging. 

DraftKings has demonstrated a keen ability to consistently cut marketing spend while growing market share. That shows me their claims about subtle product differentiation and brand quality are likely accurate. It has mastered the state launch playbook, with new states turning EBITDA positive almost immediately. Even in its most mature states, the runway remains long and the black market conversion opportunity remains large. Just this past week, DraftKings reported a new record hold (take) rate and revenue period in New York. Continued hold rate gains are expected to continue as DraftKings rolls out more parley options.

Its current profit explosion is a result of the delightfully surprising customer stickiness. It will go from roughly GAAP EBIT break-even this year, to $450 million next year (44x EV/EBIT) and $950 million (21x EV/EBIT) the year after, based on current estimates. Non-GAAP EPS is set to compound at a triple digit clip for the next two years, with it trading for likely 80x-85x 2024 earnings, 25x-30x next year and a current PEG ratio of under 1x. Estimate trends are firmly positive.

As an aside, the decision between this one and Flutter (owns FanDuel) was a tough one. I prefer the pure-play, digital U.S. gaming footprint over more of an omni-channel, global footprint. But it was a close call. I did not seriously consider any other players in the space.

Next month, I will publish an investment case article that dives far more deeply into the company, why I think the big boys (in a seemingly moat-less sector) are finding rapid leverage and the real risks that coincide with this stock (mainly regulatory). That should be sent in mid-June after the Nu investment case article is published. Stay tuned.

DraftKings closed its acquisition of the mobile lottery company Jackpocket. Jackpocket is an app-based facilitator of ticket purchasing from entrenched lottery companies. One of the best ways to drive retention and lifetime value in a highly competitive space is via cross-selling. Ask Uber, Spotify or Amazon. It means lower marketing intensity and higher-quality revenue. Jackpocket represents a third product category retention arrow in DKNG’s quiver. The main cross-sell opportunity here will be more states legalizing iCasino, but its proposed Jackpocket acquisition provides another outlet in the lottery market. It will also be able to market its current offering to that firm’s 700,000+ users (with a bit of customer overlap, I’m sure). 

Late Wednesday night, hedge fund legend Bill Ackman took to social media to accuse Uber of blatant fraud. He demanded a restatement of earnings and called the actions of the company “evil.” I have a lot of respect for Bill, but this was an inappropriate, unresearched, and negligent rant. His claims were based on taking a single taxi in New York City (through a new Uber partnership), tipping the taxi and not seeing the tip immediately show up on the screen. The driver told him this meant Uber took the tip for themselves, and Ackman needed no other information to accept that opinion as gospel and to run with it. 

Thankfully, Uber’s PR team rapidly addressed the situation. Uber immediately passes on the tip to its taxi partner named Curb. Curb then disperses the tip to the driver. Unfortunately, Ackman’s post received millions of views in the very short period of time between his erroneous accusations and this timely response. The actual user is an innocent UX issue. It’s a simple fix to make it more intuitive that tips are eventually paid to their accounts. But sure, let’s just assume it’s fraud.

Barclays is moving to a 5-day in-person work week. Most mega-cap tech names are calling employees back to the office more frequently. Nike and legacy banks are all making the same exact moves. What does this mean? The return of the daily commute. As annoying as that is for employees, it is music to Uber’s ears. This is a compelling daily use case that its product suite can impactfully address, and should be a tailwind for usage frequency for Uber and Lyft too. That’s why products to cater to this use case were a focus point in Uber’s most recent product event.

Nu is entering the telecom market in Brazil. It recently secured Mobile Virtual Network Operator (MVNO) approval through a Claro partnership, paving the way for a third quarter debut. The partnership structure is one of the most intriguing parts of this release. MVNOs in Latin America have been squeezed on margin by bigger boys like Claro for quite some time; telecom is a low margin business that requires hefty volume to make fixed costs rational. Scale matters a lot. Instead of buying data from major telcos and upcharging like other MVNOs there do, Nu is creating a revenue sharing agreement with Claro. This is yet another example of Nu’s massive customer base being an asset in many, many ways. It brings entrenched, deep-moated players to the table to partner due to the immense value that having 54% of Brazilians on a platform provides.

This approach is similar to Nu’s strategy for insurance and other non-core businesses it runs: it sheds the asset-heavy nature of the offering while still being able to offer it in a quality manner. With its massive customer base, Nu will also be able to seamlessly cross-sell and side-step hefty customer acquisition costs (CAC) just like it does in banking.

I got a few questions about whether I saw this as a distraction from the core business model. I don’t really think so… because I don’t view Nu’s core business model as solely financial services. This company is about making processes and legacy offerings wildly more convenient for Latin American customers. It is about emulating the slickest interfaces and applications across the planet to delight its end customer. Banking is simply one area where customer service was awful and inefficiency was rampant in its markets. This is another… and there will be more. 

Nu’s Ultravioleta card membership hints at where they want to take this thing. I see Nu eventually creating a baby Amazon Prime, with a boatload of other membership perks to drive usage, monetization, pricing power and retention.

Mercado Libre has begun the banking license application process in Mexico. Like for NuBank, this licensing will significantly broaden the services this firm can directly offer its users. I think incumbent banks are in trouble. Nu and Meli both have the financial service fixed cost advantage over incumbents via no branches, a more modern tech stack and broader cross-selling capabilities to diminish CAC. A formal banking license removes the one edge these incumbents had over them: an ability to connect lower cost deposits with higher yield loans. I’m not sure what stands in the way of these two taking the lionshare of the Latin American consumer banking market. It’s a matter of time, in my view.

In terms of Nu vs. Meli, I think it’s pretty inevitable that the product suites will continue to converge. I don’t see Nu doing its own fulfillment, but other than that, everything else seems to be firmly on the table. Nu already has a marketplace that’s growing nicely; Meli already offers credit cards. I also view future expansion from Nu into Chile and Argentina as all but invariable. The way leadership talks makes that pretty clear.

This week, Lulu published a press release that I candidly found a little irksome. Not alarming… just a little irksome. Chief Product Officer Sun Choe is leaving for another opportunity after a lengthy tenure. Instead of replacing this c-suite position, Lulu’s Global Creative Director will assume his responsibilities. Additionally, it’s creating a new merchandising and brand team to “scale global and regional go-to-market.” Nikki Neuburger was named Chief Brand & Product Activation Officer for this group. None of this bothered me. One very specific sentence in that release bothered me: 

“The strategic organizational changes are intended to support the company’s near-and long-term growth plans, accelerate product innovation, and further enable its go-to-market strategies.”

This is the first we are hearing of a need to accelerate the innovation engine. Lulu prides itself on staying ahead of the pack here and evolving with changing trends. That is how it has navigated fashion cycles so seamlessly over the decades. This sentence hints at its issues being more similar to Nike’s issues than the out-of-stock inventory problem blamed last quarter. As consistent readers know, I tend to over-analyze every little word. I need to guard against that and I am aware I could be doing it in this situation.

So, considering that, where do I personally go from here? I’m doing nothing. Lulu is trading at several year lows for EBIT multiple while its long term growth plans are firmly intact through last quarter. A combination of abnormally tough first half comps and its discretionary spending niche being a bit challenged today are, to me, the main sources of negative sentiment here. And if I’m right, neither of those items are structurally concerning. See Ulta, Starbucks, Revolve, VF Corp etc.

When stock prices fall, new risks will magically emerge. Some are blaming poor performance on Vuori and Alo competition. To me, not having 100% market share of a $300 billion athleisure market growing at a nice clip isn’t a red flag… it’s a permanent inevitability. If Lulu had 100% market share, it would be a mega-cap, not a $40 billion company. And as a reminder, we recently went through sell-side research showing how Alo and Vuori store openings near Lulu locations actually bolster its traffic on average. In a growing sector, not being the only notable brand in town can actually help expand wallet share and make everyone more successful. Alo and Vuori finding growth does not at all mean Lulu can’t. Some are even arguing that fewer likes on its social media pages Y/Y are yet another red flag. Quite the massive stretch.

We’re just two weeks from its earnings report. I really think this high quality team would have pre-announced bad results and worsening guidance as part of this news if results truly were going to be that bad. Regardless, near-term, temporary headwinds are creating a perfect storm of poor sentiment. I don’t think this will rapidly abate in the near future, as comps stay tough this quarter and macro remains challenging. But I also don’t think the Lululemon investment case is in trouble. I think this brand is entirely fine and I’m leaning on several years of strong execution to arrive at that conclusion. Results early next month will go a long way towards confirming or not confirming that idea. I remain optimistic about this name, but slightly more cautiously so after this press release. I did not add again to my position at my previously chosen target for this reason. I have no interest in trimming.

Two things are true: influencers are an increasingly powerful means of driving merchant sales, and YouTube’s commerce-related viewing hours are growing briskly (specifically +25% Y/Y). YouTube is making it easier for verified creators to tap into affiliate-style marketing for their favorite brands. They’re allowing these creators to tag products in videos and live feeds for commissions. And as part of this unlock, they’re directly integrating with all Shopify Advanced and Plus merchants to connect Shopify’s vast merchant network to this budding source of demand. This is a win-win. YouTube gets its hands on a large cohort of merchants, with Shopify essentially serving as a large channel partner. Shopify gets to deepen its commitment to allowing merchants to “sell anywhere.” The two companies already work closely together in several other areas, with this news merely marking the latest development.

Venmo has been under-monetized for years. It’s one thing for a Meta to take its time on something like WhatsApp monetization while it prints cash and finds scaled growth elsewhere, but PayPal doesn’t have that luxury. PayPal needs to turn on this money faucet yesterday. This week, I got an interesting notification from Venmo. Starting in July, all goods and services-tagged payments will be charged a standard 2.99% transaction fee. These have functioned as free peer-to-peer payments to date. This allows Venmo to extract value from its budding business profile base to turn all of the loyal traffic, volume and attention this verb-of-an-app has into real revenue. What a concept. This will be highly incremental to transaction margin as well. Venmo is already orchestrating this volume, it’s just not making any money from it. The costs will not scale with the added revenue contribution from this change, and traction here could mean Venmo joins Braintree, a potential branded recovery, Fastlane and the stable coin as dearly needed profit tailwinds.

PayPal raised $850 million in 5.15% convertible senior notes (CSNs) due in 2034 and $400 million in 5.50% CSNs due in 2054. Proceeds are expected to be used to refinance $1.25 billion in notes maturing this October.

The Consumer Financial Protection Bureau (CFPB) designated buy now, pay later (BNPL) lenders as credit card issuers. This means consumers can dispute changes on BNPL loans going forward. This will raise costs associated with running this business. Players like Affirm cheered this regulation while Klarna was more critical of the ruling. It’s likely safe to assume that’s because Affirm’s policies leave it less vulnerable to this change than for Klarna. Nobody else commented as those two are the only pure-play BNPL companies in public markets. Block, PayPal, Shopify, SoFi and others could also potentially be impacted less materially as chargeback rates could rise. This makes proper fraud detection all the more important.

Progyny (PGNY) added another $100 million to its buyback program. It is now authorized to purchase up to roughly 5% of its share count. That could lower its 2024 earnings multiple from 17x to 16x if it gets aggressive.

Disney licensed the rights to 10 College Football playoff games to Warner Brothers. This is a good way to minimize hefty content spend while securing the rights a company most wants. It lets Disney pick and choose what it wants while monetizing the rest. Disney also fired 175 employees within its Pixar division.

Amazon is working on infusing more of its GenAI consumer application work into Alexa. Amazon’s. Amazon is also gearing up to spend $17 billion on cloud infrastructure expansion in Spain. Finally, Amazon and Meta participated in a $1 billion funding round for a now $14 billion AI firm called “Scale AI.”

Lightspeed (LSPD) and Uber (UBER) announced a new integration for LSPD’s merchants on Uber’s Uber Direct and Uber Eats platforms.

Alphabet (GOOGL) is investing heavily in India smartphone production capacity. Google also plans to purchase HubSpot for $31 billion. HubSpot is a customer relationship management (CRM) software tool that competes with Salesforce, Microsoft and many others.

J.P. Morgan’s (JPM) Jamie Dimon says he will retire within 5 years. He’s Buffett’s favorite banker, and obviously an iconic executive within the sector.

As expected, Microsoft (MSFT) announced a new series of personal computers purpose-built for its GenAI copilot products. This will become available next month.

Tesla removed its 2030 delivery targets from its latest impact report. It’s reportedly accelerated robotics and autonomous hiring. Tesla cut Model Y production in Shanghai amid challenging demand. This is according to Reuters, not Tesla.

I started the DraftKings position and added to Duolingo with a small deposit.