$SERV 🔥Serve Robotics: The AI Robotics Platform Powering the Future of Drones, Couriers, Logistics, and Sidewalk Autonomy🔥

The next addition to my Speculative AI portfolio is $SERV, Serve Robotics. So far I’ve added $ASAN, $RXRX, and $PATH, each representing a different layer of applied AI. Now I’m adding Serve because the next frontier isn’t digital AI in the cloud, it’s physical, ROBOTIC AI in the real world. And I'm feeling SUPER bullish!

Serve builds autonomous, AI-powered delivery robots that move at walking speed through real city environments. Each robot runs NVIDIA Jetson Orin edge compute fused with Ouster LiDAR, operating at Level 4 autonomy. $NVDA NVIDIA is not just a technology supplier, it is also an investor and strategic partner that provided capital and simulation tools that help train Serve’s autonomy stack.

The company spun out of $UBER Uber in 2021, with Uber still the largest shareholder and commercial partner. The robots already run in Los Angeles, Miami, Dallas, Atlanta, and Chicago, integrated directly into Uber Eats, logging over 100,000 deliveries with up to 99.8 percent reliability.

I’m adding it because AI-powered robotics is about to explode, and it’s almost impossible to find a small-cap name that combines real technical leadership, proven deployments, and a team that understands the bigger picture.

That's why I like Serve: $SERV Serve isn’t just delivering food; it’s building an autonomy OS that could power sidewalk robots, drones, warehouse movers, sanitation robots, or any form of short-range logistics. With partners like Uber, NVIDIA, Vinod Khosla, and Magna International, it’s positioned to become the platform layer for urban robotics. Let's dive in 🧵 $SERV The story behind $SERV shows how real this platform already is.

Serve started inside Postmates as its internal robotics division, Postmates X. When $UBER Uber acquired Postmates in 2020, CEO Ali Kashani negotiated to spin the robotics unit out as an independent company in 2021. Uber remained a major shareholder and became Serve’s first commercial partner, integrating its autonomous sidewalk robots directly into Uber Eats.

The spin-off gave Serve freedom to partner beyond Uber, opening doors to trials with DoorDash, Walmart, and 7-Eleven. It also kept Uber financially aligned while giving Serve full control of its roadmap, autonomy in both name and structure.

Then came NVIDIA. In 2023 filings with the SEC, Serve disclosed that NVIDIA had taken a multi-million-share equity stake, about 3.6 million shares, and received convertible notes that were later exchanged for additional stock. NVIDIA provided not only capital but also technical support through its Jetson Orin edge platform and Isaac robotics simulation stack. This partnership helped Serve reach Level 4 autonomy in real-world environments.

By late 2024, NVIDIA had exited its stake, locking in early gains, but the collaboration had already given Serve the compute architecture and AI infrastructure it still runs today.

Uber gave Serve the demand and distribution engine. NVIDIA gave it the brain. Together they accelerated Serve’s leap from concept to commercial autonomy, a rare feat for any small-cap robotics company.

$RXRX 🚀Recursion Is The Next Moonshot In My Speculative AI Portfolio: Nvidia Is In, Big Pharma Is Paying, And Wall Street Has No Clue 🚀

This stock is sitting at all-time lows, but under the hood it’s building the most complete AI-first drug discovery platform in existence. The third pick in my speculative AI portfolio is Recursion Pharmaceuticals.

This is a stock that almost no one in the AI trade is watching right now, and that’s exactly the point. It sits near all-time lows, priced like another cash-burning biotech. Yet underneath, it’s building what I believe could be the most complete AI-first drug discovery platform in existence. NVIDIA is a holder, Big Pharma is already paying to use it, and the story is only beginning.

When I built this speculative AI portfolio basket, I wasn’t looking for polished blue chips. I wanted companies with asymmetric payoff structures: ones the market has ignored, where the downside is largely capped and the upside is multiples.

That’s why I started with $PATH, then $ASAN. Both had underappreciated AI leverage in enterprise workflows (you can learn about them in my feed).

For my third slot, I turned to a very different sector: medicine. I am already an investor in $TEM (Tempus AI) in my "AI Leaders Portfolio" which is building the clinical data infrastructure for AI in healthcare. And $RXRX complements my Tempus AI thesis perfectly and is already a large data customer of Tempus AI. Together they represent what I believe is the inevitable future: AI will transform medicine in every way, from diagnosis to drug discovery.

What makes RXRX unique is its AI-driven wetlab operating system. The company runs millions of automated experiments each week, generating one of the largest proprietary biological datasets in the world. These are not just simulations but live-cell assays, gene edits, and chemical perturbations captured through high-content imaging and structured into more than 60 petabytes of data. That information powers AI models that can surface new drug targets, design molecules to prosecute them, and guide clinical trial strategy. According to CEO Chris Gibson, the ultimate vision is to build a Virtual Cell, a computational model of biology so predictive that most of discovery can be done in silico before any patient is ever touched.

NVIDIA’s investment, combined with partnerships from Roche, Sanofi, Bayer, and Merck KGaA, shows that the most sophisticated players in tech and pharma see the potential here. RXRX has the capital and the collaborators to prove its approach at scale, and if it succeeds, this could be one of the most important companies in the future of medicine. (Tempus AI), which is building the clinical data rails for AI in healthcare. RXRX complements that thesis perfectly. Together they represent what I believe is the inevitable future: AI will revolutionize medicine in every way, from diagnosis to drug discovery.

Let's dive in 🧵 $RXRX The Vision: Solving "Eroom’s Law" with an AI Wetlab OS

Drug discovery is broken. Costs rise every year, timelines stretch longer, and the number of new medicines per dollar spent has fallen for decades. This slowdown is so well-known that it has its own name: Eroom’s Law, the inverse of Moore’s Law. As computing power has exploded, biology has resisted productivity gains. That is the problem Recursion set out to solve.

The answer, according to CEO Chris Gibson, is to industrialize biology the same way other industries embraced automation and simulation. That means moving away from the artisanal, trial-and-error methods that dominate pharma and replacing them with a system that can run experiments at scale, capture the data in structured form, and feed it into AI models that get smarter with every cycle. Recursion calls this system the Recursion OS.

What makes this vision different is the scale at which it operates. The company runs millions of live-cell experiments each week, generating more than 60 petabytes of proprietary data. Instead of starting with a hunch, the OS surfaces connections and pathways humans would miss. It can then loop directly into generative chemistry to design new molecules and into ClinTech to optimize trial strategies. The goal is not to make biology incremental. The goal is to make it programmable.

This is the foundation for RXRX’s potential 20x payoff. If it works, the company will not just produce a few drugs. It will have built the first AI wetlab operating system for medicine, with applications across every disease area. That is why NVIDIA invested, why Roche and Sanofi are paying to use it, and why RXRX at $5 is not the same story the ticker tells.

$PATH 🚀 From bots to the Brain of Enterprise AI: UiPath is My First Speculative AI Portfolio Pick

Today, as promised I'm kicking off the Speculative AI portfolio with $PATH. You already know my AI Leaders portfolio, $TEM, $GTLB, $MDB, $ESTC, and $NBIS, the backbone of small and midcap AI infrastructure.

Tempus is healthcare data pipelines, GitLab is DevSecOps AI native, MongoDB and Elastic are the search and memory layer for Vector databases and bringing enterprise data to bespoke LLM and Agentic apps, and Nebius is contrarian, explosively growing, full stack infrastructure. Those are the core compounders.

But the Speculative AI portfolio is where I take shots on names that could re-rate big if their products cross the chasm. UiPath therefore gets the first slot in my list.

UiPath is trying to transform itself from an RPA vendor into the orchestration brain of enterprise agentic AI, and it seems more than a cosmetic rebrand.

In May 2025 on the Q1 FY26 earnings call, the company officially launched its Agentic Automation platform, which CEO Daniel Dines called “one of the most important and successful product introductions in our history.” He told investors, “together, we’ve turned the promise of Agentic automation into a powerful reality, and we are just getting started,” describing it as “how UiPath transforms work by unifying AI agents, robots and people into a single intelligent system.”

The Agentic Automation platform is not a single SKU but a suite of products that includes Agent Builder, Maestro, the AI Trust Layer, Autopilot, Agentic Testing, and the next-generation Intelligent Extraction Processing (IXP) solution. Dines laid out the “five powerful advantages” that give UiPath a right to win: “our extensive installed base of robots… our ability to bridge deterministic automation and probabilistic automation… our vendor agnostic architecture… our secure, enterprise grade governance… and our fully integrated end-to-end platform.”

By timing this launch with general availability of core products like Agent Builder and Maestro, and moving Maestro into preview in March 2025, UiPath is signaling that the transition is not theoretical. They are positioning themselves as more than a task automation vendor. They are claiming the role of enterprise control plane where AI agents are created, orchestrated, governed, and scaled into production🧵 $PATH The evidence of an AI turnaround is tangible. Customers have already created thousands of autonomous agents and generated over 250,000 agent runs with Agent Builder.

Maestro has powered more than 11,000 process instances.

A Fortune 15 healthcare company signed a multiyear, multimillion dollar deal to expand on UiPath’s agentic platform.

A global apparel retailer automated its entire support workflow using Maestro.

The U.S. Air Force launched its “Agentic Airmen Initiative” to embed agents into operations for 70,000 personnel.

Deloitte is co-selling UiPath’s agentic ERP model to a Fortune 20 oil and gas company preparing to automate 70 percent of manual testing in one of the world’s largest SAP projects.

The evidence is piling up.

$TSLA $TEM $NBIS $CRWV $NVDA $GOOG $QS $JOBY $OKLO AI, Robots, Healthcare, Batteries, and Transportation: Khosla's Future Investing Playbook to Torch the Fortune 500 🤖💸🔋⚕️🚗☢️

Just finished the Vinod-Khosla-with-Jack-Altman interview and my head's buzzing. Khosla opens by saying, "Almost every job is being reinvented… any economically valuable job humans can do, AI will be able to do eighty percent of it within the next five years." Pause and sit with that. Five years. This is the guy who funded Sun, Juniper, and OpenAI back when each looked absurd.

What's hitting me is that Keynes called this exact moment in 1930. He predicted humanity would solve its "economic problem" within 100 years. Khosla is saying we'll do it in 5. That's 2030: right on time.

Keynes anticipated exactly this moment: "We are being afflicted with a new disease... namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour." He called it a "temporary phase of maladjustment" before humanity solves "its economic problem."

If Khosla's clock is right, we are living through the single fastest repricing of labor since the steam engine. But this isn't just about automation; it's about reaching what Keynes called the end of the "permanent problem of the human race." The economic problem that has driven all of human evolution may be solved within the decade.

But here's where it gets unsettling. Keynes worried about what happens when economic necessity disappears; would we face a collective "nervous breakdown"? He observed the wealthy classes of his time, calling them "our advance guard... spying out the promised land," and found their example "very depressing." They had failed to solve the fundamental question: how do you live meaningfully when survival is guaranteed?

The investment implications are staggering. If Khosla's timeline holds, we're not just repricing labor; we're repricing the entire social contract. This is where radical technological innovation will change the very fabric of capitalism itself. Investors will want to profit from this transformation, and the communists have it all wrong: capitalism IS the revolution. The market mechanism is what's driving us toward post-scarcity, not fighting it.

Keynes distinguished between "absolute needs" (food, shelter, basic comfort) and "relative needs" (status, superiority over others). The absolute needs market gets commoditized to near zero; the relative needs market becomes everything.

This suggests a brutal K-shaped economy: businesses serving absolute needs face margin compression toward zero, while anything touching relative needs (luxury, status, uniqueness, human connection, meaning) captures exponential value. But to get to that zero marginal cost production economy, we have to invest in the companies building every sort of relevant future technology. These are the explosive places that create the post-scarcity infrastructure first.

Every thesis about growth stocks, every DCF we build on ten-year head-count curves, needs a rewrite. Your models need a philosophical upgrade: What does this company sell when labor costs nothing? And what companies will sell the core technologies, the picks and shovels, and the daring innovations to fill in the core infrastructure of the world to come?

So, what companies position us for this new economy that hasn't been built yet? Even if Khosla's 5-year timeline is wildly optimistic, and oh boy, it's coming regardless. 🧵 $TSLA $TEM $NBIS $CRWV $NVDA $GOOG Khosla doubles down on the social fallout. He predicts that somewhere around 2030 the sheer productivity gain flips the labor equation: "The need to work will go away. People will work on things because they want to, not because they need to pay the mortgage."

This is exactly what Keynes envisioned in 1930. He predicted we'd reach a fifteen-hour work week where people would "do more things for ourselves than is usual with the rich today, only too glad to have small duties and tasks and routines." Work becomes voluntary self-expression rather than economic necessity.

But Keynes saw the economic disruption clearly. When work becomes voluntary rather than necessary, the entire labor market structure collapses. This echoes Karl Polanyi's insight from "The Great Transformation": labor was never meant to be a commodity. Polanyi argued that treating human work as a market good was always an artificial construct that would eventually break down.

What we're witnessing with AI is the final stage of that breakdown. When machines can perform 80% of economically valuable tasks, the fiction that human labor is a scarce commodity ends. This isn't just technological unemployment; it's the obsolescence of employment as an organizing principle for society.

The investment implication is massive: we're moving from a labor-scarce to a labor-abundant world. Companies built on exploiting labor arbitrage become worthless. Companies that can deploy capital and technology without scaling human workers become exponentially valuable. The entire framework of "revenue per employee" becomes meaningless when the denominator approaches zero.

I'm not here to debate universal basic income. What matters for investors is that pricing power for routine expertise collapses. If the marginal cost of a "junior analyst" or a "primary-care triage" visit goes to near zero, firms that sell packaged know-how must either pivot to data moats or watch revenue melt. Anyone holding legacy service businesses should reread that sentence until it hurts.

This creates a brutal bifurcation in AI investments. You want to own the companies building the AI tools that destroy pricing power, not the companies getting destroyed by them. McKinsey's consulting model dies; Palantir's $PLTR data integration platform thrives. H&R Block's tax prep gets commoditized; Intuit's $INTU financial platform captures the value. Traditional medical groups get squeezed; $TEM Tempus AI's diagnostic tools extract the margin. The playbook is clear: own NVIDIA's $NVDA infrastructure, Oracle's AI Stargate project, OpenAI's models, Anthropic's safety research, xAI's compute power, Palantir's government contracts, $BBAI AI defense applications (should they scale). These companies scale infinitely without human bottlenecks.

Stargate itself exemplifies this perfectly: $ORCL Oracle's $500 billion infrastructure joint venture with OpenAI isn't just building data centers, it's constructing the physical foundation for Keynes' post-scarcity economy. When Oracle, and neocloud AI stack companies like $NBIS and $CRWV, can rent computing power and AI deployment expertise that replaces entire workforces, the company collecting that rent captures exponential value while labor costs approach zero.

$TEM 🚨 TEMPUS AI: THE NEXT TRILLION DOLLAR COMPANY? 🚨

Just listened to Tempus CEO Eric Lefkofsky drop absolute BOMBS on this Scottish Mortgage podcast (less than 2700 views on YouTube as of today!). He literally said Tempus AI has "trillion dollars a year of cash flow" potential and compared Tempus to Apple, Google, Amazon & Nvidia. I overlooked this podcast from late February before but it gives insanely valuable color into Lefkofsky's vision and the AI developments coming down the line at Tempus. Sometimes CEOs hype, and Lefkofsky admits it might not happen, but he gives good reason to think that Tempus could be the next megacap company we all hope it will be.

After hearing this, I'm more than ever convinced Tempus is a solid 10x + investment for the future. Scottish Mortgage was an early 2018 investor and Lefkofsky breaks down everything from their $1.2B AFIB algorithm opportunity to his "Nvidia moment" prediction to how they plan to extend human lifespan by A DECADE while saving $3 trillion in healthcare costs.

This thread will blow your mind. 👇 $TEM THE MASSIVE OPPORTUNITY: The Scale Is Inhuman

Lefkofsky just dropped this bomb about Tempus' potential. He said "I suspect one day there will be a Tempus-like company that is every bit as big as Apple or Google or Amazon or Nvidia or whatever. Because it will be routing tens of millions of patients around the world to the right therapy and getting paid a small toll every time it does that."

He's literally comparing Tempus to the biggest tech companies in the world. The audacity is incredible but when you hear his reasoning, it starts to make sense. Healthcare is the biggest industry in the world, and if this technology is going to be impactful in the world then it has to be impactful in healthcare. It's not surprising Google remains a shareholder and early seeder of Tempus.

$QS Solid-State Is No Longer a Myth: QuantumScape Might Be the Trade of the Decade

This isn’t another pipe dream about solid state batteries arriving “someday.” QuantumScape CTO Tim Holme laid out their case on a recent "Batteries Included" podcast, and if you understand what was said, you’ll realize they may be sitting on the most important battery tech in a generation. This isn’t just a science project anymore. This is real data, real partnerships, and a roadmap that leads directly to mass production. If you care about energy density, fast charging, cost, longevity, or simply being early to a generational leap, keep reading. $QS A Battery That Changes All the Rules

Dr. Tim Holme, co-founder and CTO of QuantumScape, opened the interview with a statement that sets the tone for everything that follows. “A solid state battery could potentially be safer, but even more importantly could potentially enable a lithium metal anode. A lithium metal anode in a battery would give the battery higher energy density and potentially also faster charge, better safety, better lifetime. It’s rare that a battery can advance in all of the metrics that are important to battery applications simultaneously. The last time that really happened was when the lithium ion battery was introduced in 1991.”

What he’s describing isn’t incremental. This is a platform shift in battery chemistry with the power to improve every core metric at once. That almost never happens.

$ionq 🚀 IonQ is taking quantum computing to new heights with groundbreaking deals, including a $54.5M contract with the U.S. Air Force Research Lab and other federal partnerships, such as the $40M ARLIS Quantum Computing Intelligence contract for the DoD, positioning itself as the go-to for quantum networking and quantum computing power for national defense. 🌍💻

With the upcoming AQ 64 Tempo Enterprise systems and a $95M revenue forecast, IonQ is rapidly expanding its reach. But what’s behind this surge? Let’s dive into the political support that’s fueling IonQ’s success, from key lawmakers backing quantum innovation to growing federal contracts.

👀 The thread ahead will peel back the curtain on the politicians driving federal interest in IonQ’s technology. From quantum cybersecurity to cutting-edge defense applications, bipartisan support is making IonQ the face of America’s quantum future.

A deep dive 🧵

#IonQPolitics #QuantumInnovation #TechPolicy #FederalContracts #QuantumNetworking

#QuantumComputing #IonQ #QuantumDefense #TechPolicy #AQ64 $ionq Ben Cardin, D-Maryland