Eric Landau

[Eric Landau @EricEncord]

Something’s been in the works. More soon...

[Eric Landau @EricEncord]

@encord_team @latimes Read the LA Times piece here:

https://t.co/pl36xQp6af

[Eric Landau @EricEncord]

.@encord_team made the front page of the Sunday edition of the @latimes!

The piece spotlights our R&D facility in Hayward, where robots and human operators are collecting the data needed for a new generation of Physical AI systems. The problems we are solving there are not trivial or obvious. Few people think to write down how much force it takes to pull open a fridge door, or how hard you can squeeze a paper cup before it buckles, or what grip keeps a coffee pot from sliding out of hand mid-pour.

That data doesn't exist to be scraped from the internet. It has to be made from scratch, one repetition at a time, by a human pilot until it's clean enough to learn from.

Robots do not become autonomous by magic. They become autonomous through millions of examples, corrections, edge cases, interventions, and repetitions.

That is the work behind the work in Physical AI. Great to see it recognized on the front page.

[Eric Landau @EricEncord]

@paulg Perfect era for the lack of color, greyness of the UK. Ironically, it's our time to shine...

[Eric Landau @EricEncord]

Read the full case study here: https://t.co/0Z7Nf2wcC4

[Eric Landau @EricEncord]

"Encord was a game changer for us."

@UiPath is a company we have admired for many years, so it’s great to help their team push model performance forward as they scale across new modalities.

The UiPath of today looks different from the company that started by automating UI-based workflows. Today, their team is building across video, text, voice, and agentic systems, with @encord_team helping power the data layer behind that work.

One of the most gratifying parts of the case study was hearing their Director of Applied Science say that Encord gave the team “headspace.”

It may not be the first word you’d expect from an applied science leader, but it is one of the most honest descriptions of what good data infrastructure can do. It gives great teams the space to focus on the hard problems, not the operational drag around the data.

We are proud to support one of the companies that defined the RPA category and continues to push the boundary on AI.

[Eric Landau @EricEncord]

Andrej Karpathy is joining Anthropic.

Around a year ago, when the LLM race was far murkier, a common framing was that each major lab had a different comparative advantage. OpenAI had the strongest brand, Anthropic had the strongest team, and Google had the strongest distribution. What would the winning moat be?

Right now, the market seems to be voting for talent.

Anthropic has now surpassed OpenAI in valuation and is moving at a pace that would make it the fastest company in history to reach a trillion-dollar valuation.

Even while automating enormous amounts of cognitive work, Anthropic is still doubling down on elite talent density. In the age of AI, people still matter the most.

This may end up being one of the highest-stakes management case studies ever written.

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[Eric Landau @EricEncord]

A lot of the discussion around the Anthropic/SpaceX deal has focused on Claude rate-limit increases, but I think the partnership reveals something much more interesting about where the frontier lab market is heading.

One thing that has struck me as unusual about frontier labs is that operating one successfully as a business requires making highly accurate compute-demand forecasts years in advance. There’s a strange impedance mismatch where AI paradigm shifts and hype cycles happen on the order of weeks, while data-center buildouts happen on the order of years.

A more mature market will likely evolve sophisticated compute intermediaries that absorb and manage this forecasting risk so labs can focus on the layer they are actually trying to be good at. This deal feels like an early signal of this evolution. SpaceX acquiring xAI and then leasing its Colossus cluster to a competitor looks less like a lab move and more like the move of a compute broker.

I wouldn't be surprised by a world where this becomes further financialized and we start to have a proliferation of compute derivatives and financial products that allow labs to hedge and traders to speculate.

The next generation of lucrative high-frequency trading firm strategies may end up being in market-making GPU futures instead of equities. A quant's dream come true.

[Eric Landau @EricEncord]

The robot economy is coming, and data is the bottleneck.

It was a pleasure sitting down with @dessaigne on the @ycombinator podcast to discuss this bottleneck and reflect on the progress @ulrikstighansen and I have made since the W21 batch.

We started YC before the AI boom and struggled to convince many VCs the AI market would be big enough to support a new data company. Now we are building critical infrastructure in the midst of the largest technological shift in our lifetimes.

Nicolas was one of our batch partners and has seen the whole journey of the company. We cover topics ranging from the founding story behind @encord_team, why AI engineers didn't trust AI automation before ChatGPT, the data problem holding back Physical AI, and the next steps for the company after raising our Series C.

YC was our first outside backer and we are very grateful for their support through years of starting, building, and scaling Encord.

Watch the full conversation below!

[Nicolas Dessaigne @dessaigne]

I sat down with @ulrikstighansen and @EricEncord, the co-founders of Encord, after their $60M Series C led by Wellington Management.
From a wild bet to their incredible success with Physical AI, their story is wild! A seed fund once rejected them because they didn't believe in AI and invested in an Icelandic dating app instead 😅
Here are a few things from the conversation that stuck with me.

[Eric Landau @EricEncord]

Sign up for our @encord_team webinar here! https://t.co/SqiK9EePy8

[Eric Landau @EricEncord]

The shift to World Models may be the most important transition happening in Physical AI right now.

VLAs are remarkable at what they do, but they mostly react to the world rather than reason about it. Humans don’t operate that way.

We act in the physical world with instinct and intuition, but also with an internal model of how the world works. We anticipate, simulate, and plan. We understand how our actions will change the environment before we take them. World Models are emerging as effective systems to bridge this gap for Physical AI.

This is why I'm very excited on our upcoming webinar "Will World Models Eat Physical AI" this Wednesday with pioneers in the field @chris_j_paxton (@agilityrobotics) and @JasonMa2020 (@DynaRobotics).

Sign-up link in the comments!

[Eric Landau @EricEncord]

Check out our @encord_team NYC roles here! 👇https://t.co/wR85OlSFFq

[Eric Landau @EricEncord]

The last time @encord_team was in New York, we were on a billboard in Times Square announcing our Series B. Now we're back, but this time we're here to stay. Encord is opening its first New York office!

We always knew we'd return sooner rather than later. In the past year we've expanded to serve hundreds of customers, raised our Series C, and grown the team across London and San Francisco. At the same time, more and more of our customer base was coming out of NYC, and it became clear we needed to be closer.

Some of the most exciting AI work happening right now is in NYC, especially with forward-thinking enterprises in media, healthcare, and finance. New York also has some of the sharpest commercial and technical talent in the country, and we want to build alongside them.

If you're an ambitious builder based in NYC who wants to work on frontier problems in AI, take a look at the roles in the comments. We'd love to work with you.

[Eric Landau @EricEncord]

Two big releases from the model frontier this week. Anthropic gave a controlled debut to Mythos, a model so capable that it has been highly restricted rather than released publicly. Meanwhile, Meta, after a year of rebuilding its AI team, unveiled Muse Spark. Most AI coverage obsesses over benchmark scores of these models, but I think these launches highlight something more interesting.

Anthropic and Meta are proposing opposing visions of what superintelligence looks like. One is built around pure capability, the other is built around personal context.

By restricting Mythos, Anthropic is signalling a view of superintelligence as a central oracle that should be guarded, controlled, and deployed selectively for high-stakes work. Meta’s bet is different. It envisions superintelligence as deeply personal and productized for every individual. The value of the model comes from knowing you: what you see through your Ray-Bans, your purchase history, your social graph, and the content you engage with.

There are two very different bets on where the value of intelligence lives. Anthropic is superintelligence in the cloud. Meta is superintelligence for you.

Ironically, I think both can win. The most capable model and the most useful model are not always the same thing. Context is the moat that benchmarks don't measure.

[Eric Landau @EricEncord]

There is a certain irony in Anthropic, a company at the forefront of commoditising code, now facing a leak of its own code. If this had surfaced 12 hours later, it would have been a perfect April Fools joke.

Instead it serves as an accidental demonstration of a larger point that code is no longer a company’s moat. Neither really are the models, which are rapidly depreciating assets.

Anthropic’s moat is its data, its compute infrastructure, its investor and customer relationships, its talent, and the context embedded in how it builds and deploys systems. Value is no longer in the artifact itself, but in the system that produces and improves it.

Leaks don’t really break that. If anything, they reinforce it.

[Eric Landau @EricEncord]

Following our recent London office opening, it was an honour to sit down with the UK's Minister for AI, @KanishkaNarayan MP, to talk about the importance of data and what that really means for the UK's position in the AI ecosystem.

For us, the conversation isn't abstract. Most people don't know that without the UK Biobank dataset, one of the world's largest medical research datasets, Encord likely wouldn't have ever existed. @ulrikstighansen used the dataset in his work at Imperial and gained a number of insights from that work which he would later bring to the founding of @encord_team.

Data should be thought of as a national asset for the UK, one which gives Britain an advantage in AI. Glad to see that the people shaping policy are recognising this.

[Eric Landau @EricEncord]

We were very honoured to welcome Britain’s Minister for AI, @KanishkaNarayan MP, to commemorate the opening of our brand new London office!

We’re excited about this next chapter as we continue to scale here in London. From the very beginning, @ulrikstighansen and I believed the UK was one of the best places in the world to build and grow a company due to the exceptional talent shaped by world-class universities, strong institutions, and a globally diverse workforce.

This opening ceremony was quite a moment as I remember back to our first office, a single white room that could hardly hold a handful of people. Now we have close to 40 nationalities represented in our London office alone. That's nearly one fourth of the world!

A huge thank you to Kanishka for joining us, and to every person who has helped make @encord_team into what it is today.

[Eric Landau @EricEncord]

Read the @WSJ's article here: https://t.co/cOwxo3RtZW

[Eric Landau @EricEncord]

Thrilled to be featured in the @WSJ yesterday in their coverage of the surge in physical AI investment.

When Ulrik and I started @encord_team, this wasn't a category many were paying attention to. Consumer humanoid robots were a distant promise, and the idea that multimodal data infrastructure would be a priority for the world's most advanced AI teams seemed ambitious.

Now it’s a cover story.

Last year I noted that physical AI hadn't had its ChatGPT moment yet. The WSJ’s piece is proof that its moment is finally arriving. From the article, physical AI investment in 2026 is on pace to nearly double last year's. As the data supply chain to support it is being built, the volume stored on our platform has grown from 1 petabyte to 5 in less than 12 months.

We raised our Series C to support the data infrastructure for the teams at the center of this shift. Glad to see this attention coming as AI is brought to the physical world.

[Eric Landau @EricEncord]

In the wake of @encord_team's Series C, @ulrikstighansen and I appreciated the invite to @10DowningStreet to discuss the current state of AI and how the UK government can help foster the domestic startup ecosystem. We had a great session and are very excited about the progress being made in the UK tech environment.

Thank you to James Carroll for hosting us and Dom Hallas for the support!