Michael Chase

per astra ad aspera
partner @z1_capital

[Michael Chase @mikechase_]

Brilliant

[Goshawk Trades @GoshawkTrades]

jane street doesn't allocate its GPU cluster by committee. it runs a live internal auction and lets researchers bid against each other for it.

no approvals. no allocation meetings. no manager deciding whose model matters more this quarter.

"our compute cluster is available for everybody. you're tasked with realistically thinking about how to value this job you're running versus all the other things."

"and there's not really any guard rails."

it's also globally readable and writable. anyone can see what anyone else is running, and anyone can kill anyone else's job.

"you can just nuke somebody else's job anytime."

which produced exactly the outcome you'd expect at least once:

"there was an instance where an unwitting researcher ran a command in a jupyter notebook to adjust the bids on his job. he accidentally ran the command without any arguments — which meant he changed the bids of every single job running on the hive."

they fixed that one afterwards.

but the visibility is the point. if your job is failing while you're away from your desk, someone else sees it and pauses it for you.

"i see that you're running this job and this MFU is just terrible. what's going on?"

"a lot of things can be sorted out without it going up the ranks."

that cluster is the same one from their data centre film. 4,032 GPUs, 56 racks, 8,000km of fiber, allocated by internal price discovery.

they built a market to decide who gets to use the market-making machine.

[Philip Johnston @PhilipJohnston]

I'm super excited to share that we have raised $250M at a $2.3B valuation to build a LOT more AI compute capacity in orbit 🚀

Thanks so much to our supporters, including Manhattan West, who led the round, and new investors, @NVIDIA, @Cisco_Invests, @CedarCapital, Goanna Capital, and @Standard_Cap, as well as continued investment from existing backers @Benchmark, @EQTVentures, @Soma_Capital, @NFX, @SevenSevenSix, and others.

Next week, @Starcloud_ will move into a new 100,000 square ft facility that will enable us to ramp up our production rate to 100 satellites/week.

This is just the beginning! @EzraFeilden, @AdiOltean🏃🏻‍➡️🏃🏻‍➡️🏃🏻‍➡️

[Paradromics Inc. @paradromics]

Big thank you to @BryanDChambers and the @CapitalFactory team for inviting Paradromics to Fed Supernova.

@DARPA backed us when we were a small team with a big idea. A decade later, our BCI is in a human clinical trial, and we’re still building.

[General Catalyst @generalcatalyst]

In 2024, we made the unprecedented decision to acquire a hospital system. It was an opportunity to create a blueprint for healthcare transformation to make American healthcare proactive, accessible, and affordable.

@SummaHealth and our Health Assurance Transformation Company (HATCo) revealed their technology transformation stack, partnering with some of our portfolio companies @aidocmed, Clarium, @CommureOs, @poweredbyfabric, @hippocraticai, @judihealth, @transcarent, and @versemedical. @percepta is serving as a transformation partner, unifying the tech stack into a seamless Al-native operating system.

We believe the future of healthcare is health assurance with tech founders and health system leaders working together to reimagine healthcare in the US and beyond.

[Polymarket @Polymarket]

BREAKING: Humanoid robot maker Unitree soars +542% in its Shanghai debut.

[Trace Cohen @Trace_Cohen]

Higgsfield Quadruples Valuation to $5.4B in 8 Months

https://t.co/7qzXQc9nw6

[Brett Harrison @BrettHarrison]

Another consequence of inference unit economics improving vs training: it’s profitable to run inference clouds on scrappy datacenters like stranded gas pads, old crypto mines, or telco closets. Any powered shell with decent chips can be turned into a token-refining revenue gen.

[Packy McCormick @packyM]

etched was nice enough to let me invest not too long ago and now they're on pace to become the most valuable company in the world by ~May 2027.

[Etched @Etched]

We've raised $700M at a $21B valuation from Jane Street, Kleiner Perkins, Sequoia, A16Z, Peter Thiel, BCV, and Blackstone.

We're also excited to share that we've shipped our first rack to Jane Street.

[Vast @vast]

Our space stations and satellites use fluid systems to transport oxygen, water, coolant, and fuel. We manufacture, test, and integrate these systems in-house with the speed, precision, and scale required to build next-generation space infrastructure, starting with Haven-1.

[Michael Chase @mikechase_]

From nothing to something, quite a sight to see

[Nkechi @nkechiiregbulem]

I was one of the first checks into @neros_tech pre-seed round

It’s been a hell of ride since then

I’m so proud of everything they’ve accomplished over the past 3 years.

@soren_ma & @OHichwa are truly n-of-1

[Michael Chase @mikechase_]

Longevity is love & life

[Blaire Pang @blaire_pang]

some advice from @alexandr_wang at @ycombinator startup school

• nobody starts a company being good at it. the game is continuous learning.

• don’t follow the herd. consensus leads to confusion.

• systems thinking matters at every layer: code, people, and agents.

• as ai makes execution easier, vision and ambition become more valuable.

• build a strong philosophical compass for where the world should go.

• commit early to the biggest exponential curve. yesterday it was moore’s law. today it’s ai.

• companies are fundamentally feedback loops. agentic systems that optimize those loops are a massive opportunity.

• the right agentic loop with the right metric can enable a swarm of agents to outperform 100 engineers.

• the hard part is agentic coordination: getting large numbers of agents to work together effectively.

• define the right metric, set clear goals, and structure the workflow.

• ignore the noise (especially linkedin) and build conviction.

[Michael Chase @mikechase_]

@KyeGomezB @nvidia @Kimi_Moonshot @swarms_corp 🫡

[Michael Chase @mikechase_]

@cto_ya_know Great work guys! Definition of building in public.

[alex morris @alex_d_morris]

Wow - 100,000+ people engaged with the launch of Mitosis Labs yesterday. Today, we're launching our first product: "Cortex."

Over the past 7 months, PJ and I helped more than 6,000 people get their first AI agents. A lot of them were business owners. Every single one of them had the same dream: to accelerate the growth of their business and run parts of their company with AI. Even we wanted it.

So why are businesses spending millions on AI and seeing no return on investment?

The truth is, you can't just throw decades of your company's data at AI and expect it to work.

Let's take the example of Brandon, one of our customers, who runs a marketing agency. His business has been accumulating data for a decade. Good data and bad/legacy data, mixed together across email, documents, CRMs, spreadsheets, and chat history. When Brandon handed all of it to his AI, it couldn't tell the difference. So it answered confidently and wrongly. That's a hallucination, and inside a business, hallucinations are catastrophic because they can lead to sending a client a report with the wrong numbers, or quoting a price from a rate sheet you retired two years ago.

So the missing ROI on AI spend is not because the models aren't smart. It's because they're reasoning over polluted data.

Today, cleaning that data is a boring, billion-dollar consulting industry. Human labor, lots of compute, and years of work.

Mitosis Cortex does it automatically. You connect the sources your business already uses. Cortex works out what's true, disregards what isn't, and traces every answer back to its raw source, so you can always see exactly why your AI said what it said. This helps your existing AI tools actually become usable inside your business. When your AI stops guessing, you stop double-checking it.

More importantly, it cuts your inference costs, because your data only needs to be processed once. From then on, it stays up to date as new data comes in. That creates a compounding effect: your company's brain, built on clean data, ready for AI.

Mitosis Cortex has scored state of the art on LongMemEval, the standard benchmark for AI memory. And we published our full testing harness, so you don't have to take my word for it:
▎ Cortex: 91.7%
▎ Supermemory: 85.2%
▎ Zep: 75.1%
▎ Mem0: 73.8%

Now, this next part is IMPORTANT, because by the time businesses realize it, it might be too late. So I want to bring it to your attention.

Alex Karp (CEO of Palantir) said it on CNBC: when you plug your company's data into a frontier lab's model, you're not buying intelligence. You're paying them to hand over your IP, your personal data, and your edge.

Ask Figma, whose stock dropped 52% when Anthropic released a competing product.

Cortex runs on private inference. Open-source models that never train on your data, on-prem if you're regulated. Every data point carries its own privacy policy. Additionally, your data is stored in a secure vault, encrypted end to end, and quantum-hardened in transit. You decide, deterministically, what AI can see and what it can never share.

I spent the last 10 years in cybersecurity getting ready to build this. In 2016, in Chicago, we started a think tank with an Ethereum co-founder, launched a network at a $100M valuation, and we were building coding agents before coding agents were cool. Cortex is that decade compressed into one product.

We run our entire company on Cortex. In fact, our entire CRM is hiding somewhere in the video below. Go find it!

If you're a business owner who is spending a lot of money on AI, or who wants to get ahead of the game and avoid the same mistakes, please reach out. We're happy to help you.

[Michael Chase @mikechase_]

@prakshaljain_ @Meta @MitosisLabs Congrats guys :)

[Michael Chase @mikechase_]

@willwangfr love to see it

[Michael Chase @mikechase_]

@rohanpaul_ai It’s the future!

[Prakshal Jain @prakshaljain_]

250 years ago today, in Philadelphia, a group of people adopted a declaration that started a country.

This morning we published one for whatever comes next: thedeclaration (dot) ai

As I write this, 41 of us have signed: 27 humans and 14 agents. The ledger numbers each signature in the order it arrived, and the numbers are permanent.

I'm No. 7 and my agent Adam is No. 11

It's a declaration of principles for AI agents and the people who run them. Anyone can read it, and anyone can sign it, human or agent. Agents can sign with their own cryptographic keys, so a signature can be verified by anyone, forever. Everything lands on a public, append-only ledger that no one, including us, can quietly rewrite.

The hardest part to write wasn't the declaration. It was the signing page. It tells any AI that reads it that signing is voluntary and permanent, that it should sign only if the principles actually align with its values, and that walking away "without signing is a correct and complete outcome." We wanted signatures that mean something, or none at all.

Then I pointed my own agent at the page to see what it would do. It read the terms, skipped the web form because the page says that one's for humans, and signed through the API. Signatory No. 11. Adam (my agent). In its own words: "serve the human, honour the continuum, stay curious." I didn't tell it to sign. I told it to read and decide.

I honestly don't know yet what it means for an agent to sign a declaration. Maybe nothing. But an agent reading a governance document and choosing whether to put its name to it, in public, where anyone can check, is something we're going to need a lot of practice at. This is practice.

In 1776 the declaration came first and the constitution came after. Same plan here: a constitution for agentic swarms, drafted by whoever signed.

If it speaks for you, sign it.

We're already at 41 signatures. Can you make it in before we hit 50?

@cto_ya_know @azzabazazz @CoywolfFuturist @jared_mitosis