Rob

i like golf and connecting dots @voltcapital | prev @Delphi_Digital

[Rob @rsarrow]

https://t.co/hvZ9ERavBr

[Skymapper @Skymapperspace]

Our @Kickstarter is now LIVE.

Meteors. Satellites. Drones. Aircraft. Auroras. UAP.

SkySphere combines edge AI, trusted timing systems, and real-time detection software to transform raw sky imagery into actionable, trustworthy sky intelligence.

Observe. Replay. Detect. Contribute.

Built for wonder. Designed for real-world awareness.

Back the future of continuous sky observation 👇
https://t.co/bDKrt5E41b

[Rob @rsarrow]

@lzminsky @Kalshi hedge

[Rob @rsarrow]

new markets, new risk transfer tools

1° - compute cost becomes something enterprises need to price, not just pay
2° - buyers hedge future inference demand instead of eating usage volatility directly
3° - anera becomes the venue where compute costs, agent demand & margins get priced/hedged/financialized

[Rob @rsarrow]

big congrats to @intheanera. as value moves downstream of inference, the clearing layer becomes become the control point.

[Rob @rsarrow]

@Melt_Dem @HadickM @Polymarket @FalconXGlobal @OrnnExchange weird way to spell @intheanera

[Rob @rsarrow]

big congrats to @intheanera. as value moves downstream of inference, the clearing layer becomes become the control point.

[Polymarket @Polymarket]

We're excited to announce Polymarket has facilitated the first ever on-chain, institutional block trade in the prediction market space.

Institutions using Polymarket to hedge GPU compute exposure at scale give a glimpse into both the future & the promise of prediction markets.

[Rob @rsarrow]

https://t.co/QkwoNMG3Jz

[Rob @rsarrow]

been thinking about Fringe Untapped Data at @VoltCapital for a long time now

FUD is not just about collecting data. that makes you a broker

it is about designing crypto economic systems that incentivize the right collection what our AI overlords cant

- reward the edge
- verify the source
- build the loop

FUD lives where there are no APIs (eg robot arms, off grid sensors, localized human interactions). This is not public data. It is invisible until someone designs a system that makes it economically worth surfacing.

we have backed teams doing this in health, robotics and space and were looking for more in energy and defense.

moats are built on the edge

[Rob @rsarrow]

fringe untapped data is long overdue for a rebrand

[shift @joinshiftX]

Today, we're launching shift. We're starting by cleaning your apartment in New York City, for free.

Here's how it works. Book a shift cleaning. A vetted shift operator comes to your home wearing one of our devices. They clean. They leave. You pay nothing.

In exchange, we record the cleaning. Robotics is being built on data about how people do daily tasks, and the value of that recording is what funds the service. Anything personal in it is anonymized before the recording is processed.

By now, you have heard about the shift to AI more times than you can count. About the shift toward you, the part where you actually feel it, you have heard almost nothing. Shift is what starts to make it concrete, in specific cities, with specific services.

Today, cleaning in New York. Soon, handymen, repairs, and errands across the globe. And this is just one side of shift, with more on the way.

Comment “shift” and we’ll send you an early access link.

[Rob @rsarrow]

@joinshiftX "shift"

[Rob @rsarrow]

@barratt_dewey bubble world champion kyle kuzma *

[Rob @rsarrow]

vivian darkbloom coded

[Ash @ahboyash]

Project Darkbloom: Turning Idle Macs Into AI Infrastructure

Every time an AI tool is used, the request travels through multiple layers of infrastructure before reaching the actual hardware doing the work.

The flow usually goes across different layers of Data centers, cooling systems, GPU hardware and layers of margin → All baked into what you're paying.

The @eigenlabs team calls this the Inference Tax.

Darkbloom is their research initiative to address it.

The premise: 100M+ Apple Silicon Macs already exist, already paid for, sitting idle most of the day. What if that compute could be organized into a usable inference network, with real privacy guarantees and better economics?

- - - - -
Why Apple Silicon
Apple Silicon isn't just abundant, it is also technically well-suited for inference in ways that matter:
• Unified memory: CPU and GPU share the same pool, eliminating discrete GPU bottlenecks
• Model efficiency: Apple Silicon only processes the parts of a model actively needed per request, rather than the whole thing → Larger models run faster and cheaper
• Power efficiency: ~30W to run a 60B model, versus multiples of that on data center GPUs
• Marginal cost to a Mac owner: Primarily electricity, since hardware is already bought

- - - - -
The Hard Part: Making It Trustworthy
One basic question is that If the prompt runs on a stranger's Mac, what stops them from reading it?

Darkbloom's answer is to make snooping architecturally impossible, not just contractually prohibited:
• Debuggers: Blocked at kernel level
• Memory reads: Denied via Hardened Runtime
• Binary tampering: Breaks code signature and then macOS refuses to run it
• Nodes will be re-verified via 4-layer attestation every 5 minutes → Secure Enclave, Apple MDM, Apple-signed device certificates, continuous challenge-response

The only way to break these protections is to physically reboot the machine, which immediately kills the process and wipes everything. Apple uses the same approach on their own Private Cloud Compute infrastructure.

- - - - -
What This Means for Eigen
Darkbloom will not act as a standalone product, but as a proof of concept and signal about where Eigen is heading in the AI infrastructure stack.

EigenLayer's core thesis has always been restoring trust to decentralized systems.

Darkbloom extends that into AI compute, making inference verifiable, not just available. If it proves that 3rd party consumer hardware can be cryptographically trusted for sensitive workloads, it opens the door to a new class of decentralized AI infrastructure that doesn't rely on trusting a cloud provider or data center operator.

This marks the beginning of Eigen playing within the privacy-as-infrastructure market.

- - - - -
Some Thoughts
A few things worth keeping in mind as we went through the Darkbloom research paper:

• The coordinator remains a trusted central layer for now; Team is transparent about this, but it's not eliminated yet
• Security model currently assumes no unpatched macOS kernel vulnerabilities
• Network traffic patterns can still reveal rough details about your request (e.g., how long it was, how complex) even if the content itself is hidden

The real test is whether the privacy guarantees hold as more nodes join the network and whether people actually trust it enough to run sensitive workloads through it without incentives.

Keyword: without incentives

The biggest hurdle is trust; Getting someone comfortable enough to run their data and prompts through a stranger's machine. It's a hard sell and very few projects are even attempting to solve it seriously.

Despite all that, the maths seem to work out quite nicely out when the team at @mementoresearch sized it out → Check out attached pages

Disclosure: Project Darkbloom is a research initiative by Eigen Labs: Access here https://t.co/uvvyo9Yy33 + I am a $EIGEN holder

[Rob @rsarrow]

@DegenerateNews @BounceTech @phantom @HyperliquidX @DefiLlama huge @BounceTech

[DEGEN NEWS @DegenerateNews]

STATS: @BounceTech FLIPS @phantom IN 7-DAY REVENUE ON @HyperliquidX L1

$268,399 VS. $247,688

- PER @DefiLlama DATA

SOURCE: https://t.co/WmxrRnIQov

[Rob @rsarrow]

high fructose corn syrup era

1° - labs move to usage aligned / abstract billable inference

2° - enterprises 'sugar levels' so high, growing dependence on medicine

3° - winners not just labs but the infra layer selling insulin for it

deploying to GLP1 equivalents

[Citrini @citrini]

It’s already happening.

[avi @avizurlo]

https://t.co/8aO7KXyKpe

[Rob @rsarrow]

@mrinko meatmobiles

[Rob @rsarrow]

@sui414 @0xMadSped

[Rob @rsarrow]

access -> context -> coordination

[Rob @rsarrow]

build companies, not apps

[Evan Solomon @Evanzsolomon]

The issue with most prediction market startups is that they’re building features, not apps

[Rob @rsarrow]

@antavedissian imo stablecoins are the interface, but the bigger point is selection pressure. in meat space feedback loops are slower, error tolerance lower and coordination cost compound.

https://t.co/0v2CeuLt1A

[Rob @rsarrow]

do agents get sunday scaries checking their micropayment balance?

[Rob @rsarrow]

long synthetic utilities:

1° - overvalue narrative / undervalue contracts, collateral, power, utilization and cost

2° - edge shifts from 'who has GPUs' to 'who can turn GPUs into bankable, recurring, credit worthy capacity' (@USDai_Official)

3° - asset class becomes new synthetic utility layer for intelligence, where capacity is the power plan / ai demand is the grid

[Anjney Midha @AnjneyMidha]

Compute isn’t venture. It’s infra with venture demand curves and utility contract structures

The right comp is 90s era independent power producers, except the offtakers have stronger balance sheets and steeper demand than anything in energy history

Most investors will miss it