This account is now home to Sorites Research, founded by Drew Clement.
Our first thesis: The Agent Multiplication Effect. What happens to compute demand when agents create work for other agents?
Evidence, counterarguments and a dated forecast:
https://t.co/ihSyMJMSa9
@sk_2496 That's the exact gap. Every IP clause I've read assumes the vendor's output is the asset and the customer's input is just fuel. Nobody writes down who owns the fuel until the fuel turns out to be worth more than the engine.
New note on Kraken Robotics (PNG): a real technical edge in compact sonar, a big acquisition, and a data-moat story the public documents don't support.
Traded it before, no position today, no company contact. Not advice.
https://t.co/5kUaxWy0tc
Anthropic reportedly signed a 20-year lease for 95 MW of Canadian data-centre capacity in Nova Scotia.
AI infrastructure is moving from announcements to commitments.
Now comes the hard part: grid connections, transformers, switchgear and construction.
Follow the bottlenecks.
@sk_2496 Good question, and the honest answer is that nothing public shows Kraken owns it. Its published service terms say new IP created while performing services is Kraken's, with confidentiality obligations, but they don't expressly give it raw customer survey data. notes in section 6
Transformer manufacturing expansion is creating demand for highly qualified cellulose insulation materials. Canada's softwood forestry sector possesses potentially relevant feedstock, but the investable opportunity may reside in specialty processing and qualification not timber.
@StableBread Turing was at the top of my list too. A little more difficult of a deep dive as Randy is a lot more connected in silicon valley than the usual canadian microcap CEO to say the least....
@NRGBloom Exactly. Everyone models the electrons, nobody models the queue. The grid study is the real lead time on every powered-land deal I've looked at, and signed behind-the-meter generation is the only honest bypass. How far out is the study queue stretching from what you're seeing?
AI infrastructure is moving from power demand forecasts to signed generation contracts.
Enerflex ($EFX.TO) just announced another 1+ GW behind-the-meter power award, bringing contracted capacity above 1.75 GW.
Data centres aren't waiting for the grid.
@buildcanada Just finished a full proposal for a Canadian Diskos — Norwegian-style mandatory outcome-data capture on major projects. Every mine/corridor/energy project leaves Canada two assets: the infrastructure, and the record of how it was built. The standard is open. Canada needs this. 🇨🇦
The New Backbone of Global Power Grids: Energy Storage ✅ 🌞
Read the full article here 👉 hhttps://privatebank.jpmorgan.com/eur/en/insights/markets-and-investing/the-new-backbone-of-global-power-grids-energy-storage
$WEB $WEGYF #solarenergy#solar
@steep_slopes Long $WEB.V from $1.22, watched it fade to the $.90s on basically no volume, still here. The math: ~C$39M pro-forma cash vs ~C$28M market cap once Red Willow closes. The market prices the whole pipeline at $0 and the cash at a discount — I think the market can't do division.
I am turning MAX BULLISH right now. Just like a river boat gambler holding his last chips I’m looking at the landscape and thinking fuck man we are in the fast take off stage right now.
I want to put it all max levered long on the high beta names and walk off into the orange glow of the sun. My bullishness has absolutely nothing to do with the math problems that are being solved most of them don’t matter that much.
But it’s more the realization that every AI lab just had. They all woke up and said wait a minute what are we doing selling $200 a month subscriptions to idiots who are making slop apps and nonsense substack articles when we can just subsidize a few super geniuses by giving them real compute to work on an important problem.
No one really cares about navier stokes besides some CFD simulation cycles. But what if we put these compute resources on real valuable problems? That opens up a whole new world. The bull case for AI has always been to me discovering new drugs or even verifying they work/don’t work reliably… I was thinking way way wayyyy too small.
There are hundreds of problems in engineering that if you got the experts in the room with real compute and even if they made a marginal improvement it would be worth hundreds of billions to the economy. Imagine we can build a steep slope device at 0.3V that’s worth like several generations of lithography nodes, or we can design a sub 100 femtojoul/bit optical IO and cut datacenter power by 40%, or even something as simple as more energy efficient molecular separation to replace distillation which is like 15% of all industrial energy use.
This is the real shit guys. The labs are realizing quickly this is the REAL frontier this is the final land grab. Open source can never compete here because they don’t have the capital and resources this plays right into the labs hands. They can’t give everyone a 10,000 agent swarm but they definitely can give it to Exxon mobile and charge them $50M dollars for it if it means they find more oil or Dow Chemical to create a new kind of super glue or to Moderna to computationally create different mRNA therapies… the list goes on and on.
A big reason why I never cared much for AI is despite all the normies going googoo Gaga over it is that literally they don’t have any clue what to do with it. Like if you were mediocre before AI you are mediocre after it, nothing changed u just got more skills that you don’t know how to use and you have no imagination or intuition. It’s the same reason why education is a waste on the majority of the population because let’s be real most of you aren’t going to be deriving differential equations or using epistemological concepts on your day job.
But you give this kinda compute and unfettered AI in the hands of people who are world class. They will cook. It’s the reason why Deepmind has a Nobel prize and no other lab does because deepmind actually hired or worked with the top biochemists and biophysicists to develop alphafold.
AI alone isn’t going to discover anything. Don’t fool yourself and grow up already if you still think AI is going to just figure out large scale nuclear fusion on its own then you are simply lost in the sauce at this point and are beyond saving. The pragmatic answer has always been use the AI to automate the busy work and keep the human experts for the actually thoughtfulness and intuition.
I think the AI labs will wake up now and realize selling coding tokens and image models to normies to make Disney characters isn’t the best business in the long run. Actually using the compute for real serious innovation is and it’s really easy to monetize this upfront.
I expect AI labs to stop looking like API companies and start looking like real research labs now. Thank god.