Lawrence Lundy-Bryan
@LawrenceLundy
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https://t.co/e5BLRrH50q. Just going hard and trying to get us out of this mess.
Lewes
Joined December 2020
1/11 🚀Launching State of the Future: The World's First Deep Tech Tracker. Technologies combine & reinforce in novel ways. We are exploring the intersections. https://t.co/Nkdb1kgt1n
#DeepTech #StateoftheFuture @lunar_vc
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The implications of this thread for biotech drug dev are enormous. Currently US market generates ~75% of the profit of global biopharma sector. If 1.3bn+ Chinese are truly consuming at same levels of Americans by ~2040, we are about 15 years away from: - China joining US
Well, Americans (and the Japanese and Western Europeans) are still richer on average than the Chinese. But the gap is relatively mild if you compare Chinese living standards to those of very poor countries in Africa and Asia. For example, Chinese life expectancy is 1.3 years
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Set the target, 2 weeks from first call to money in founder account. Signal government money means fast money
⚠️ this also applies to SovAI, govt's new strategic AI investor, which will fail if: a) it just becomes a DSIT policy unit b) it's reliant on a slow-moving BBB c) it can't appoint a respected investor to lead it as @LawrenceLundy says: build for *velocity*
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Big tech is an unhelpful moniker. All capex is industrial build out. There are modern industrialists. Neo-industrialists?
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this doesn't really hit as hard on X because most the energy sector left the platform a while ago
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great piece by @LawrenceLundy on the state of affairs in market adoption of privacy tech like FHE, MPC etc. "It’s a market failure driven by risk aversion and regulation creating a catch-22. 1/ Organisations with sensitive data (NHS trusts, government departments, financial
5/ Market Failure 1: Privacy-Preserving AI. We have the tools, MPC, ZKP, FL, FHE. But we don't use them. Risk aversion and regulation create a catch-22 where no one wants to go first.
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12/ This only works if the institution is designed for speed from day one. Everything else flows from that foundational choice. Full essay:
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11/ Success in 18 months: 80-100 decisions with two-week cycles, 15-20 clear failures showing appropriate risk-taking, privacy-preserving AI deployed in two high-stakes domains, 30-40 teams funded on defense/infrastructure/healthcare.
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10/ Privacy-preserving AI enables data collection at scales others cannot match. Early-stage hard-tech builds capabilities where innovation happens but can't access capital early enough to go fast enough. Both require velocity because leadership comes from being first.
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9/ This creates a funding gap for work too applied for research councils but too early for venture. Novel architectures, new hardware for niche applications, compound semi, new lithography, etc, etc
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8/ Market Failure 2: Early-Stage Hard-Tech AI. VCs funded early-stage AI research five years ago. Not today. The venture market evolved into late-stage growth investing. They fund hot deals with momentum, not genuinely uncertain technical research.
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7/ If the UK demonstrates privacy-preserving tech working at population scale in healthcare, we set the global standard. Other democracies adopt UK frameworks because we proved comprehensive data and strong privacy can coexist.
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6/ The UK is uniquely positioned. UK Biobank has genetic data on 500k participants. NHS has 70M people cradle to grave. Met Office has century-spanning climate data. These datasets are underutilized because organizations are terrified of privacy violations.
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5/ Market Failure 1: Privacy-Preserving AI. We have the tools, MPC, ZKP, FL, FHE. But we don't use them. Risk aversion and regulation create a catch-22 where no one wants to go first.
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4/ The UK needs an institution that makes decisions in 2 weeks and deploys capital in 2-4 weeks. Not about efficiency. About whether investments arrive in time to win fast-moving markets.
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3/ The theory of failure isn't investing in the wrong things. It's being too slow to invest in the right things and missing the window where those investments create value.
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2/ The UK will not compete on compute scale. Traditional funding takes 18 months. AI moves on 3-6 month cycles. By the time traditional mechanisms deploy capital, it's already too late.
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1/ OpenAI bought 6GW of compute with AMD, matching the UK's entire national AI infrastructure ambition through 2030. A single American company is deploying more capital into AI than the UK's entire annual R&D budget.
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the technocapital hyperobject at the end of time begins to pull itself together
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It’s interesting how much momentum seems to be forming around this view - that electrification, not renewables, should be the primary focus for the climate movement - across a political spectrum that is otherwise highly fragmented.
I advised Boris to expand offshore wind – but we now need to pause our renewables rollout and scrap the 2030 clean power target. Ed Miliband is wrong. The greatest threat to climate action is not right wing billionaires buying up TV stations. It is expensive electricity. 🧵
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@LawrenceLundy underrated angle here is that proof of humanity going to be increasingly important in a world/internet/economy dominated by agents
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