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This blog is about Reducing Deeptech Risk with Shared Infra & Alliance. A concrete plan to solve bottlenecks without waiting for larger structural changes.
It hits concrete challenges that founders, VCs, and enterprises face in AI. We cover proceedings from 2nd roundtable of Innovators & Industry Deeptech AI Alliance which is gearing to be in league of pvt AI labs across China, EU, US, UK.
We also cover, the sustainable model by reducing cost, Risk & access to shared infra(Section 8 non-profit) & for-profit with Tech transfer to Enterprises, VCs, Startups along with Revenue engine.
Momentum in Deeptech that can’t be ignored – AI, and RDI (Research, Development & Innovation) & Indian Deeptech Alliance by VCs have started building momentum for Deeptech, new funds are being formed, startups are getting ready, govt & international mobilization of funds by pvt players are getting ready, new products are getting launched.
Core challenges – not visible but harsh reality in numbers – But in reality most startups lack the balance sheet to fund long-gestation research, dataset, infra.
Most VC funds are not large enough to absorb concentrated Deeptech bets. In fact a reality check – Only 45-75 VCs led a round > $500k in last 3 years as per Vaayu’s study.
It’s a general perception & reality that most VCs end up investing like P/E in India. How will they agree to bsuiness models which has capital efficiency of 0.02 to 0.1 at max during initial stages. (Reference Anthropic, Sarvam revenue vs funds invested.
Net result is, founders & VCs invest in either what looks like Deeptech or a crowded market but what seems Deeptech. ( Eg Defense always may look like Deeptech.)
If a Deeptech company can create early GTM motion & Capital efficiency ast seed stage – I would rather question whether they have even understood what a Deeptech is.
Reducing Deeptech Risk, Gestation period
Yet opportunity is too big to ignore by Founders, VCs, Enterprsies.
Focused Research Organization(FRO) with Revenue Engine & examples
An FRO works with a mandate of 3 to 5 years on Research which has marketability but Enterprises or academicians don’t have enough incentives to innovate.
Such orgs, both Profit & non-profit have emerged. Though FRO term itself is pretty unique & new & has gained momentum in RDI fund, EU & US.
As analogy you may consider early version of OpenAI. Closer home AI4Bharat may be termed an FRO.
More examples from around the world – Beijing Academy of Artificial Intelligence (BAAI) in China & Fraunhofer Society in Germany, Italian Institute of Artificial Intelligence for Industry.
Revenue & Engineering led Innovation
The pvt examples include a full fledge org or you may look at Salesforce, SAP have teams building time-series models & Co-pilot. They aren’t as capex intensive as OpenAI or Anthropic.
Put Quantitatively, an FRO may grow a market cap(Pvt value or notional) which can run into 20-50m or grow to 10s of billions USD.
What IIDA & FRO do – Examples of how it reduces Deeptech AI risks
Some examples of topics at IIDA (This is when we have merely started)
JEPA & World Model Based Reasoning
At Vaayu, this is our core topic. So anything even done in IIDA as open research directly aligns with our work. While an FRO allows collaboration in different dimensions.
Not only Vaayu benefits but generally a core technology has multiple usages.
Data set collection & Sustainability, Net Zero Mission & CleanTech
I recently met a founder whose startup provides dataset & labelling to humanoid building company in US. Scale AI was acquired for Meta for $14B for 50% stake.
So there’s already market which is validated. But creating & labelling data for Solar, EV – this shared infra itself is of huge usage.
Token Economics & Enterprise Adoption
Everyone knows the biggest hurdle in Enterprise adoption is the token cost & benchmarking ROI. While two camps are in a tug war. Builders of AI spread narrative of using the max token usage. (Eg NVIDIA, Anthropic, OpenAI).
Second camp is whose business is getting cannabilized – Zoho, Salesforce, SAP, Microsoft. They spread their own narratives.
At FRO we build scientific frameworks, billboards, benchmarking infra for Enterprise adoption.
Game Theoretic Multi Agents & Reasoning
While world is in awe with OpenClau & Claude library, we take it a level further. How will AI Agents negotiate pricing in procurement with multiple vendors & power & demand dynamics?
This can be directly put to use in infra libraries for Multi agent orchesration.
How it solves the Gestation & Capital, Market positioning problem
So, we have to be creative in structure, look at a emerging category of AI Deeptech around the world but still not be in crowded space.
As you can see from topic, these have a market or market formation or category formation is there. Yet these are hard problems to build & it’s the right time for innovaiton to enter in.
With IIDA – We mitigate these risks to commercialize in 3-5 yrs from Lab to market, plus we have partners – startups who have a revenue Engine which is now backed by Focused Applied AI Research & differentiation.
Biggest icing on cake – having an FRO unlocks certain advantages like grants & scope – vast applicability, impact the world.
We aren’t alone; such alliance models have appeared in China, Europe, US. The closest terminology is Focused Research Organization after which IIDA is modelled.
How & Why to be part of IIDA & Assymtric outcomes
Here’s a poll with real reasons why people want to be part of IIDA. I will never underrate anything which serves some need of high IQ people & can compound.
Some more reasons to join include – Identity beyond job & livelihood or a pride symbol to be founding member of IIDA which can make a real change.
You may have goal of wealth generation or research or do cool stuff or make an impact. IIDA targets assymtric outcomes.
If you want more access, happy to connect.
Read about why & what is IIDA & how it plugs into emerging opportunities