j_shi
Rough math plugging in public #s and comments here:
- All stock deal at Aug 2021 val of 38B (1B ARR)
- Assume rev doubled to 2B (which may even be aggressive)
- SAAS multiples are down 6x since Aug 2021
- 38B x 2 / 6 = $12.7B
- 12.7B / 38B * 1.3B = 434M = effective price
- Assume 100M to pref stock
--> Comes out to 334M, with a chunk of that (1/3? 1/4?) potentially subject to earn out
Similar offline risk goes for all tech: navigation, generating energy, finding food & water.
And as others have noted, like other personal tools, ai will become more portable and efficient (see progress on self hosted, minimal, efficiently trained models like Vicuna that are 92% parity with OpenAI fancy model)
https://lmsys.org/blog/2023-03-30-vicuna/
https://www.semianalysis.com/p/google-we-have-no-moat-and-ne...
While consumers are happy to get their data mined to avoid paying, businesses are the opposite: willing to pay a lot to avoid feeding data to MSFT/GOOG/META.
They may give assurances on data protection (even here GitHub copilot TOS has sketchy language around saving down derived data), but can’t get around fundamental problem that their products need user interactions to work well.
So it seems with BigTechLLM there’s inherent tension between product competitiveness and data privacy, which makes them incompatible with enterprise.
Biz ideas along these lines: - Help enterprises set up, train, maintain own customized LLMs - Security, compliance, monitoring tools - Help AI startups get compliant with enterprise security - Fine tuning service
Hong Kong shuts most China crossings over virus as medics strike
Where the valuation came down to earth was when public investors evaluated We as an incrementally better office rental company, and didn't buy the idea of We as creating and monetizing a religion.
A few (unsubstantiated) guesses at reasons to counter:
1 - Medium risk medium reward opportunities exist (a currently unprofitable but otherwise promising startup addressing a 25m niche can't get bank debt or venture funding)
2 - Could decrease risk holding reward (avg. multiple of investment) constant by having small funds with managers that have deep knowledge of particular niche deploy smaller checks in markets they are better at evaluating (v. large fund managers needing to cast net wider than their "lane")
3 - Size expectation can be correlated with risk. Can decrease risk holding reward (avg multiple of investment) constant by just having smaller funds writing smaller checks for smaller companies that be happy with smaller exits or alt. upside capture (v. forcing companies that could work with small exits into chasing big inflexible exits). Sure no 100x-ers but theoretically could see higher blended fund returns
4 - Opportunities generally continuous on risk and reward calling for equally diverse approaches to capitalization
Curious - to extent you're willing to share - what dynamics are like for LPs (assuming raising outside). Since median vc fund return is barely 1x, and traditional VCs sometimes blow up otherwise good niche companies by forcing them to go big or bust, targeting 3-5x returns with way faster liquidity for investors a super interesting alternative.
And if the niche market turns out to be a massive market, can still go in with eyes wide open!
That said one guess on a trigger for the most recent sell off was that Bitcoin Cash, a fork of "reference" Bitcoin, forked in a bigly hostile way, resulting in two new Bitcoin Cash chains (Bitcoin Cash ABC and Bitcoin Cash SV - for satoshi vision lol) each now with its hash power majority controlled by one group e.g. highly centralized. The market is confronting the possibility that proof of work -- the most widely used consensus mechanism -- is way more centralized than it thought, and way more subject to value destruction from a tiny % of people.
An SF-based group Measure Water is fighting for a solution to the problem, starting with getting schools to correctly examine their water.
I'm friends with the founder and she'd welcome anyone interested in helping to reach out at [email protected]
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