2023 Elad Gil predictions
startup macro, LLMs, defense-tech
Macro on startups
“Startups are an act of desperation” - desperation went out of the ecosystem over the last few years with people being very status/money focused. now people are building for other reasons including impact/products/career acceleration
2022 was the warm-up to bad times… 2023 is the bad times - we’ll see mid-late stage, layoffs, blow-ups, down-rounds, shutdowns
ChatGPT demonstrates potential of LLM, but still early
chatGPT is a key moment demonstrating the potential of LLM models
who develops/commercializes this? maybe OpenAI, Google or someone new
competition creates the need to reexamine assumptions about safety and reputation risks
virtual sssistants (like adept.ai) understand language and take action
On AI models
AI open vs closed - the massive models today largely closed (e.g. Chinchilla, GPT-3.5) while the image-gen models more open (Stable Diffusion)
image models are easier from a cost/quality-expectation-threshold
higher threshold of quality required on language-gen than image gen
2x2: image vs. language, big vs. small model
Costs to train LLM models today
costs to train a GPT-4 competitor from scratch might be tens of millions to low hundreds of millions of dollars today depending on baselines starting from
capital scale will hit billions shortly, limited window of time for startups to enter LLMs
does the industry structure look more like the cloud world with multiple competitors or more like semiconductor world where just TSMC won?
Space and Defense
SpaceX Starlink
Anduril becomes the default defense-tech startup
defense tech
rise of drones
rise of machine learning/machine vision
cybersecurity
why defense tech hasn’t worked well before
no “why now”
defense tech starts with a point product as a subcontractor
need a lot of capital
business model of cost-plus versus - Anduril sells gross margin model
execution speed of deal-closing