4 predictions in AI, AR/VR & consumer hardware for 2024
Saying AR/VR will take off is a lazy prediction, for what it's worth.
At Earthling VC, we invest in next paradigm technology that feels more human— in other words, we’re investing in emerging tech like AI, AR/VR, and robotics that disband the perceived barriers between real and digital worlds.
Sharing with you all 4 market trends — which I shared with our LPs earlier this week — that I expect to see impact these spaces in 2024:
AI software is now a consensus bet— and a better investment for large funds.
There is consensus among the entire industry that AI-enabled software represents a paradigm shift in the human-computer relationship and thus presents a huge economic opportunity. Consensus in venture markets means saturation i.e. many builders and investors running after the same prize. The result: a lot of noise, and companies that pique our interest (often pre-product, strong founder-market fit) commanding valuations upwards of $20M post-money.
There is no doubt that some of these companies will be very successful (rightful consensus), but they are not interesting as potential investments for us. The biggest returns in VC come from correct non-consensus bets (i.e. under-invested, high-impact opportunities), and a fund of our size and stage needs to be in religious pursuit of such asymmetric opportunities for the math to make sense— paying Seed/Series A prices for a company assuming Pre-Seed risk kills asymmetric upside. Once a bet becomes consensus, I believe it becomes an opportunity for large multi-stage funds that can purchase and maintain large equity ownership across multiple fundraising rounds, thus having a huge share in the eventual exit — money on money investing.
It’s never been easier to build more with less— so distribution will be the big unlock for growth.
The step up we’ve had in (AI-enabled) dev tooling has reduced technical risk for many consumer tech startups— it’s never been easier to build a valuable, high-tech product with such few resources. I think this shift displaces technical risk into distribution risk. With an ocean of new companies (and not just companies, how about AI influencers etc?), how does your company cut through the noise and speak to customers?
I suspect the answer lies in content: our fastest-growing companies (e.g. Blockade, Throwback, Red Team) are all extremely effective in creating engaging short-form content which enabled them to build organic funnels to their products. I only see this trend continuing: most fast-growing startups will crush short-form content and off-platform community building (e.g. Discord). In some ways, the AI onset signals the end of the engineer-led founder era and rings in the creator-led founder era.
VR apps will become cross-platform experiences.
In my view, social VR (particularly social gaming target at Gen Alpha) is the greatest market opportunity in the Meta Quest VR ecosystem. Players come into the app, in short, for community. VR devs will realize they can build valuable access points to their ecosystem outside of VR. Roblox proved this in reverse (going from 2D to VR). To set the stage, the Apple Vision Pro (releasing 2/2) supports iOS apps making cross-platform access points native to its function.
Some off-the-cuff cross-platform examples: VR fitness apps will create experiences to earn “points” through phone/watch-based activities, and social VR games will create bridges to publish content directly to social media platforms like TikTok. I expect cross-platform access to become normative for VR companies.
AI goes multimodal unlocking consumer hardware.
Recent AI advances (e.g. Google’s Gemini Nano) are increasingly focused on multimodal inputs e.g. sensory inputs not limited to text, AND running on edge. In other words, AIs are being trained to better understand their presented environments and deployed to sensor-loaded edge devices (i.e. not on the cloud). With an LLM’s ability to process a variety of input modalities, perform or delegate an instruction, and return a response in natural language, such AI systems are breaking down barriers for consumers of not just significantly more sensor-driven mobile devices that rely less on analog “computerized” input (e.g. Humane Ai Pin) but also to consumer robotics (e.g. a robot that does your dishes at home).
The advancement in LLMs solves the communication layer between the consumer and the machine instruction, which was previously technically infeasible for most startups. I believe in 2024, we will see the early onsetting boom of consumer robotics in particular— however, I don’t believe we’ll see fully-baked offerings and mass consumer adoption immediately. We’re taking a long-term view of this space.