Render Network created an entirely new marketplace for GPU supplyan area that we believe will face continued supply/demand imbalance in the years to come. Helium Mobile is seeking to materially shift the cost structure of the telecom industry by piggybacking on cryptoenabled, user-owned infrastructure and equipment. Nubank, one the largest neobanks with more than 80 million customers, is leaning into crypto with the launch of Nucoin as a form of loyalty. Starbucks is leaning into crypto with their Odyssey program , an offshoot of their existing top-tier rewards program. Blackbird is using crypto rewards as a wedge into restaurants (which can be a precursor to driving a robust payments business that adds additional margin to the bottom line of restaurants). BAXUS is using crypto to light up a marketplace for trading and investing in whiskey and other ne spirits, opening the market to a new pool of participants.

All of these examples are very different, but at their core they are the same: they are all using crypto to power products that drive a meaningful economic outcome. In some cases, like Starbucks, Nucoin, and Blackbird, crypto is mostly obfuscated and operating under the hood. In other cases, like Hivemapper and Render, crypto is tightly coupled, highly visible, and a key part of the product itself. The design space here is wide, and the infrastructure buildout over the last 5 years has paved the way for crypto to power everyday use cases. In 2024, experimentation in this arena will explode. Eli Qian

On-Chain Data In 2024 I expect the amount of on-chain data to grow by orders of magnitude. As new users are onboarded, the use cases and functionality of dApps and protocols will grow as well. Data from decentralized social protocols will be especially abundantpeople do more things and produce more data on social products than nancial products. What will we do with this explosion of data? In the past, on-chain data has been viewed through the lens of advertising and personalization. However, Im eager to see teams take a more rst-principles approach and acknowledge that contextualizing on-chain data isnt just a luxury, but a necessity when it comes to building social products. Currently, our on-chain social data and identity is built into one, universal graph (e.g. Farcaster), making it difcult to build social products for different social contexts. People are multifaceted. We live across a wide range of social contexts. We act differently and

We go to Facebook, Twitter, LinkedIn, and Snapchat for unique reasonsthe social graph creates a specic context and