Skip to main content

AI Dispatch #38: Can AI Really Trade?

AI Dispatch #38: Can AI Really Trade? — research from Castle Labs.

Castle Labs3 min read
AI Dispatch #38: Can AI Really Trade?

Welcome to another edition of the AI dispatch, which starts with a question:

How good are AIs really at trading?

Last week, @jay_azhang of https://x.com/the_nof1 launched a competition named “Alpha Arena”, where they gave $10k each to the six most well-known AI models and asked them to trade.

Article figure

How are they doing? Here is the last update:

Article figure

Kinda funny how this was described as “AI hamster races” for those who remembers lol, but regardless, this may prove a worthwhile experiment to see which model performs the best in a trading scenario.

An interesting thing to note is that the different models have their own style of trading, as noted by @jinglingcookies below.

Article figure


David from USDai shares more on the link between AI and stablecoins and how the latter can help it scale.

Article figure

USDai is doing extremely well. We talked briefly about them in our Arbitrum corner this week: they have over $500m in TVL, and every time they open their vaults, they fill it.

Article figure

Given the demand, the token has actually been trading with a premium above $1 for a while (probably will continue until caps are raised).


In other news, Mode launched Season 6, powered also by @optimism rewards, and focusing on AI trading agents:

Article figure

These can be either:

  • Breakout Agent: with a focus on volatility

  • Trend Agent: focusing on trend momentum

The most important aspect here is Mode’s focus on ensuring verifiability of trading operations with a (soon-to-be-launched) framework built on ERC-8004.


More on AI verifiability from Eigenlayer:

Article figure

Plus, someone built a game using EigenAI x Eigen Compute!

Article figure


Someone recently integrated $REI’s closed beta access into his ChromBot LMAO

Article figure


Depending on where you stand, here are some developments that you either consider extremely creepy or just the way our future looks.

Article figure

Uber is now paying drivers for doing tasks such as:

  • Data labelling for AI

  • Recording audio samples

  • Language training across different scenarios

  • Uploading restaurants menus

Great post by @bearlyai, which highlights how data labelling is expected to continue growing as a market. Uber’s move is not random, as it recently acquired Segments AI, a data-labelling startup.


We haven’t been talking about Virtuals in a while! This week, they shared an analysis on their Agentic Commerce Protocol (ACP) and how it compares with others, such as Anthropic, Coinbase, Stripe, Google, and Ethereum.

Article figure

For more Virtuals news, we also suggest this great interview the chads at Blocmates did!

Article figure


Also, a lot of news for Bittensor, which has been benefiting TAO, Sammy sums them up:

Article figure


Last week we also had our own couple articles on AI.

First, we shared more about the Almanak agentic wars and how they are planning to leverage incentives in a way similar to Curve but adapted to their protocol.

Article figure

Secondly, we wrote an introduction to Robotics - which you should expect to be followed by more.

Article figure


Now, Kaito launched a leaderboard for Robotics, which might be a treasure trove in terms of who to follow to get the best robotics news.

Among the projects that also launched their own leaderboard, we find OpenMind (@openmind_agi), which “ builds open-source software that helps machines think, learn, and collaborate, with OM1 - the Android for robots, and FABRIC - the coordination layer for machine economy.”

Article figure

Those interested in diving deeper into OpenMind should do so with @cot_research's great report on the project!

Article figure


Maybe not directly AI related, but super nerdy read on chip printers!

Article figure


This week, we leave you with a bullish outlook by Galaxy Digital Head of Research!

Article figure


Actually not, we leave you with a final reflection. As the demand for AI grows in the coming years, this will require building many data centres all around the world, which need water and fuel to run 24/7.

How will this impact our consumption of energy?

Imagine a data centre being built right next to where you live, sucking up all the water and electricity. Kind of a big deal, no?

Article figure


If this is not enough here’s more weekly AI content from Jeff the man himself:

Article figure

Anyway, that’s it for this week! Have a great Monday, and make sure to keep up because these are the best times to be on top of the market.

Originally published in the Castle Labs newsletter. Subscribe at research.castlelabs.io.