Mythos reportedly cracked classified systems at the NSA within hours.
This will stoke intense AI fears, which will lead to calls for more regulation and federal oversight. It is hard to see a world where the government doesn’t get more involved if the technology is accelerating at this pace.
But the bigger story to me is that AGI is essentially here. We have technology that is not only smarter and more powerful than humans, but the technology is training itself to improve at rates that are hard to comprehend.
Humans are no match for the models.
Given the pace of innovation over the last two years, we have become desensitized to these major leaps forward. Each model release has brought bigger expectations and a higher degree of confidence that technology is going to improve.
We have to address the negative trade-offs, but this remains one of the most exciting times in human history. Superhuman intelligence is abundantly available to anyone. The possibilities are endless and society is going to be a big winner in the end.
“Most people are scared to be uncomfortable.”
Joe Rogan and Tom Segura were talking about guys in their late 40s who never focused, never built anything, and now they’re scrambling, desperate, and depressed.
Tom says he has a lot of friends like this. The root cause? They spent decades avoiding discomfort, and suddenly time is gone.
This is classic “avoidance coping.” Research shows chronic avoidance of discomfort doesn’t just delay growth, it compounds regret and increases anxiety and depression later in life. The pain of regret eventually outweighs the temporary pain of discipline.
The most valuable skill sets on the planet right now:
1. people who can set up agents properly, manage them, and run local AI models
2. marketers who know how to build distribution
3. robotics engineers who can do all three: build the hardware, wire in the AI, and source manufacturing etc
4. curators who are good at yapping and can do short form video in their sleep
5. the builder-distributor. The one person who can both ship the product AND get it in front of people
6. IRL community builders
Try running this prompt in Nansen AI:
“Look at all my trading history. What are my top areas of improvements? What am I doing well?
Look at the data first, then give me a summary.”
Actually super useful!
We crossed $500M in tokenized equities under management while the announcements were still being written.
$30B + volume. 150+ assets. 170K+ holders. 100+ partners. 1:1 backed. Live today.
Good to see the rest of the world catching on.
Many lost hope on Crypto-based projects and I think we reached rock bottom or almost near it.
Despite that my last two bet is still in two well differentiate projects:
1) @nansen_ai On-chain analytics merged now with the almighty power of AI.
2) @Claynosaurz a unique NFT Community that offer ownership in the equity of the whole brand.
I'll come back to this (probably after years) to check if my last bets were a good one or if I just couldn't see through.
"Every company is going to have to build what I think of as human capital and token capital. Human capital comprises the knowledge, judgment, relationships, ingenuity, and pattern recognition of its people, while token capital is the firm's Al capability it builds and owns."
Unlike many investors in crypto, I did not pivot to AI in the last few years. However, since 2020, I built some of the deepest understanding in this industry on the intersection of AI and decentralized networks (crypto, web3).
From the start, it was very clear that AI models are a centralizing force and the biggest target for government control. That point became market fact last night, with @AnthropicAI’s export control compliance.
As an investor in decentralized AI, I know that d-networks are a counterbalance to this state of affairs. In particular, the starting point of sovereign, open, public, decentralized AI is the seemingly insurmountable compute problem.
How are people supposed to source more industrial compute for frontier training than these huge trillion dollar companies? The answer is simple: there is enough commodity GPU compute in the world to compete on the frontier, but to make use of it we need new algorithms for training.
That’s what a few companies like @gensynai@PrimeIntellect@bageldotcom@Pluralis@NousResearch@MacrocosmosAI@covenant_ai set out to research, while everyone on the planet told them it was impossible.
The result is that it is not only possible, but it can be cheaper and nearly as efficient as the alternative process.
The second major problem is economic sustainability. Open source models are great, however, they are not economically viable as they don’t have a business model. So far in decentralized AI, only @Pluralis has an answer — by breaking up the weights of the model among participants, we create a business model for tokenized AI models.
This is the moment of truth — will AI become fully centralized and fall under censorship and unilateral government control? Or will the AI world realize the importance of public AI on open decentralized networks?