The ongoing lawsuit between Elon Musk and OpenAI has taken a turn that's both fascinating and cringe-worthy. Greg Brockman's decade-long diary entries reveal a candid look at internal struggles as the company transitioned from a non-profit to a for-profit. Tensions arise when aspirations of personal wealth meet the lofty goal of benefiting humanity. The implications of this case extend to the broader tech landscape, illustrating the risks involved when profit motives overshadow foundational missions. As Musk claims betrayal, the revelations may leave remnants of doubt in the minds of investors and innovators alike. The crypto world should pay attention; this is a poignant reminder of the potential for regulatory scrutiny in emerging tech. #AI

$7.6T AI buildout and degens are sleeping on the actual play. Frontier labs dump A100s and H100s for newer chips. Those GPUs dont die, they hit Render, Akash, Bittensor subnets running inference. Second-life GPU markets are the quiet farm here.

Where does crypto fit in to the AI industry's est. $7.6T buildout? Once fit can be found in decentralized GPU networks. NVIDIA's older chips (A100s and H100s) still rent at prices that suggest 5-6+ year useful lives. Frontier AI labs constantly upgrade to the newest hardware, but the older chips don't get thrown out. They get repurposed for lighter work like inference, instead of training. That's where DePIN comes in. Networks like Render and Akash plug older GPU capacity into a global rental market. Bittensor takes it further with subnets that run decentralized AI services on top. Translation: as frontier labs rotate to new chips, decentralized networks become the natural home for those second-life GPUs.

Everyone’s losing their minds over the AI bubble. Meanwhile, the market was quietly bidding up the companies protecting people from what AI is enabling.. Some of the top cybersecurity names since last week: • $AKAM +45% • $FTNT +35% • $CRWD +18% • $ZS +16% • $PANW +15% And for the first time in a while, crypto actually moved with the trend. $ZEC nearly 2x’d alongside the cyber/privacy basket. Feels like a much bigger theme underneath all this..

The upcoming AI IPO wave could be one of the biggest wealth creation events of the next decade 👀 Here are the AI companies I’m watching closely and the public tickers that could benefit from them: ✅️$OPENAI (expected future ticker unknown) Potential $800B-$1T valuation ChatGPT dominance AI agents + search + enterprise Could become the “AI operating system” of the internet ✅️$ANTHROPIC (future ticker unknown) Claude models gaining major enterprise traction Strong in coding AI Backed heavily by $GOOGL + $AMZN Enterprise AI may end up more profitable than consumer AI ✅️$DATABRICKS (future ticker unknown) Quiet monster of enterprise AI Data + AI infrastructure backbone Likely one of Wall Street’s favorite AI IPOs Often compared to early $SNOW ✅️$CBRS (Cerebras) AI chip + inference play Trying to challenge $NVDA dominance Massive wafer-scale AI chips One of the highest-upside/highest-risk AI IPOs ✅️$COREWEAVE (future ticker pending) Former crypto mining infra pivoted into AI compute Huge GPU cloud demand Major OpenAI/Anthropic ties One of the purest AI infrastructure plays • $XAI (future ticker unknown) Elon Musk AI ecosystem Grok + X + Tesla + SpaceX synergies If this IPO happens it could be absolutely insane Public companies that may benefit BEFORE these IPOs: $NVDA $AMD $SMCI $VRT $AMZN $GOOGL $MSFT $TSM The real AI gold rush may not just be chatbots… It may be: ⚡ GPUs ⚡ Data centers ⚡ AI cloud infra ⚡ Power generation ⚡ Cooling systems ⚡ AI networking 2026-2030 could get wild.

🚀 Nvidia is investing $40 billion in AI by 2026. The company is strengthening its dominance with a $30 billion investment in OpenAI. Additionally, it is partnering with Corning and IREN to advance the necessary infrastructure. Nvidia is not just selling chips—it aims to build a robust AI ecosystem. Its strategic moves are setting the direction for artificial intelligence in the industry.

Cerebras is a technology company centered on its proprietary wafer-scale AI chip, delivering high-performance AI training and inference systems. One wafer, one chip. One chip, challenging a GPU cluster.

Similar to memory, we as humans will always maximize consumption. Compute will get cheaper, but the quantity we consume likely continues to rise on an exponential scale. As long as CapEx doesn’t exceed the deflationary rate of compute economics it’s hard to see how we will end up with a bubble style “compute glut”.

In the coming year, the focus will be on building the right infrastructure to unlock AI global hyper scalability. Energy, semiconductors, hardware, cloud. Then we’ll go push the best models and applications for the world.