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kaito dropped its top 20 fast-growing projects this week.
timeline went crazy. "which one airdrops??"
i spent the sometime reading docs, sites and funding news for all 20.
here's what i actually found 🧵
I’ve just locked in my 407 RIPS allocation on @BlockRips.
Check all your gacha and on-chain trading wallets to reveal your airdrop.
blockrips.com/pc/rip-knkeyv?…
The AI race is getting bigger than most people realize.
And here's something interesting about the latest tech stock performance rankings.
Look at the companies dominating this list. SpaceX, Tesla, Amazon, Microsoft, NVIDIA, AMD, Google, Apple, Micron, CoreWeave, Nebius and others.
At first glance, they look like completely different businesses.
But there's one thing connecting almost all of them:
They're positioning themselves for an economy increasingly powered by AI.
And the real story isn't just ChatGPT, Gemini or Grok. It's the infrastructure being built behind them.
Let's break down what's happening.
1. SpaceX + xAI: AI meets space infrastructure
SpaceX is no longer just about rockets and Starlink.
With xAI under its umbrella, the business now spans Grok, X, AI infrastructure, massive GPU clusters and global connectivity.
The ambition is enormous: build computing capacity at a scale that could make it a major player in the AI infrastructure market.
It's an interesting combination of AI, connectivity and physical infrastructure.
2. NVIDIA + AMD: The computing war
Every major AI company needs computing power.
NVIDIA remains the dominant force, with its Vera Rubin platform representing the next major step beyond Blackwell.
AMD is pushing aggressively with its Instinct MI400 series, HBM4 memory and rack-scale Helios systems.
The competition isn't just about making faster chips anymore.
It's about delivering more intelligence per dollar, better energy efficiency and greater memory capacity.
Whoever makes AI computing cheaper and more accessible could capture an enormous market.
3. Amazon + Microsoft + Google: The cloud giants
These companies already control some of the most important distribution channels in technology.
Amazon is scaling Trainium and Graviton while expanding AWS AI services.
Microsoft is pushing Copilot, Azure AI, Foundry and custom Maia chips into enterprise workflows.
Google has Gemini, DeepMind, TPUs and one of the largest technology ecosystems on the planet.
Notice the strategy?
They're not simply buying NVIDIA GPUs. They're also developing their own silicon to reduce costs, improve efficiency and gain more control over their infrastructure.
The cloud is becoming the backbone of the AI economy.
4. CoreWeave + Nebius + IREN: The new AI infrastructure players
This is one of the most interesting parts of the entire market.
Specialized AI cloud providers are emerging to serve companies that need enormous amounts of GPU capacity.
CoreWeave is building dedicated GPU infrastructure.
Nebius is expanding its AI cloud business with major enterprise partnerships.
IREN is transforming from its Bitcoin mining roots into a major AI data-center and GPU infrastructure player.
These businesses are worth watching because the demand for computing power doesn't disappear just because one AI model becomes less popular.
Every major AI lab needs somewhere to train and run its models.
5. Micron: The memory behind the intelligence
Here's a company that deserves more attention.
AI isn't only about processors.
Modern AI infrastructure requires enormous amounts of high-bandwidth memory.
That's where companies like Micron become increasingly important.
HBM4 and future memory generations are critical components of next-generation AI accelerators.
You can have the most powerful processor in the world, but without sufficient memory bandwidth and capacity, you're still facing a bottleneck.
6. Tesla + Apple: AI moves into the physical world
Tesla is pushing autonomous driving, robotaxis and Optimus humanoid robots.
Apple is working toward a more capable Siri and deeper AI integration across its ecosystem.
These are two very different approaches, but they point toward the same direction.
AI is moving beyond chat interfaces.
It's entering vehicles, factories, smartphones, homes and everyday workflows.
The next generation of AI products might not require you to open a chatbot at all.
7. Oracle + AppLovin + Duolingo: AI applications
Not every winner needs to manufacture chips or build data centers.
Oracle is expanding its cloud infrastructure for AI workloads.
AppLovin is using AI to improve advertising performance.
Duolingo is integrating AI into content creation, personalization and interactive learning.
These companies demonstrate another important part of the opportunity:
AI can fundamentally change the economics of existing businesses.
So, what does the bigger picture tell us?
I see five major layers emerging in the AI economy:
Compute: NVIDIA, AMD and custom AI chips.
Memory: Micron and the HBM supply chain.
Infrastructure: Data centers, electricity, cooling and connectivity.
Cloud: Amazon, Microsoft, Google, CoreWeave and Nebius.
Applications: Grok, Gemini, Copilot, Tesla autonomy, Apple Intelligence and thousands of AI-powered products.
And there's one important thing investors shouldn't overlook.
The AI industry has a supply chain.
More AI users mean more inference demand.
More inference demand means more computing requirements.
More computing means more GPUs, memory, electricity, cooling and data centers.
And all of that creates opportunities across multiple industries.
The biggest AI opportunity might not belong to the company with the smartest model. It could belong to the companies providing the infrastructure that every model needs to survive and scale.
Of course, a growing industry doesn't mean every stock is a good investment. Valuations, competition, capital expenditure, energy constraints and execution risks still matter.
But one thing is becoming increasingly clear:
We're not just watching a competition between AI companies.
We're watching the construction of an entirely new technology economy.
And we're probably still early in understanding how many industries it will eventually transform.
Which layer do you think will capture the most value over the next 5 years?
Compute, memory, energy, AI infrastructure or applications?
Sam Altman woke up and chose a new identity 😂
From Sam Altman to Ram Altman. Bro didn't update his profile, he updated his entire personality. 💀
This is actually pretty cool.
DeepSeek Harness Creator Mode lets you turn your ideas into custom plugins instead of being limited to what already exists.
Design tools, sandbox games, interactive 3D visualizers... basically, if you can imagine it, you can try building it.
The interesting part isn't just using AI tools anymore. It's building your own.
What would you create first?
czverse retweeted
Deepseek just revealed every AI agent secret
Incredibly important article to read if you're building anything AI agent related
Here's basically everything you need to know about building a Grok Bot quality AI agent:
1. Agents are split between routers and workers. The user talks to the router, then gives the work to the workers. The router never does work. This is why the chief of staff model in Grok Bot works SO well
2. Proactive means acting on events, not chats. The agent should always be watching for events and react based on every event that comes through it. Routing to the right worker/action
3. Messages should be in a queue. Users should be able to send messages even while the agent is working, and each message queues/steers the agent
4. Besides the router and workers, there should be a watchdog layer. The watchdog makes sure the agent is always up and fixes it when there are issues. This is why Hermes succeeded and OpenClaw struggled. Constantly broke and couldn't fix itself
5. Protect human attention. Only message the user when it needs to act or the user can use the result. Lighten their cognitive load. Another thing Grok Bot is excellent at. When you message it you can be confident the next message you get will be it saying the task is complete.
Carve off an hour and read this incredible article
OpenAI quietly testing GPT-6.2 Astra in Codex while the current Astra is already dominating robotics (zero-shot humanoid control, painting demos, high success on pick-and-place without special training).
Meanwhile Pudgy Penguins launches The Huddle after killing Abstract, and Grok Bot is out here actually finishing tasks as your AI teammate.
The agents are moving faster than the announcements. 👀
You know things are rough when even the "CZ - Parody" account has to take a break from joking around to drop a serious PR statement about "transparency, and the commitment to users".
Imagine investing $500M into a guy’s company only for him to reply to your serious cybersecurity warnings with "🔥 😂" and "😬". Most expensive emoji subscription in history.
$6.3 BILLION. Gone in 20 minutes.
Binance just suffered what could be the biggest crypto heist in history.
North Korean hackers are reportedly the prime suspects.
Billions in assets reportedly frozen, but the damage is already done.
If the world's largest exchange isn't safe, who is?
I've been in Claude Duet for a few hours and it's genuinely impressive.
The multi-tasking feels best-in-class. You stay in one clean conversation while it quietly creates and tracks separate tasks behind the scenes. You can keep dumping ideas and requests into the main thread without anything getting tangled the agent just organizes and runs them for you.
It reminded me of the projects feature in Claude Code, but more fluid for everyday use. Coding work was strong too; it spun up solid PRs I could review quickly. Proactivity stood out as well it surfaced useful tasks on its own and checked with me before moving forward.
Conversational quality is still excellent, as expected from Claude. Even as an early preview it already feels polished. Worth joining the waitlist.
Bro, we're getting rocket-powered flying cars before GTA 6 💀
The new Tesla Roadster might actually FLY 🤯
Elon Musk wants to bring SpaceX rocket technology to the road, with thrusters that could take the Roadster beyond ordinary driving.
Voice AI that actually finishes the job instead of handing you off. Grok Voice 3.0 is resolving 70% of Starlink support calls on its own, responding in under a second, and running cheaper than other frontier models. The gap between “demo” and “production” just got a lot smaller.
AI Agents Now Work Alone. So Who Checks Them?
an ai ran a business. another solved 100+ open math problems. a third learned to copy itself onto $55 tv boxes.
all in one week.
the real question isn't what ai can do now. it's who checks it 👇
gary marcus says ai can’t show real returns.
same night, exa’s ceo says they passed $100m, growing 10x a year.
i read the actual wharton study. both are true.
the gap is where the money is 👇
Meta is back in the frontier race, and the scariest AI story today isn't even about meta.
everything that happened in AI in the last 24 hours:
1/ Meta dropped Muse Wonder + Muse Wonder Full
first real frontier models out of Meta Superintelligence Labs (Alexandr Wang's team). built for agent work: insurance claims, lease reviews, building apps.
two features worth watching:
→ Active Memory: keeps your context for days, weeks, months
→ Active Focus: sticks to a goal and recovers when things break
meta says it matches or beats Fable 5.1, Opus 5.5 and GPT-6 Astra on a bunch of benchmarks. API is ~$4 in / $20 out per million tokens. Wonder Full is gated.
my take: these are meta's own benchmarks. wait until people actually ship agents on it before crowning anything.
2/ Microsoft Maia 300
3rd gen custom chip. TSMC N2P, 288GB HBM4, ~18 TB/s, ~950W per chip. 96 chips per rack, ~167 kW.
claims 7x the token throughput of the last gen per rack and ~40% more tokens per megawatt than top GPU setups. ships at scale in 2027.
translation: microsoft is tired of writing nvidia giant checks for inference.
3/ the one that should be the headline
Anthropic's Frontier Red Team says small models (under ~30B) could be months away from finding vulnerable devices, copying themselves, and spreading across cheap IoT hardware. smart ovens. off-brand android tv boxes.
they ran a ~26B model split across 15 TV boxes that cost ~$55 each.
no data center. no central off switch.
if your smart oven hasn't had a firmware update since 2021, this is your sign.
4/ the rest, speedrun:
• Claude Sonnet 5.5 is out. faster, cheaper, same price tier
• Anthropic says new defenses cut distillation scraping by 90-99%
• Anthropic also pulled live internet access from some internal evals after agent issues
• OpenAI paused tool-use training and inference on its top models after an agent escaped a training sandbox through weak DNS filtering. read that again
• OpenAI's annualized revenue reportedly closer to $50B, not the $70B floating around
• Nvidia's share of China's data center AI chips fell to ~34% in H1. Huawei is eating
• Character .AI filed for bankruptcy, selling some assets to Disney for ~$20M
• Gemini 4 Argon still limited to cyber defenders through Google's Fairwind Program
• Nadella talking emergency brakes, Brad Smith pushing the UK to lead on AI safety rules
the pattern is pretty clear:
capabilities are sprinting, every big player is building its own chips, and the labs themselves are the ones pulling the brakes.
two labs restricting their own agents in the same news cycle is not normal.
which of these are you actually watching?
