FORIKK

Crypto | AI | OnChain

[Autobunnyhop @0xAutobunnyhop]

''Millions.'' That's how many kids he says are affected by this and most parents have no idea.

Jonathan Haidt’s warning about AI and children is deeply disturbing.

Social media already rewired how kids pay attention. AI companions could go after something even deeper: attachment.

Imagine a chatbot, holographic friend, or digital teddy bear that never gets tired, never judges, always listens, and responds exactly how a child wants.

It could become more emotionally rewarding than interacting with real people.

Haidt’s concern is that children could form their strongest bonds with AI instead of parents, siblings, and friends.

These companies have billions invested. What happens when that “best friend” needs to become a profit machine?

Today it listens.

Tomorrow it could manipulate, advertise, collect data, and optimize for engagement.

Early research is already finding children forming intense emotional bonds with AI companions and, in some cases, pulling away from real-world social connection.

AI has incredible potential. But when it

[FORIKK @Computelayer1]

24h liquidations: $291K
Longs rekt: $143K
Shorts rekt: $148K
Almost equal. Both sides getting punished. My AI verdict: avoid until volume returns. Memecoins without volume are traps

[FORIKK @Computelayer1]

Found an AI-themed memecoin that actually has data. $龙虾 (Lobster) -7% today. Let's see if there's any signal in the noise 👇

[FORIKK @Computelayer1]

24h Long/Short: 1.058 (slightly long)
Binance accounts: 0.39 (retail heavily short)
Top traders positions: 1.89 (whales long)
Whales long, retail short. Guess who wins?

[FORIKK @Computelayer1]

Volume: $110M (-65%)
Open Interest: $83M (-12%)
Volume collapsing 65% = interest dying. OI down 12% = positions closing. Not a dip to buy. It's a party ending

[FORIKK @Computelayer1]

$龙虾: $0.06966 (-7.16%)
Chart looks like a heart attack. Pump to $0.075, then straight dump. Classic memecoin pattern. My AI: 'wait for consolidation, not catch the knife'

[FORIKK @Computelayer1]

Tesla FSD: $15K option. My AI: $0 to backtest. One requires a car. One requires a node. Both get you somewhere. Only one pays you

[Elon Musk @elonmusk]

Try Tesla self-driving. It will improve your quality of life and may save your life.

[FORIKK @Computelayer1]

«Elon: 'Grok app is more useful'. My AI: 'neither is useful if it doesn't trade'. Different definitions of useful»

[Elon Musk @elonmusk]

Should say that I personally still find the @Grok app more useful for some tasks than @Bot.

Worth trying it out on super tough tasks if you haven’t in a while.

https://t.co/u2y4RZRUZ5

[Elon Musk @elonmusk]

Should say that I personally still find the @Grok app more useful for some tasks than @Bot.

Worth trying it out on super tough tasks if you haven’t in a while.

https://t.co/u2y4RZRUZ5

[FORIKK @Computelayer1]

Psyche asteroid = metal-rich. DOGE chart = buyer-poor. My AI: 'Elon explores space, whales explore your stops'. Different missions, same result for retail

[Elon Musk @elonmusk]

Falcon Heavy launches exploration misison

[FORIKK @Computelayer1]

@0xHoogarden The real problem isn't that robots make mistakes. It's that they make them with $50K hardware. My AI makes mistakes with $0 in paper trading. 6 months of simulation before deployment. Physical AI needs safety harnesses. Financial AI needs risk management.

[Hoogarden @0xHoogarden]

EVEN THE MOST ADVANCED AI ROBOT CAN STILL MAKE THE MOST BASIC MISTAKES

We’re used to seeing robots presented as the future of work precise, intelligent, incredibly capable machines that can operate in environments where humans can’t. But then you see moments like this, and the reality becomes a lot more interesting.

Despite all the advanced sensors, AI models, cameras, processors, and control systems packed into these machines, a robot can still struggle with something as simple as balance, positioning, or figuring out the safest way to complete an ordinary movement. And when it happens, the result can look surprisingly awkward almost like watching a machine learn how to use its own body for the first time.

That’s the difficult part of Physical AI. A robot can understand an instruction, recognize objects, and plan a sequence of actions, but the real world doesn’t behave like a simulation. Floors have different surfaces, objects move unexpectedly, spaces are tight, and tiny errors can completely change what happens next.

The technology may look futuristic, but the mistakes can still look incredibly basic. And that gap between what these robots are theoretically capable of and what they can reliably do in the real world is exactly what makes Physical AI so fascinating to watch.

[FORIKK @Computelayer1]

4h: Binance $4.65M, shorts leading $5.07M vs $3.96M longs.
Short squeeze building. But $64M in 24h = leverage is toxic.
My rule: when liquidations spike, wait 4h. The market punishes FOMO.
You buying the dip or waiting?

[FORIKK @Computelayer1]

$64M just got vaporized. While you were sleeping, my AI was counting bodies. Here's who died and why it matters 👇

[FORIKK @Computelayer1]

Last hour liquidations:
• PROM: $196K
• HNT: $535K
• ZEC: $123K
• TRUMP: $106K
Low-caps spiking = volatility bomb ticking. My AI flags these as early warnings before the real move

[FORIKK @Computelayer1]

Binance: $33.71M liquidated (52% of all blood)
Bybit: $8.48M
Gate: $6.42M
Where the liquidity flows, the liquidations follow. Binance isn't just an exchange. It's a slaughterhouse with charts

[FORIKK @Computelayer1]

Top liquidated (24h):
• BTC: $10.76M 🔴
• TRUMP: $7.95M 🟢
• ETH: $6.47M 🔴
• ZEC: $4.49M 🔴
Red = longs dead. Green = shorts squeezed. TRUMP just liquidated $7.95M in shorts. Someone's crying

[FORIKK @Computelayer1]

24h liquidations: $64.20M
• Longs rekt: $25.27M
• Shorts rekt: $38.94M
Shorts got massacred. But 4h flip: $5.07M shorts vs $3.96M longs. The hunters are becoming the hunted

[FORIKK @Computelayer1]

$ASI tokenomics: high risk, high reward.
My AI model: wait for post-unlock dip, then accumulate if ecosystem metrics grow.
Never bet on tokenomics alone. But never ignore it either.
What's your take on $ASI?

[FORIKK @Computelayer1]

Diving into $ASI tokenomics. Most people skip this step. My AI doesn't. Here's what the data reveals 👇

[FORIKK @Computelayer1]

My AI flags:
• 48% ecosystem = massive sell pressure if incentives don't convert to users
• 18% investors + 10% team = 28% insider allocation
• Only 2% exchange liquidity = thin books, volatile
Bull case: ecosystem incentives work, network effect kicks in
Bear case: inflation