Technology

#AI #DePIN #GPU #CPU #blockchain $IO Yapay Zeka ve Kripto Projeleri Analisti 💯🙌🏻 | Airdrop Avcısı ✨

[Technology @Technology3327]

My M2 Max worker working hard 💪🏻 Always ready to get jobs 💯 Places are also reserved for future workers 🙌🏻

@ionet #IOnetworker

[Nosana @nosana_ai]

New milestones unlocked 🔓

✅ 4 million completed jobs
✅ 4 million total job hours

This is only the beginning!

https://t.co/rFJXWqgCkn

[Tory | io.net 🦾 @MTorygreen]

Honestly good to see @OpenAI officially join the list backing open weights. That leaves Anthropic as the only major US lab still off to the side.

Nvidia, Microsoft, Meta and now OpenAI on it, right after the gov floated treating distillation as a sec threat. Basically every big US lab and infra player except one.

Also easy to read this as follow-the-money, and for most on the list it is. Nvidia sells chips, Microsoft rents cloud, both win if models commoditize. OpenAI's a bit different but signing costs them little, also ChatGPT is the moat now, not just the raw model.

Anthropic's the interesting one, and I don't think it's really about margin for them. They're spending billions making their own models cheaper to serve, Trainium, TPUs, the AMD deals, Opus 5 pricing. That's not a company betting on models staying scarce.

It's the brand. Three years of arguing powerful models are too risky to release openly, plus lobbying for export controls and tighter oversight. Signing this would undo all of it. They're likely not off the list to protect a price but to keep the branding alive.

[Technology @Technology3327]

@MTorygreen @ionet 🔥🔥🔥

[Tory | io.net 🦾 @MTorygreen]

1.2M $IO burned, $26.2M in total network earnings for @ionet

Every burn traces back to someone paying to run a workload. Demand first, burn second. That's the only order that holds up over time.

[Nosana @nosana_ai]

“The technology itself is rarely the hardest part. The real challenge is making decentralized infrastructure feel as simple and reliable as the tools developers already use.”

@Sjoerdieb in conversation with @hackernoon ahead of the Decentralize AI Hackathon: https://t.co/mT3ycUROQx

[Nosana @nosana_ai]

Why do GPU prices keep going up, and what does that change? 📈

We’re sitting down with @ionet and @AethirCloud next Thursday to talk through the supply and demand shifts reshaping AI infrastructure costs.

📆 23 July, 5PM CET

Set your reminder: https://t.co/ZLX6UbkbP3

[IO.net TR @ionet_tr]

IDE’nin ilk ayı.

11 Haziran’dan bu yana 1,1 milyondan fazla $IO yakıldı.

Bu yakımların arkasında 122 binden fazla cihaz saati bulunuyor.

2,5 milyon $IO ödül olarak dağıtıldı.

Müşteriler tarafından desteklenen bir token modeli tam olarak böyle görünür.

Kullanım tokenı yakar. Gelir ağı finanse eder.

Bu bir yol haritası güncellemesi değil. Bu, somut bir kanıt.

[io.net @ionet]

Access.

It's a driving force at https://t.co/ZuybGWvjv9.

We want to give as many people as possible the tools to build.

That starts with our new UI.

Redesigned dashboard. Fewer clicks to a GPU. Clear pricing. No jargon.

Because decentralization means nothing if the interface keeps people out.

Live now.

[Ninja @TheIronCoder]

One month. Real results.

1.1M+ $IO burned.
122K+ device hours powered.
2.5M $IO distributed to the network.

Every burn is backed by real usage, not hype.
That’s what sustainable tokenomics looks like

[Chain INK @0xchainink]

Top 10 DePIN Projects

By Annualized Revenue

( 30D Run Rate ) 👇

• $IO → $12.1M
• $GEOD → $8.2M
• Chutes ( SN64 ) → $4.1M
• $HNT → $3.6M
• $AKT → $2.64M
• $FIL → $1.5M
• $2Z → $1.3M
• $RENDER → $1.13M
• $GLW → $511K
• $NODE → $308K

data : @DefiLlama

note: annualized ≠ realized.

one month x12, not actual inflows. run rate, not receipts. don't get baited.

[Kingeni @Kingeni_Mod]

Chaque $IO brûlé provient d'une utilisation réelle du réseau. 784 451 $IO brûlés, et ce n'est qu'un début. Aucune intervention manuelle. Aucune promesse creuse.

Une demande réelle des entreprises alimente la déflation on-chain via l'IDE.

[Technology @Technology3327]

@MTorygreen @ionet 💯🙌🏻

[Tory | io.net 🦾 @MTorygreen]

The most common objection two years ago was: "nobody will run real production workloads on decentralized GPUs."

Today @ionet is processing

> 4 billion inference tokens a day
> has crossed $25.75M in network earnings
> closed $8M in enterprise deals in Q1 alone
> burned 1,000,000 $IO in one month

All of it funded by customers paying for compute.

Nobody's asking whether decentralized compute works anymore. The new debate is how much of the market it takes.

[io.net @ionet]

$7 trillion.

That's how much will be spent on building out data centers by 2030.

Over 5% of world GDP.

Someone pays for that. Energy costs, grid strain, and access to compute itself.

That's why we built https://t.co/ZuybGWvjv9.

Immediate access. Up to 70% less than hyperscalers. No lock-in. Today, not after a $7T buildout finishes.

[io.net @ionet]

$4+/hr, an 8-GPU minimum, and a 5-year contract.

Or instant access at a fraction of the cost, scaled to what you actually need.

That's the choice in front of AI teams right now.

Enterprise-grade doesn't have to mean "locked in." Check out the full breakdown.

[Technology @Technology3327]

@ionet 💯🔥🔥🔥

[io.net @ionet]

1,000,000 $IO burned.

And that's just the first month.

This isn't just a milestone, it's a mechanism.

Every unit of compute demand on the network feeds the burn. More usage, more burn, tighter supply.

$25.75M in total network earnings and counting.

This is what real utility looks like.

[io.net @ionet]

5.3x.

That's https://t.co/ZuybGWvjv9's market cap to 30-day annualized revenue. The tightest ratio in DePIN.

No large treasury spend chasing volume. No emissions propping up the story. Just $12M+ in real, verifiable annualized revenue from customers actually using the network.

When the product does the work, the multiple takes care of itself.

[io.net @ionet]

64 H100s, 10 days.

@awscloud on-demand: $62,918.

@ionet: $22,886.

Same fine-tune. Two price tags.

Hyperscalers gate capacity behind enterprise agreements and quota approvals. @ionet pulls from idle GPUs across 130+ countries and spins up in minutes.

That's the difference between a platform built for builders, and one built for corporate profits.

[Borsa Mühendisi @borsamuhendisim]

Yapay zekanın babası Geoffrey Hinton:

“Eğer bu dersi gerçekten anladıysanız, bu gece rahat uyuyamayabilirsiniz.”

47 dakika. İzlediğim en iyi içerik.

Türkçe altyazılı. Ücretsiz. İzle.