ACN ANNOUNCEMENTS
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Enterprise-grade AI infrastructure ecosystem enabling autonomous AI systems at scale.
Mostrar más📈 Análisis del canal de Telegram ACN ANNOUNCEMENTS
El canal ACN ANNOUNCEMENTS (@solidusaitech) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 184 254 suscriptores, ocupando la posición 572 en la categoría Tecnologías y Aplicaciones y el puesto 340 en la región Internacional.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 184 254 suscriptores.
Según los últimos datos del 31 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -5 228, y en las últimas 24 horas de -179, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 12.31%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 11.35% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 22 682 visualizaciones. En el primer día suele acumular 20 905 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 24.
- Intereses temáticos: El contenido se centra en temas clave como compute, solidus, infrastructure, workflow, agents.aitech.io.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Enterprise-grade AI infrastructure ecosystem enabling autonomous AI systems at scale.”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 01 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
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Suscriptores
-17924 horas
-1 1797 días
-5 22830 días
Archivo de publicaciones
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A lot moved forward at ACN this month.
We launched the Compute Marketplace Private Beta, Agent Forge achieved Google CASA Tier 2 certification, and more than 250 million ACN is now locked on-chain.
We also permanently removed another 132,811 ACN from circulation through the June token burn, with the next burn already scheduled.
This week, we also sent the community a more personal, forward-looking update over email, sharing some of what has been happening behind the scenes. The response was overwhelmingly positive, which was great to see.
Behind the announcements, the team continued shipping across both products every week.
Good progress, but there is still a lot of moving parts and things to accomplish.
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🗞️ AI News Roundup!
Welcome to this week’s AI News Roundup, let’s dive into the seven headlines that had everyone talking!
➡️ Read here: https://x.com/AITECHio/status/2083160273116856364?s=20
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Did You Know? Copilot Can Help Fix Your Workflow
When a workflow encounters an error, “Fix with Copilot” in Agent Forge 2.0 sends the error logs directly to Copilot for troubleshooting and automatic workflow correction.
➡️ Apply for early access: https://shorturl.at/REZfU
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Stop Guessing Your GPU Costs!
Most teams know what GPU they need.
Far fewer know whether they're paying the right price for it.
Our Cost Calculator lets you compare estimated monthly infrastructure costs across hyperscalers and ACN using your own deployment requirements.
• Select your GPU.
• Enter your node count.
• Set your monthly runtime.
See your estimated monthly spend and potential savings instantly.
Try it yourself:
➡️ aitech.io/compute-marketplace
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One Variable. Multiple Workflow Steps.
Variables blocks make it possible to store values such as names, IDs, URLs, limits, or configuration details and reuse them throughout a workflow.
Agent Forge Copilot can include these values directly within the generated workflow YAML.
👉 Apply for early access: https://shorturl.at/REZfU
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What's your biggest challenge when sourcing AI compute?
➡️ Answer here: https://x.com/AITECHio/status/2082737756531528188?s=20
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The next ACN token burn will take place in 3 days.
As part of AITECH Cloud Network’s long-term supply management strategy, a fixed amount of ACN tokens will be permanently removed from circulation through a transparent and publicly verifiable on-chain burn.
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> Running AI workloads? This one's for you.
We've added three new regions:
- US East 1
- US Central 3
- US Central 9
No need to worry about latency anymore. Simply deploy your workloads in the region closest to you.
➡️ aitech.io/compute-marketplace
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Everyone is chasing bigger models.
The biggest model isn't always the best choice.
A 70B model might outperform a 7B model on benchmarks, but if it doubles your inference cost and adds latency, it may be the worst product decision.
The best AI products aren't built around the biggest models.
They're built around the right balance of quality, speed, and cost.
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Still manually moving data, chasing leads, replying to support tickets or building reports?
You are competing against teams that have already automated it.
Sales. Support. Operations. Marketing. Finance. Internal tools.
If the work is repetitive, it should already be running through an automated workflow.
➡️ https://x.com/AITECHio/status/2082073691652010240?s=20
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250M ACN Locked!
The ACN ecosystem continues to maintain strong community participation, with 250M ACN now staked, representing 12.64% of the total token supply locked on-chain and highlighting ongoing engagement across the ecosystem.
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You can build half of Y Combinator's next batch using Agent Forge.
➡️ https://x.com/chatgpteeee/status/2081775933078573118?s=46
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One AI Model vs a Complete Workflow!
A model can generate an answer. A workflow can turn that answer into action.
It can collect data, apply conditions, request approval, update a system, and trigger the next step automatically.
Agent Forge 2.0 brings models, tools, data, and logic together in one visual workspace.
Apply for early access: https://shorturl.at/REZfU
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Weekly Development Update!
Development continues across the Compute Marketplace and Agent Forge, with ongoing progress across infrastructure development, platform refinements, expanded workflow resources, and improvements to performance, stability, and the overall user experience.
Compute Marketplace
• CDC platform development 90% complete
Agent Forge
• Continued platform optimization, stability improvements, and quality enhancements across Agent Forge
• Added new workflow templates to Agent Forge, providing users with additional ready-to-use starting points for building workflows
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🗞 ACN Weekly Snapshot!
Hey everyone, here's your ACN Weekly Snapshot, let’s dive in!
➡️ Read here: https://x.com/AITECHio/status/2081409010658660534?s=20
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Your Next Workflow Does Not Need to Start from Zero!
Agent Forge 2.0 makes workflow discovery simpler through a redesigned Template Library.
Browse different use cases, narrow down the available options, and start building from an existing structure.
👉 Apply for early access: https://shorturl.at/REZfU
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Did You Know? You Can Search and Filter Workflow Templates
The Agent Forge 2.0 Template Library brings templates into one organized space with built-in search, sorting, and filtering.
Find a workflow that fits your use case, use it as a starting point, and customize it around your needs.
👉 Apply for early access: https://shorturl.at/REZfU
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The biggest waste in AI isn't GPUs.
It's over-provisioning.
Companies size infrastructure for peak demand. Peak demand happens for maybe 30 minutes a day.
The other 23.5 hours?
You're paying for hardware that's mostly waiting.
The companies that solve utilization will have a huge advantage over the companies that simply buy more hardware.
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🗞️ AI News Roundup!
Welcome to this week’s AI News Roundup, let’s dive into the seven headlines that had everyone talking!
➡️ Read here: https://x.com/aitechio/status/2080682249369100560?s=46
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Why does everyone want H100s?
Not because they're the fastest. Because they're the safest choice.
Most enterprises don't buy the absolute best GPU for every workload. They buy the GPU they know frameworks support, engineers know how to optimize, and customers trust.
Sometimes adoption beats raw performance.
