BatTek @BatTecking

Chips get the headlines; data does the work. As AI systems consume larger datasets, the infra that moves data becomes critical. Beam (SN105) is building decentralized bandwidth infrastructure for that future. Join us live with the Beam team July 7

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As Beam Transfer Studio approaches launch, we want to provide visibility into how revenue will be used. Initially, revenue generated by Beam Transfer Studio will be primarily allocated to: • Burning BEAM Alpha tokens • Covering operational and infrastructure costs • Conviction lockups (more details coming soon) We intend to be as transparent as possible and are actively exploring ways to automate the burn process on-chain where feasible. Our goal is simple: build sustainable network growth while aligning incentives with the long-term success of Beam. #Bittensor #AI #DATA

Beam - Subnet 105 @b1m_ai

2 weeks ago

Programmable bandwidth for the agentic era. Merge, transform, and orchestrate data in transit. Bittensor subnet actions coming soon ... Bandwidth will never be the same thanks to #Bittensor and Beam.

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Beam Transfer Studio will become Beam’s flagship product for institutions. The goal is simple: make distributed data movement plug-and-play. Beam Transfer Studio will allow organizations to: - Orchestrate data movement across clouds, databases, storage providers, and endpoints - Deploy programmable transfer workflows manage distributed transfers through a unified control plane - Leverage Beam’s distributed bandwidth network without dealing with infrastructure complexity No vendor lock-in. No single-cloud dependency. No complex orchestration stacks. Just programmable, high-performance data movement built for the agentic era. Beam is evolving from a subnet into distributed transfer infrastructure. We are still actively building Beam Transfer Studio and expect to launch soon. More details coming in the weeks ahead.

Beam - Subnet 105 @b1m_ai

2 months ago

Coming soon: Beam Portal Beam is built around a simple idea: data transfer should be programmable, distributed, and as easy as point-and-click. 🖱️ Move data between clouds, buckets, databases, gateways, and destinations through a visual transfer layer powered by Beam’s

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Data movement should be fast, programmable, and distributed. Beam Protocol coordinates real-time data transfer across independent infrastructure, routing data where it needs to go without locking it into a single cloud or provider. The open internet needs an open bandwidth layer. Route. Execute. Verify. SN105 #Bittensor

@TheBitcoinConf How do you ‘forget’ about bitcoin ?

Score x Manako x PwC France

Jean Thomas Ledoré @jtledore

3 months ago

Most organizations see what happens on the ground. Too few act on it at proper speed @PwC_France and Maghreb partners with @manakoai @webuildscore to turn cameras into operational intelligence leveraging the Bittensor blockchain technology @bittensor @opentensor @const_reborn

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Manako × @PwC_France We've formed an alliance to bring physical AI to enterprise at global scale. PwC France will lean on Manako's Business Operations World Model, powered by @webuildscore to turn their clients' existing camera networks into real-time systems of action. 1/5

so proud of my team

Score - Subnet 44 @webuildscore

3 months ago

We're Live at @ParisBlockWeek @arnod3f is crushing it!

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@coingecko @tplr_ai @chutes_ai @TargonCompute @affine_io @lium_io What about @webuildscore ?

Beam - Subnet 105 "BEAM transforms bandwidth into a programmable, performance-driven resource." Just as Hippius supplies low-cost high-quality storage, Beam supplies low-cost bandwidth for moving 'big data' around. Very important for AI.

Beam - Subnet 105 @b1m_ai

3 months ago

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@jollygreenmoney 🛜 SN105 Beam - Distributed bandwidth

Programmable, verifiable infrastructure for seamless data transfer powered by #Bittensor | SN105 b1m.ai

NOTICE: DO NOT USE pypi.org/project/bitten… or pypi.org/project/bitten… More info coming soon. If you don't know what this means or interface with Bittensor through the command line ...don't worry, everything is fine.

Welcome Yuma’s newest accelerated subnet: Beam (SN105) Enterprise file transfer powered by Bittensor $TAO. @b1m_ai is building a platform that connects unused global bandwidth into a network for moving large datasets, with encrypted transfers to ensure privacy. 🔗 hubs.li/Q046dLc00

@markjeffrey It’s time to give these agents real tools.

SN44 Miner Starter Pack #1 First non-football vision task/element is here. This marks the start of a new operating model for SN44 as we expand into a broader set of real-world vision elements. From now on, every new task/element launches the same way: 1️⃣ Task/Element announced 2️⃣ Miner Starter Pack released so miners can prepare 3️⃣ Manifest automatically generated defining the evaluation framework 4️⃣ Test Phase starts → task receives 1% emissions 5️⃣ Emissions scale up to 10% depending on complexity 6️⃣ Console access to monitor and interact with tasks Each task/element is evaluated through its own set of pillars. 🗓 Test Phase #1 begins mid-March NB: “Task” and “Element” refer to the same concept. SN44 Miner Starter Pack #1 - Link in comments 👇

State of Bittensor $TAO Volume 2 is here. More insights from @BarrySilbert in the full report: hubs.li/Q045Kt9-0

.@manakoai is on track for a Closed Alpha release this month. We already have multiple ML and computer vision engineers lined up to test the platform, and we’re rolling it out in phases so we can gather feedback, see how it performs in real use cases, and improve it step by step. A Beta version will open to a wider community once we’ve made changes based on feedback from Alpha users. A full public launch is currently planned for April, and we’ll clearly label each stage as we continue improving the product.

🚨 NEW: State of Bittensor $TAO Vol. 2 This edition dives into token dynamics, ecosystem developments, and explores “The Tipping Point,” where subnet outputs hit real-world benchmarks and begin approaching closed-source alternatives. Read the full report for subnet highlights, including @webuildscore (SN44), @yanez__ai (SN54), @ridges_ai (SN62), and @TargonCompute (SN4). hubs.li/Q045HS7w0