Cryptopixie(💙,🧡) “$XAR”

Join io.net CSO/CMO @0xHushky and APAC Lead @TheAntiApe to talk about the growth of DePIN and the impact that decentralized compute networks will have on AI

Compute is the digital oil powering a new industrial revolution with AI at it's center. @ionet_official is building the petrodollar - IO. This is compute as a currency.

In just 10 days since io.net's Ignition program launched, the number of workers has grown from 26,000 to over 51,000 GPUs! Listen to @angelaywyi give alpha about how consumer @Apple M1 / M2 / M3 chips are supported by io.net (and are eligible to receive boosted rewards in the Ignition program).

Nov 4 2023 to Feb 4 2024: 24K nodes on io.net Feb 5 2024 to Mar 17 2024: 89K nodes on io.net

The AI compute DePIN space is just getting started. io.net is building the largest AI compute DePIN in the world and giving builders the power to create super clusters from tens of thousands of distributed GPUs. Let's bring AI to the world.

Happy genesis block day @solana

AI innovation is advancing rapidly, leading to an increased demand for computing power while simultaneously reducing GPU availability. This daily intensifying challenge motivated the establishment of @ionet_official. @ionet_official tackles the global shortage of GPU compute by aggregating supply from underutilized sources, including independent data centers, crypto mining farms, and consumer GPUs, boosting utilization rates to nearly 100%. This facilitates the creation of decentralized GPU clusters across multiple locations, with @ionet_official being the sole GPU aggregator capable of doing this. Leveraging these strategies allows for the provision of unmatched cost efficiency for low-latency, on-demand GPU compute, priced 90% lower than the competition.

As AI innovation continues, demand for GPU compute to power AI and ML workloads doubles every 3 months, however some sources of the supply of GPU compute remains underutilized. By aggregating underutilized sources of supply from independent data centers, crypto mining farms, and consumer GPUs, @ionet_official's abilities to create decentralized clusters accross multiple locations facilitates the creation of a 'structural arbitrage'. This allows @ionet_official to increase utilization rates to nearly 100%, whilst offering prices up to 90% cheaper than competitors –– the recent expansion of supply in the network featuring 72 A4000 GPUs only accelerates these capabilities. @ionet_official is building the internet of GPUs.

Interested in joining the 60,000 GPU workers on io.net and building the largest AI compute DePIN in the world? Check out the installation guide from our Turkish community ambassador @okansariirmak Bring AI to the world.

Gain access to hundreds of thousands of GPUs in seconds with @ionet_official. Seamlessly access an array of 44K+ GPUs on the @ionet_official network and deploy instantaneously –– with customization features for level of security and connection speed –– at lower prices that are 90% cheaper than traditional cloud providers. Users can select from best-in-class GPUs, such as A100s and H100s, and utilize low-latency compute with a click of a button. @ionet_official offers unmatched cost-efficiency for on-demand GPU compute. Discover how the world's largest AI compute cloud is being built at io.net.

Community Notes: There are actually 72,495 GPU nodes on io.net

Demand for GPU compute continues to rise, making it much more expensive to access GPUs. This is because GPUs are used to power the compute capabilities of AI and ML, and as AI continues to innovate, GPUs become increasingly unavailable and hence more expensive. @ionet_official Cloud is addressing this growing concern by aggregating GPUs that are geographically distributed across multiple locations into a DePIN. This allows @ionet_official to offer low-latency compute capacity at the scale required by AI and ML companies while staying cost-efficient.

Building the world's largest AI compute DePIN means io.net has tens of thousands of independent node operators around the world. Providing alternatives to centralized cloud providers is more than bringing transactions for compute on-chain, it is tapping into the distributed compute that already exists in the world and making it available to innovators and builders advancing AI and ML. video from our community member @leeland_sol

io.net harnesses the power of hundreds of millions of consumer Apple Silicon chips to power AI/ML workloads. Engineers can cluster Apple M1/M2/M3 chips for ML and AI compute from anywhere around the world on io.net, and users with Apple hardware can earn by contributing spare computing resources for AI and ML use cases. Consumer Apple chips are also eligible to receive boosted rewards in the io.net Ignition Program. Discover the full article by @Cointelegraph on io.net's expansion to support Apple hardware here: cointelegraph.com/news/ionet…

🎙️ Join our space with @BanyanComputer for a discussion on partnership, crypto, AI, and more. 🗓️ March 6th, 1 PM EST Set your reminders below - we hope to see you there! xitter.cf/i/spaces/1OdKrjYwwPvKX

BREAKING: io.net has raised $30M to build the largest decentralized GPU network in the world and solve the AI compute shortage. The Series A round was led by Hack VC with participation from Multicoin Capital, 6th Man Ventures, M13, Delphi Digital, Solana Labs, Aptos Labs, Foresight, Amber, Longhash, SevenX, ArkStream, Animoca Brands, Continue Capital, MH Ventures, Sandbox Games. Prominent industry leaders also joined the funding round, including Solana founder Anatoly Yakovenk, Aptos founders Mo Shaikh and Avery Ching, Yat Siu of Animoca Brands, Sebastien Borget of The Sandbox, and Jin Kang of Perlone Capital. reuters.com/technology/ai-fo…

The io.net community came in force to countdown the Series A announcement. Join us in Discord every Wednesday at 3:30PM UTC.

🤝 @laurashin @Unchained_pod

Over $400K in Worker earnings (just $100K in the last 21 days) in just four short months since launch. 40,000+ Workers in the network and over 3,800 GPU clusters deployed. AI/ML companies can create clusters of up to tens of thousands of GPUs for both model training AND inferencing.