AlphaTON Capital Secures First NVIDIA B300 GPUs for Cocoon AI Network

Reuters
Dec 16, 2025
AlphaTON Capital Secures First NVIDIA B300 GPUs for Cocoon AI Network

AlphaTON Capital Corp. announced that it has secured its first NVIDIA B300 GPUs, integrated with Supermicro's advanced HGX Systems, through a strategic partnership with Atlantic AI. The GPUs will be deployed to enhance the Cocoon AI Network, providing enterprise-grade artificial intelligence capabilities with a focus on privacy protection. This initial allocation will be deployed within the week and is aimed at supporting large language models, neural network training, and advanced AI workloads for the Telegram ecosystem.

Disclaimer: This news brief was created by Public Technologies (PUBT) using generative artificial intelligence. While PUBT strives to provide accurate and timely information, this AI-generated content is for informational purposes only and should not be interpreted as financial, investment, or legal advice. AlphaTON Capital Corp. published the original content used to generate this news brief via GlobeNewswire (Ref. ID: 9602543) on December 15, 2025, and is solely responsible for the information contained therein.

Disclaimer: Investing carries risk. This is not financial advice. The above content should not be regarded as an offer, recommendation, or solicitation on acquiring or disposing of any financial products, any associated discussions, comments, or posts by author or other users should not be considered as such either. It is solely for general information purpose only, which does not consider your own investment objectives, financial situations or needs. TTM assumes no responsibility or warranty for the accuracy and completeness of the information, investors should do their own research and may seek professional advice before investing.

Most Discussed

  1. 1
     
     
     
     
  2. 2
     
     
     
     
  3. 3
     
     
     
     
  4. 4
     
     
     
     
  5. 5
     
     
     
     
  6. 6
     
     
     
     
  7. 7
     
     
     
     
  8. 8
     
     
     
     
  9. 9
     
     
     
     
  10. 10