KNOWLEDGE ATLAS Deploys 1GW of Domestic Computing Power and Finalizes Acquisition of XCore Sigma

Deep News
Jul 21

KNOWLEDGE ATLAS has successfully deployed a 1GW-scale domestic AI computing data center, utilizing entirely domestically produced AI chips. In a related move, the company has also completed the acquisition of the domestic AI heterogeneous computing software firm XCore Sigma.

These two strategic actions address two critical capabilities: computing power supply and computing power utilization. The data center provides the computational resources necessary for large-scale model training. The acquisition of XCore Sigma, a team originating from the Compilation Laboratory of the Institute of Computing Technology, Chinese Academy of Sciences, brings expertise in heterogeneous computing software stacks and compilation optimization. This is expected to enhance the utilization rate of heterogeneous chips, reduce inference costs, and improve model deployment efficiency through foundational software capabilities like compilers, runtime systems, and inference engines.

Recent market discussions have focused on KNOWLEDGE ATLAS's next-generation foundational model. Industry observers suggest that, supported by this large-scale computing power, a mature infrastructure system, and long-accumulated post-training capabilities, the company's next model is poised to evolve towards larger parameter scales and higher intelligence levels, while maintaining a focus on inference efficiency and engineering deployability.

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