AI startup Magic has completed a $320 million funding round, with participation from Eric Schmidt, Alphabet's CapitalG, and investors like Atlassian, bringing the total funding close to $500 million. Magic focuses on AI model development aimed at generating code and automating software development tasks, featuring an exceptionally long context window of up to 100 million tokens, surpassing current commercial models. Magic plans to collaborate with Google Cloud to build two supercomputers to enhance

Amazon Web Services (AWS) has launched a new High Performance Computing (HPC) management service - AWS Parallel Computing Service, aimed at simplifying the process for businesses to access and utilize supercomputing resources, lowering the barrier to entry. This service utilizes the open-source tool Slurm to manage clusters, allowing users to easily set up and manage clusters of Amazon Elastic Compute Cloud (EC2) instances on AWS without complex system administrator support. Businesses only need one AWS account to experiment and test the advantages of their workloads in large-scale computing.

Elon Musk showcased the internal structure of Tesla's Cortex AI supercomputer cluster being built at the Austin headquarters, which is expected to require 130 megawatts of cooling and power upon launch, growing to 500 megawatts by 2026. The cluster contains 70,000 AI servers, primarily used to solve real-world AI issues, particularly for training Tesla's full self-driving system and the AI for the Optimus robot. Cortex will rely entirely on Nvidia's hardware at launch, while Tesla's own hardware is expected.

Nvidia's net income increased by 265% in the fourth quarter, with founder Jensen Huang announcing Nvidia AI services. The company generated $22.1 billion in revenue, with net profit skyrocketing by 769%, exceeding expectations. The Nvidia AI supercomputer DGX can be accessed via web browser and is available on multiple cloud platforms.

Scientists successfully trained a model at ChatGPT level using only 8% of the computing power. The research team utilized innovative technology on the Frontier supercomputer, training a trillion-parameter language model with just thousands of AMD GPUs. They achieved 100% weak scaling efficiency for 175 billion-parameter and trillion-parameter models while utilizing only 8% of computing capacity. The results indicate that training large language models with trillion parameters remains challenging.

The EU plans to support local AI startups in model training by providing access to supercomputer processing power. The early involvement of Mistral in the EU's supercomputer access program may indicate alignment of ideas. The European Commission has announced that dedicated supercomputer access will be provided to AI startups to help them develop large models. This initiative is the latest move in the EU's increased investment in artificial intelligence, aiming to help European companies compete with the US in this critical field.

🔍 Government Quadruples AI Spending: The UK government will increase spending on AI chips and supercomputers. 🌐 UK Positioned as a Global Hub: The UK government aims to position the country as a global center for AI technology through agreements with international research networks. 🔬 Supercomputer Investment: The government has approved an investment of £100 million for a supercomputer facility in Bristol.