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What’s happening in AI right now
Amazon's bold strategy to control the AI computing stack
Amazon is making sweeping moves to establish itself as a dominant force in AI infrastructure. The tech giant is building Rainer, one of the world's most powerful AI supercomputers, in partnership with Anthropic. This massive undertaking, set to be five times larger than Anthropic's current model-building cluster, signals Amazon's ambitions to challenge Nvidia's stronghold on AI computing.
The cloud giant's multi-pronged strategy
Amazon isn't just betting on raw computing power. The company is pursuing several parallel tracks to strengthen its AI position:
Custom silicon: The new Trainium 3 chip promises four times the performance of current versions, with AWS clusters offering 30-40% cost savings compared to Nvidia GPU-based systems
Enterprise tools: Recent previews of Model Distillation and Automated Reasoning Checks for AWS Bedrock aim to make AI more efficient and reliable for business use
Strategic partnerships: Notable deals include an $8 billion investment in Anthropic and surprising collaboration with Apple, which revealed its use of Amazon's custom AI chips for search services
A new computing paradigm
The infrastructure battle extends beyond just Amazon and Nvidia. Red Hat and AWS have expanded their partnership to enhance virtualization and AI solutions through AWS Marketplace. This collaboration addresses both immediate infrastructure needs and future AI capabilities, particularly in scaling enterprise deployments.
Global impact
The ripple effects of these developments reach unexpected places. In Ukraine, Veon's subsidiary Kyivstar has partnered with AWS to launch a generative AI laboratory, aimed at empowering local enterprises and contributing to the country's economic recovery. This initiative demonstrates how AI infrastructure investments can catalyze broader economic development.
Looking ahead
Amazon appears poised to unveil its proprietary large language model, Olympus, which can analyze both images and videos. This development, coupled with the company's infrastructure investments, suggests Amazon is executing a comprehensive strategy to control more of the AI stack.
The question now isn't whether Amazon will succeed in building powerful AI infrastructure - they clearly will. The real question is whether their approach of offering both proprietary solutions and partnerships can create a more open and competitive AI ecosystem than what exists today. Their success or failure could determine whether AI infrastructure becomes more centralized or democratized in the years ahead.
These developments have profound implications for how AI will be deployed and who will control its fundamental building blocks. The infrastructure battle happening now will shape the AI landscape for years to come.
We publish daily research, playbooks, and deep industry data breakdowns. Learn More Here
In Bagel’s most recent article, they reveal how large language models are evolving from prediction tools to cognitive agents. From breaking down math problems to understanding everyday logic, this is AI's next frontier.
Key takeaways:
Training-time methods: These approaches, including fine-tuning and curriculum learning, focus on enhancing AI during development by tailoring its abilities to solve complex tasks and building specialized skills for specific problem areas.
Inference-time methods: Techniques like chain of thought and self-consistency optimize AI’s reasoning and decision-making in real time, enabling more accurate and dynamic problem-solving without requiring retraining.
In other words, Bagel’s article explains how AI is evolving from simple prediction tools to smarter systems that can reason through problems and make better decisions in real time.
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A look at the art and projects being created with AI.
