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  • šŸ¤– Former PayPal CEO Warns AI Threatens ā€œMath Peopleā€

šŸ¤– Former PayPal CEO Warns AI Threatens ā€œMath Peopleā€

PLUS: Elon Muskā€™s xAI Builds Worldā€™s Biggest AI Cluster, Nous Research Fixes GPU-to-GPU Communication

Welcome back AI enthusiasts!

In todayā€™s AI Report:

  • šŸŽ™Former PayPal CEO Warns AI Threatens ā€œMath Peopleā€

  • āš™ļøElon Muskā€™s xAI Builds Worldā€™s Biggest AI Cluster

  • šŸ’ØNous Research Fixes GPU-to-GPU Communication

  • šŸ› Trending Tools

  • šŸ’°Funding Frontlines

  • šŸ’¼Whoā€™s Hiring?

Read Time: 3 minutes

šŸ—žRECENT NEWS

PETER THIEL

šŸŽ™Former PayPal CEO Warns AI Threatens ā€œMath Peopleā€

Former PayPal CEO Peter Thiel discussed how AI is bad news for ā€œmath peopleā€ on the Conversations with Tyler podcast.

Key Details:
  • ā€œMy intuition tells me that AI advancements are much worse for the math people than for the word people,ā€ said Thiel.

  • Thiel argues that AI systems have excelled in routine tasks that require complex calculations, data analysis, and pattern recognition.

  • As AI systems automate these routine tasks through mathematical expertise, the value placed on math skills will diminish.

  • Instead, soft skills (i.e., non-technical attributes) paired with critical thinking and authenticity will become more in demand.

  • ā€œI thought everyone should be tested on their ability to play Chess. Then, that idea was undermined by computers in 1997,ā€ Thiel added.

  • In 1997, IBMā€™s ā€œDeep Blue Computerā€ defeated World Chess Champion Garry Kasparov.

  • Thiel suggests AI systems will defeat ā€œmath peopleā€ within the next five years.

Why Itā€™s Important:
  • Many critics of Thielā€™s opinion outline how math skills increase logical thinking and analytical reasoning, which are important skill sets when optimizing AI systems.

  • In other words, no ā€œmath people,ā€ no AI advancements. Just because everyone has access to calculators doesnā€™t mean theyā€™re experts in quantitative analysis.

šŸ©ŗ PULSE CHECK

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XAI

āš™ļøElon Muskā€™s xAI Builds Worldā€™s Biggest AI Cluster

Image Source: Canvaā€™s AI Image Generators/Magic Media

Elon Muskā€™s xAI launched ā€œColossus,ā€ the worldā€™s biggest AI Cluster powered by 100,000 NVIDIA H100 Tensor Core GPUs.

Key Details:
  • xAI focuses on building AI frameworks that accelerate human scientific discovery to advance ā€œour collective understanding of the universe.ā€

  • An AI Cluster is a computer network that combines its power, storage, and memory to process large datasets and accelerate AI workloads.

  • ā€œColossusā€ was built in just 122 days after dropping Oracleā€™s $10 billion multi-year agreement to provide cloud computing to xAI for training AI models.

  • xAI plans to expand ā€œColossusā€ to over 200,000 NVIDIA H100 Tensor Core GPUs and 50,000 NVIDIA H200 Tensor Core GPUs.

  • Musk recently stated that xAIā€™s latest conversational chatbot, ā€œGrok-2,ā€ was only trained on 15,000 NVIDIA H100 Tensor Core GPUs and beat Anthropicā€™s Claude 3.5 Sonnet, Googleā€™s Gemini Advanced, and Metaā€™s Llama 3.

Why Itā€™s Important:
  • ā€œColossusā€ offers the computing power necessary to train, develop, and deploy advanced AI models that surpass human intelligence.

  • ā€œColossusā€ also reduces power constraints for the startupā€™s researchers and developers, giving them a competitive edge in the AI race.

AI RESEARCH

šŸ’ØNous Research Fixes GPU-to-GPU Communication

Image Source: Nous Research/ā€œA Preliminary Report on Distributed Training Over-The-Internet (DisTro)ā€

Nous Research developed ā€œDistributed Training Over-The-Internet (DisTro),ā€ a family of network optimizers that reduces GPU-to-GPU Communication requirements for AI tasks.

Graphics Processing Units (GPUs) are specialized hardware designed to manage heavy computational workloads through parallel processing (i.e., performing mathematical calculations simultaneously).

A single Large Language Model (LLM) like OpenAIā€™s GPT-4 requires continuous GPU-to-GPU Communication to process large datasets and respond to complex user queries.

GPU-to-GPU Communication refers to exchanging data between multiple GPUs to distribute computational tasks and accelerate AI inference processes (i.e., using inputs to generate outputs).

ā€œDisTroā€ reduces the amount of data that needs to be exchanged between GPUs during AI tasks. By minimizing data transfers, ā€œDisTroā€ improves efficiency, increases scalability, and reduces computational costs.

šŸ› TRENDING TOOLS

šŸ—£RetellAI builds lifelike AI voice agents at scale.

šŸ—’Bizplanr generates a professional Business Plan in minutes.

šŸ›ŽKater lets you ask questions about your data in plain English.

šŸ”RedditScout sifts through Reddit comments, so you donā€™t have to.

šŸ¦ ParticleNews curates AI-powered news to help you understand more faster.

šŸ”®Browse our always Up-To-Date AI Tools Database.

šŸ’°FUNDING FRONTLINES

  • Approveit raises a $1M Seed Round for a payments automation software.

  • Creatopy secures a $10M Series A to build an AI-powered advertisement platform.

  • SparkLabs closes a $50M Investor Fund to back AI startups like Anthropic, OpenAI, and xAI.

šŸ’¼WHOā€™S HIRING?

  • Netflix (Los Angeles, CA): Software Engineering Intern, Summer 2025

  • Viam (New York City, NY): Software Engineering Intern, Summer 2025

  • ServiceNow (Santa Clara, CA): Software Engineering Intern, Summer 2025

  • Matroid (Palo Alto, CA): Full Stack Engineer Intern, Computer Vision Products, Summer 2025

  • NVIDIA (Santa Clara, CA): Mixed Signal Design Engineer, New College Grad 2024

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