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šŸ¤– a16z Stockpiles Over 20,000 AI Chips to Woo Startups

PLUS: OpenAI Partners With LANL for Bioscience Research, Microsoft Drops Observer Role on OpenAIā€™s Board, Microsoftā€™s MInference Tackles Long-Context Tasks

Welcome back AI enthusiasts!

In todayā€™s AI Report:

  • šŸ“¦a16z Stockpiles Over 20,000 AI Chips to Woo Startups

  • šŸ§ŖOpenAI Partners With LANL for Bioscience Research

  • šŸ¤ÆMicrosoft Drops Observer Role on OpenAIā€™s Board

  • āš™ļøMicrosoftā€™s MInference Tackles Long-Context Tasks

  • šŸ› 5 Trending Tools

  • šŸ’°Venture Capital Updates

  • šŸ’¼Whoā€™s Hiring?

Read Time: 3 minutes

šŸ—žRECENT NEWS

ANDREESSEN HOROWITZ (A16Z)

šŸ“¦a16z Stockpiles Over 20,000 AI Chips to Woo Startups

Image Source: Steve Jennings/Getty Images for TechCrunch

Venture Capital (VC) firm Andreessen Horowitz (a16z) reportedly secured thousands of AI chips to provide for its portfolio companies at below-market rates in exchange for equity.

Key Details:
  • The initiative is called ā€œOxygenā€ because the AI chips ā€œBreathe Lifeā€ into AI startups.

  • Video generation platform Luma AI is an early participant in the ā€œOxygenā€ initiative, citing access to AI chips as a key factor in choosing a16z as its lead investor.

  • a16z has already secured thousands of AI chips, with plans to add over 20,000 Nvidia H100 Tensor Core GPUs to offer accelerated computing power for AI-centric tasks.

  • Over the last two years, a16z has invested significantly in generative AI (GenAI), including funding for notable companies like xAI, Mistral AI, and OpenAI.

Why Itā€™s Important:
  • By offering scarce computing resources, a16z is positioning itself as more than just a source of capital.

  • The VC firm is selling ā€œshovelsā€ during a ā€œgold rush.ā€ a16z is stockpiling AI chips (ā€œshovelsā€) and offering them to startups (ā€œminersā€) at below-market rates without being directly involved in the gold mining (ā€œAI developmentā€) itself.

  • In exchange for these AI chips, a16z gets equity in the startups, which gives them a stake in the potential payoff (ā€œthe goldā€) if the startups are successful.

šŸ©ŗ PULSE CHECK

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OPENAI

šŸ§ŖOpenAI Partners With LANL for Bioscience Research

Image Source: Los Alamos National Laboratory (LANL) Screenshot

OpenAI partnered with Los Alamos National Laboratory (LANL) to understand how scientists can safely use multimodal AI models in laboratory settings.

Key Details:
Why Itā€™s Important:
  • Moderna currently uses OpenAIā€™s technology to augment clinical trial development by building data-analysis GPTs designed to tackle large datasets.

  • OpenAIā€™s frontier AI models will assist in performing tasks like transformation (e.g., introducing foreign genetic material into a host organism), cell structure, and cell separation for LANL.

AI DRAMA

šŸ¤ÆMicrosoft Drops Observer Role on OpenAIā€™s Board

Microsoft dropped its observer role on OpenAIā€™s Board of Directors less than eight months after securing a non-voting seat.

Microsoft obtained an observer role on OpenAIā€™s Board of Directors by investing $13 billion into developing the companyā€™s products and services.

OpenAIā€™s new approach toward Microsoft and Apple will involve hosting ā€œregular stakeholder meetings to share progress on our mission.ā€

The decision comes as antitrust authorities, including the Federal Trade Commission (FTC) and Department of Justice (DOJ), continue investigating ā€œwhether investments and partnerships pursued by dominant companies risk distorting innovation and undermining fair competition.ā€

AI RESEARCH

āš™ļøMicrosoftā€™s MInference Tackles Long-Context Tasks

Microsoft unveiled MInference, which stands for ā€œMillion-Tokens Prompt Inference,ā€ to accelerate how Large Language Models (LLMs) process long-context tasks while maintaining accuracy.

When dealing with massive amounts of text containing millions of tokens, a crucial step in LLM processing called ā€œpre-fillingā€ becomes a bottleneck.

ā€œPre-fillingā€ refers to processing the entire context of an input text for LLMs to perform tasks.

Traditional LLMs rely on an ā€œattention mechanismā€ during the ā€œpre-fillingā€ process to compare every token in the input text to understand their relationships.

This comparison process becomes computationally expensive for long-context tasks with millions of tokens. Imagine the mental strain of comparing every word in a long novel to every other word.

Instead of comparing every word in a long novel to every other word, MInference identifies essential sections related to the characterā€™s motivations (e.g., flashbacks, internal monologues, etc.).

MInference only reads the crucial parts of the long novel to process the essential context of an input text and answer user queries quickly with fewer computational resources.

šŸ› TRENDING TOOLS

šŸ“±Prodia adds AI to your app with one API.

šŸ¦¾MathSolver is an interactive math problem solver.

šŸŒCrew helps you hire, pay, and manage the worldā€™s top talent.

šŸ•øReworkd simplifies your data extraction process with end-to-end automation.

šŸ Gendo offers architecture designers stunning AI-enabled CGI in minutes.

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

šŸ’°VENTURE CAPITAL UPDATES

  • Volley raises a $55M Series C for voice-enabled AI games.

  • Index Ventures raises a $2.3B Third Fund to chase AI breakthroughs.

  • Icelandā€™s early-stage investor, Frumtak Ventures, raised a Fourth Fund totaling $87M to use cutting-edge technologies to solve real-world problems.

šŸ’¼WHOā€™S HIRING?

  • HP (Palo Alto, CA): Personal Systems Machine Learning (ML) Intern, Summer 2024

  • Amazon (New York, NY): Applied Science PhD Intern, Fall 2024

  • DataVisor (Mountain View, CA): Software Engineer Intern, Summer 2025

  • Applied Intuition (Mountain View, CA): Product Manager, New Grad

  • OpenAI (San Francisco, CA): Software Engineer, Backend

šŸ¤–PROMPT OF THE DAY

LEADERSHIP

šŸ„Managing Multi-Generational Teams

Imagine youā€™re leading a diverse team with members spanning different generations, including Gen Z, Millennials, Gen X, and Baby Boomers.

How would you foster collaboration, understanding, and productivity among team members with varying work styles, communication preferences, and technological comfort levels?

Share strategies for leveraging each generationā€™s strengths while promoting a culture of mutual respect and effective teamwork.

šŸ“’FINAL NOTE

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