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š¤ OpenAI Says Microsoft Isnāt Moving Fast Enough For Them
PLUS: AI Tells Amazon Drivers Which Packages to Deliver, AI Improves Simulation Accuracy in Computational Finance

Welcome back AI enthusiasts!
In todayās AI Report:
š¦AI Tells Amazon Drivers Which Packages to Deliver
šOpenAI Says Microsoft Isnāt Moving Fast Enough For Them
šAI Improves Simulation Accuracy in Computational Finance
š Trending Tools
š°Funding Frontlines
š¼Whoās Hiring?
Read Time: 3 minutes
šRECENT NEWS
AMAZON
š¦AI Tells Amazon Drivers Which Packages to Deliver

Image Source: About Amazon News/Ivy Levine/āNew AI Tech in Amazon Vans Spotlights Packages to Save Drivers Effort and Timeā/Screenshot
Amazon plans to deploy 1,000 Rivian Electric Delivery Vans (EDVs) with Vision-Assisted Package Retrieval (VAPR) by early 2025.
Key Details:
Amazon drivers spend several minutes at each stop looking for packages, which can add up when delivering to hundreds of customers.
VAPR is a new AI-powered device that prevents Amazon drivers from having to manually locate a customerās name and address on the packages. Instead, they look for VAPRās green light, then grab and go!
When packages are loaded into the EDV, theyāre scanned and uploaded to a database.
VAPR is equipped with Computer Vision (CV), which enables it to interpret, analyze, and extract visual data on the packages and compare it to the database.
Then, VAPR projects a green āOā on all the packages that should be delivered at a stop and a red āXā on all the other packages.
Why Itās Important:
In early tests, VAPR has saved Amazon drivers more than 30 minutes during deliveries.
āBefore, organizing packages for the next stop took me up to five minutes. VAPR takes about a minute. Itās made my life so much easier,ā said Bobby Garcia, a driver for Bloomfield Logistics testing the AI-powered device.
OPENAI
šOpenAI Says Microsoft Isnāt Moving Fast Enough For Them

Image Source: Canvaās AI Image Generators/Magic Media
According to The Information, OpenAI is reducing reliance on Microsoft for computing power by partnering with Oracle and building their own AI hardware.
Key Details:
OpenAI CFO Sarah Friar told shareholders that Microsoft āhasnāt moved fast enoughā to supply computing power, slowing down AI projects.
Tensions are rising between OpenAI and Microsoft over the budget, design, and timeline of their joint venture called āFairwater.ā
āFairwaterā involves building new data centers equipped with over 300,000 Nvidia GB200 Grace Blackwell Superchips to handle the demanding computational requirements to run AI applications like ChatGPT.
OpenAI plans to lease an entire data center in Abilene, TX, from Oracle, a major competitor to Microsoft that specializes in offering cloud infrastructure and enterprise software.
Microsoft likely had to āblessā OpenAIās plans with Oracle. However, Microsoft had limited input in the decision-making process.
Why Itās Important:
OpenAI is diversifying the companyās computing resources to gain more control over AI development timelines and reduce reliance on Microsoft.
Despite these shifting dynamics, OpenAI maintains that its relationship with Microsoft remains unchanged. However, this situation highlights the ongoing complexities of their partnership.
š©ŗ PULSE CHECK
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AI RESEARCH
šAI Improves Simulation Accuracy in Computational Finance

Image Source: MIT CSAIL/āMessage-Passing Monte Carlo (MPMC): Generating Low-Discrepancy Point Sets via Graph Neural Networks (GNNs)ā/Screenshot
Imagine youāre tasked with sending firefighters into a skyscraper to inspect for fire hazards. If you randomly assign their positions, they might cluster together on certain floors, potentially missing fire hazards. However, if you outline a strategy, like spreading out uniformly across each floor, youād better assess the skyscraperās fire hazards.
Now, imagine needing to spread out uniformly across hundreds of dimensions. To accomplish this, MIT CSAIL researchers developed Message-Passing Monte Carlo (MPMC), which generates uniformly spaced points across hundreds of dimensions to improve simulation accuracy.
In computational finance, accurate simulations of complex financial systems are crucial. These complex financial systems often involve multiple underlying assets and market conditions.
Consider a portfolio optimization problem involving hundreds of assets. To accurately assess the portfolioās Risk-Return (R/R) ratio, MPMC can accurately simulate its performance under various market conditions.
R/R measures the potential risk and potential return of an investment. A lower ratio means the potential return is greater than the potential risk.
š TRENDING TOOLS
šKvistly is an AI-powered quiz maker.
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šMetaview provides AI-powered interview analytics for recruiters.
š®Browse our always Up-To-Date AI Tools Database.
š°FUNDING FRONTLINES
VanEck launches a $30M Venture Fund to back AI startups.
Distributional raises a $19M Series A to automate AI model testing.
Restoke AI secures a $5.1M Funding Round to offer restaurant process automation solutions.
š¼WHOāS HIRING?
Force Factor (Boston, MA): AI Integration Intern, Summer 2025
Qualcomm (San Diego, CA): Machine Learning {ML} Engineering Intern, Summer 2025
Codazen (Irvine, CA): Full-Stack Engineer, New College Grad 2024/2025
Universal Music GRP. (New York City, NY): Junior Software Developer, New College Grad 2024/2025
NVIDIA (Santa Clara, CA): Mixed Signal Design Engineer, New College Grad 2024
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šFINAL NOTE
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