Big Tech's secret race for AI data

PLUS: U.S. announces CHIPS deal

Welcome, AI enthusiasts.

As the AI arms race heats up, tech giants are scrambling to secure the most valuable resource of all: high-quality training data.

But as the data gold rush grows, so do the murky deals and blurred lines surrounding the content being fed to hungry AI models. Let’s investigate…

In today’s AI rundown:

  • AI training data gold rush surges

  • U.S. strikes CHIPS deal with TSMC

  • New Gemini feature lets you fine-tune answers

  • Jamie Dimon on AI’s transformational impact

  • 6 new AI tools & 4 new AI jobs

  • More AI & tech news

Read time: 4 minutes



Image source: Getty Images

The Rundown: A new report from Reuters revealed new details on how tech giants like Google, Meta, OpenAI, and Apple are racing to secure vast quantities of online data to feed their AI models.

The details:

  • Reuters reports that Meta, Google, Amazon, and Apple all reached a deal with Shutterstock in 2022 following ChatGPT’s debut.

  • The agreement included hundreds of millions of images, videos, and music files for AI training, with deals ranging between $25-50M.

  • Prices for training data range from cents per image to hundreds of dollars per hour of video.

  • Companies are also paying for access to private content archives, including Photobucket's 13B photos and videos and other old internet platforms.

Why it matters: While initially scraping the web, a flurry of lawsuits and the wave of AI-generated content flooding the internet now have tech giants paying big bucks for high-quality content for AI models. The gold rush is a boon for data-heavy platforms eager to cash out — but also treads into murky waters regarding privacy and consent.


The Rundown: OctoAI just launched OctoStack, the GenAI serving stack that lets you run AI models in your own environment — ensuring data privacy and efficient utilization.

Join OctoAI’s live event on April 17 to learn how you can:

  • Run super-efficient inference and maximize utilization

  • Customize your use of any model you chose

  • Deliver highly-reliable GenAI inference at scale


Image source: Getty Images

The Rundown: President Joe Biden just announced that the U.S. and Taiwanese chipmaker TSMC have reached a deal for the company to build three advanced semiconductor factories in Arizona in exchange for $11B in grants and loans.

The details:

  • TSMC will invest a total of $65B and create over 25,000 jobs in the agreement.

  • $50M of funding will be dedicated to developing and training the local workforce.

  • The US aims to produce 20% of the world's leading-edge semiconductors domestically by 2030.

  • The government has now struck five CHIPS Act deals, including $8.5B to Intel and $1.5B to GlobalFoundries.

Why it matters: Amidst growing concerns for both Taiwan’s political (China) and natural (earthquake) vulnerabilities, the U.S. moving to secure its place toward the front of the supply chain is sharp — particularly given the AI chip shortages predicted as demand continues to soar.


The Rundown: In this tutorial, you will learn how to use Gemini's latest update, which lets you fine-tune generated answers and get the output you need without rewriting your entire prompt.


  1. Visit Google Gemini. You will need to sign up or log in with your Gmail account.

  2. Enter your prompt and let Gemini generate an initial answer.

  3. Highlight the specific part of its output that you want to change and click the “Pencil with a star” button. Choose to either modify it with additional instructions, regenerate it, make it shorter/longer, or remove it entirely.

  4. Repeat the fine-tuning process as needed until you have the ideal result.


Image source: JPMorgan Chase

The Rundown: JPMorgan Chase CEO Jamie Dimon just published his annual letter to shareholders, focusing on artificial intelligence — predicting the tech will have sweeping changes to both business and society as a whole.

The details:

  • Dimon compared the “extraordinary consequences” of AI to historic innovations like the printing press, electricity, steam engines, and computers.

  • The CEO said the use of AI has the potential to “augment virtually every job” at the company.

  • Dimon said the firm has already grown its AI talent to over 2,000 experts and data scientists, with over 400 AI/ML use cases in production.

Why it matters: As the CEO of America's largest bank, Dimon's endorsement of AI's transformative potential carries significant weight. The letter is also yet another look at how an industry leader is thinking about AI’s broad implications — and planning internally for a future completely reshaped by the tech.


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Elon Musk said that Grok V2 is currently being trained and expected to be completed in May, also revealing the model “should be better” than GPT-4.

Microsoft announced the opening of a new AI hub in London to advance language models, develop foundation model tooling, and collaborate with AI teams across the company and partners like OpenAI.

Spotify introduced AI playlists in beta, allowing users to generate personalized playlists based on written prompts.

A New York Times report revealed that OpenAI transcribed over 1M hours of YouTube videos for GPT-4 training data, raising legal concerns.

Oracle unveiled a new AI-powered cloud service called Compliance Agent to help banks mitigate anti-money laundering risks.

NTT and Yomiuri Shimbun, two of Japan's most influential companies, released an AI manifesto warning that democracy and social order could collapse if AI is left unchecked.

Poe introduced a new ‘price per message’ monetization model, allowing bot creators to generate revenue each time a user interacts with their creation.



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