AI's $200 Billion Question

ALSO: GPT-4 can read your X-rays (well, sort of)

Author

Zain Kahn
October 09, 2023

Read time: 2.5 minutes

Welcome back, Superhuman

To build, or not to build, that is the question troubling the companies pouring billions into manufacturing the GPU chips that run AI models. Venture Capital firm Sequoia thinks that these companies need to generate about $200 Billion in revenue to justify their current investments.

Plus: A new paper shows that AI can read your X-rays (well, sort of).

TODAY’S MENU

  • AI’s $200 Billion Question: Will investments in GPUs pay off?

  • 5 AI tools to supercharge your productivity

  • Research: AI can read X-rays (sort of)

  • AI In Business: How to adopt AI at your company

  • Tutorial: How to use Google Bard extensions

  • AI Generated Images: Wes Anderson Sci-Fi

TODAY IN AI & TECH

  • Sky High: Amazon launches first satellite in project to provide high-speed internet anywhere in the world.

  • AI Phone: The Economist thinks that AI needs a new device and that iPhones are no longer sufficient.

  • Premium-er: Spotify may launch a super premium subscription with high-quality audio, AI playlists, and more.

  • Hard Times: IT unemployment soars to 4.3% despite overall jobs growth.

  • Art-astic: Check out all the ways people are using ChatGPT’s new image creation feature.

AI’S $200B QUESTION

Companies are pouring billions into GPUs — but where does the revenue come from?

The appetite for GPUs - the chips required to run AI models and apps - seems to be limitless. The sky-high demand is reflected in chip manufacturer Nvidia’s stock market valuation, which has grown over 60x from $18 Billion in 2015 to $1.2 Trillion at its peak this year.

The frenzy is fuelled by the success of AI applications like ChatGPT and Midjourney, which have demonstrated the potential for AI products to generate billions in revenue.

But Venture Capital firm Sequoia raised an interesting question in a blog post recently: With tens of billions being invested into GPU capacity, how do firms expect to generate the revenue to pay it back? The VC firm behind major companies like Instagram, Snapchat and WhatsApp, lays out its argument as follows:

  • For every $1 spent on a GPU, roughly $1 needs to be spent on energy costs to run it.

  • Nvidia will conservatively sell $50 billion in GPUs this year.

  • With the requirement of a 50% margin baked into the assumption, companies will need to generate $200B in lifetime revenue for each year of current GPU expenditure.

  • It is unclear how much of this expenditure is linked to end customer demand.

  • Based on current earnings expectations from AI products, Sequoia estimates that there is going to be a roughly $125B shortfall in required revenue.

While Sequoia thinks this will cause problems in the short run, they see this as a positive trend in the long run. The investment in GPUs will both lower the cost of running AI applications, and create the space for new startups to fill the current revenue gap.

You can read the full blog post here.

TOGETHER WITH YOUAI

What is the application layer of AI, and why do we need it?

Learn why:

  • Foundation models should be thought of as backends — abstracted from consumers.

  • Most consumers shouldn’t (and won’t ever) understand prompting strategies.

  • Model agnostic application layers are key to optimizing the benefits of various foundational AIs as new capabilities emerge.

5 AI Tools to Supercharge Your Productivity

Zendesk: Built on billions of real customer service interactions, Zendesk AI lets you unlock the power of personalized support.

ChartGen: Convert data and spreadsheets into charts instantly with text prompts.

GrowthSchool (sponsored): GrowthSchool makes you a ChatGPT & AI genius in just 3 hours. Worth $49 but free for the first 100 people.

Emma: Create an AI-powered personal assistant in minutes.

We Are Learning: Create amazing interactive stories to help you learn like a pro.

RESEARCH

AI can read your X-rays (sort of)

A new research study published last week says that GPT-4V can read X-rays and produce some pretty impressive reports.

But University Hospital Zurich Radiologist Christian Bluethgen dug into the study and found the results to not be as compelling as the report may imply. According to Bluethgen, GPT-4V can produce some pretty good results when it comes to X-rays, but not good enough.

In the example below, Bluethgen shows that GPT-4V can diagnose a fracture correctly, but gives an incorrect diagnosis of the type of fracture — not ideal if you’re looking to get the right type of treatment for the fracture.

You can check out his analysis below:

AI IN BUSINESS

How to adopt AI at your company

A recent KPMG study revealed an interesting dichotomy: 65% of US business leaders see generative AI as a disruptive force in the next 3-5 years. Yet, 60% are still at least a year away from starting their first AI venture.

A recent Forbes article suggests a measured 6-step strategy that can help you bring AI into your organization and use it effectively:

  1. Focused Deployment: Choose 2-3 core AI use cases that suit company your goals and are obvious in terms of advantages and risks.

  2. Pilot Projects: Begin testing projects for these use cases to demonstrate their usefulness and outcomes.

  3. AI Responsibility and Data Governance: Create company-wide AI standards that include everything from ethical to legal, and make sure data is handled correctly.

  4. Workforce Development: Provide AI training to employees, emphasizing how humans and AI can operate effectively together.

  5. Integrity and Compatibility: After successful tests, gradually increase AI utilization while ensuring compatibility with previous systems.

  6. Continuous Monitoring: Always keep an eye on how AI models and applications are performing and use feedback to improve.

If you want to dig deeper, you can find more details related to risk assessment, pinpointing use cases, and optimizing human resources in the article here.

Other key news from AI in business:

  • IBM’s AI consulting business expected to grow by $1 Billion in 2024

  • Nucleus AI emerges from stealth with 22B model to transform agriculture

  • Enterprise-focused AI startup Cohere launches demo chatbot Coral and Chat API

AI TUTORIAL

How to use extensions for Google Bard

First, you need to access Google Bard.

  • Create a Google account.

  • Visit the Bard website while logged in.

  • On Bard's main page, toggle on desired extensions from the top right corner: Google Flights, Google Hotels, Google Maps, YouTube, and Google Workspace (Gmail, Google Docs, Google Drive).

  • Now use tags like @docs, @drive, or @gmail to direct the chatbot.

  • For example, I used the following prompt to get summaries of my unread emails:

@gmail Summarize my unread emails from today in Gmail

Here’s the result:

Similarly, Bard can help locate emails or docs. It can also provide feedback on writing, suggesting improvements in tone and conciseness.

AI-GENERATED IMAGES

Wes Anderson Sci-Fi

Source: u/One_Sherbert_6904 on Reddit

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