⚙️ Exclusive Interview: AI & the business of transparency

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Good Morning. An overwhelming majority of you (65%) are concerned about the departure of top safety researchers from OpenAI. The consensus is that Sam Altman will now have to deal with fewer dissenting voices, something that has a lot of you worried.

In other news, Sony Music dipped its toe into the copyright question, sending a letter to 700 AI companies demanding to know if its music was used to train AI models. Sony said it has “reason to believe” its copyright has been violated by these companies.

In today’s newsletter:

• 🏷️ Stability AI is discussing a potential sale

• 💻 Gartner: The biggest barrier to enterprise AI adoption 

• 🤗 Hugging Face is committing $10 million to get GPUs to developers

• 📞 Exclusive Interview: AI & the business of transparency

Stability AI is discussing a potential sale

Stability AI – the startup behind the popular Stable Diffusion image generator – has, according to The Information, talked to at least one potential buyer about a sale. Stability declined my request for comment on the report. 

The potential sale comes as Stability’s revenue (and expenses) are growing. The problem is that the expenses are outpacing the revenue growth. 

• In 2022, Stability generated about $1.5 million in revenue

• In 2023, Stability generated about $8 million in revenue

• In Q1 of 2024, Stability generated less than $5 million in revenue

Meanwhile, Stability lost $30 million during the first quarter of this year, and reportedly owes around $100 million to cloud providers.

Gartner: The biggest barrier to enterprise AI adoption 

If you listen to the analysts, the value proposition of AI is all about the enterprise. Investors — Dan Ives prominent among them — have been really excited about the idea of widespread enterprise adoption, which could result in enormous, sustained revenue streams for the tech firms building AI. 

The revenue, however, isn’t there yet. 

• Sequoia found that in 2023, AI firms spent $50 billion on Nvidia chips and brought in only $3 billion in revenue, a scenario that has led many to believe that the “AI Bubble” is about to burst. 

A recent Gartner survey of corporations across the U.S., U.K. and Germany found that the biggest barrier to enterprise AI adoption is estimating & demonstrating the value of AI projects. 

• Even with 29% of respondents already deploying generative AI, 49% are having a problem finding the actual value of such projects.

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Hugging Face is committing $10 million to get GPUs to developers

Hugging Face, the open-source AI community, said Thursday that it is donating $10 million worth of GPUs to the developer community through a new ZeroGPU program. 

ZeroGPU is accessible through Hugging Face’s Spaces, where multiple users and applications can split portions of available GPU capacity. 

• “AI should not be held in the hands of the few,” Hugging Face CEO Clem Delangue said.

One of the biggest barriers in the development side of the AI world has to do with the cost of compute. 

• Analysts have estimated that a single next-gen, entry-level Nvidia chip could cost a minimum of $30,000.  

This cost barrier plays a significant role in the ability of established Big Tech giants to continue dominating the competition. It also makes it difficult for university researchers to stay ahead.

💰AI Jobs Board:

• AI Scientist: Samsung· United States · San Jose, CA · Full-time · (Apply here)

• Machine Learning Engineer: Splunk · United States · Remote · Full-time · (Apply here)

• Artificial Intelligence Specialist: TechnoGen Inc. · United States · Hybrid - Portland, Oregon · Full-time · (Apply here)

 🗺️ Events: *

• Ai4, the world’s largest gathering of artificial intelligence leaders in business, is coming to Las Vegas — August 12-14, 2024.

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🌎 The Broad View:

• Billionaire Frank McCourt is looking to buy TikTok (Semafor).

• A U.S. cybersecurity official discloses attacks on the country’s mobile network that have occurred in recent years (404 Media).

• The Misinformation Combat Alliance (MCA) is fighting to protect India’s elections (Rest of World).

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RingCentral: AI and the business of transparency 

As I mentioned above, some analysts, venture capitalists and investors are starting to look at the current environment as an AI bubble, akin to the dot-com bubble of the late ‘90s. Part of the reason has to do with privacy and security concerns; a recent Cisco study found that 27% of businesses have banned generative AI because of privacy/security concerns. 

For cloud communications provider RingCentral, the core focus is on transparency and privacy, not just from an ethical standpoint, but as a tenet of its business in AI.

• Paola Zeni, the company’s Chief Privacy Officer, told me that a lack of transparency around AI tools is “really bad for business.”

This transparency goes beyond breakdowns of what customer information RingCentral collects, and goes into the specifics of the data inputs, processing and outputs for the company’s third-party AI-powered tools: how a tool works, and how a tool interacts with customer data.

• “I don’t think companies and enterprises are looking for magic,” she said. “In the business-to-business space, enterprise customers are much more interested in visibility and being able to understand what’s going on.”

Zeni said that for enterprise customers dealing with AI, understanding the risks and potential legal violations — compliance with Europe’s AI Act, for instance — is top of mind. 

My Thoughts: 

There is a fascinating dichotomy between many of the companies producing AI models and the businesses that feel such pressure to adopt them. Broadly speaking, the tech companies are in the business of selling magic. 

OpenAI’s GPT-4o demonstration – in everything from the livestream to Sam Altman’s tweets – was designed to show an instance of science fiction made real. Google’s I/O demos the next day were very much in the same vein. 

• Neither company has been transparent about the data used to build their models (multi-modal or not), as it is currently in their interest to sell people investors on the illusion of intelligence (LLMs are not the real thing).

But this magical, opaque approach — while good at attracting VC cash — is just no good for businesses; this sets up a big roadblock for these companies that are struggling to generate big returns on their huge AI investments, all because they can’t satisfy many enterprise requirements of privacy, security, transparency and explainability. 

What these AI companies need the most right now is solid adoption in the enterprise, but what enterprises need is reliable, understandable tech. As Zeni said, not magic. Right now, what the enterprises need for adoption doesn’t seem to be in line with what Big Tech is selling.

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One last thing👇

That's a wrap for now! We hope you enjoyed today’s newsletter :)

We appreciate your continued support! We'll catch you in the next edition 👋

-Ian Krietzberg, Editor-in-Chief, The Deep View