Good morning. Apple announced that it is holding its iPhone launch event on Sept. 9.

So, like it or not, Apple Intelligence is coming soon.

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

In today’s newsletter:

AI for Good: California’s wildfire detection system

Last year, ALERT California and CAL Fire created and launched an AI-powered fire detection tool.

How it works: The system is connected to a network of more than 1,000 cameras; when the system detects a potential fire on the live feed, it sends an alert to firefighters and estimates the fire’s potential path and location.  

Why it matters: With wildfires, early detection is critical. Neal Driscoll, ALERT California’s director, said at the time that “remote sensing data and AI have never been more essential to develop effective and time-critical plans for wildfire prevention, protection, mitigation and response.”

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Real World AI: A robot folds a T-Shirt

A new application of real-world AI from Hugging Face features two robotic arms (successfully) folding a T-shirt. 

The details: The system uses neural networks to predict future motor positions from camera inputs. 

It took a little more than 30 seconds (so I can fold a shirt faster), but it did accomplish the task. 

“This type of work is unironically more useful for humanity than building yet another chatbot,” Hugging Face applied policy researcher Avijit Ghosh said. 

Some context: “I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes,” author Joanna Maciejewska said (rather famously) a few months ago. 

But I’ve encountered very few people who would have a problem with using a robot to do their household chores. 

Register today for Ashby’s upcoming launch event

When it comes to ATSs, Ashby is the best (that’s why we use it as our all-in-one recruiting platform at The Deep View). 

Ashby’s got a new feature coming — AI-assisted application review — designed to make it easier for companies to handle high volumes of inbound applications while maintaining a great candidate experience.

On September 10, Ashby will:

Save your spot by signing up for the launch event today.

AI sales agent to boost lead gen by 3x, drive 7x more sales meetings, with personalized follow-up & closure. Set up in 5 min. Chatsimple.*

If you want to get in front of an audience of 200,000+ developers, business leaders and tech enthusiasts, get in touch with us here.

A marketing company wants to use AI to listen in on your conversations 

Many of us have long suspected that our phones are listening in on us, tailoring advertisements accordingly. It’s a feature that Cox Media Group claims to have developed, through something it calls “Active Listening.” 

What happened: In a pitch deck obtained by 404 Media — which was sent to at least one company — CMG said that smart devices capture “real-time intent data by listening to our conversations.” 

The company said that it uses “AI to collect this data from 470+ sources” to design highly targeted advertising campaigns around location-identified audiences that are “ready to buy.” 

The context: CMG’s Active Listening was first reported in December of 2023 by 404 Media. At the time, CMG had content related to Active Listening published on its website; it deleted that content following the initial report. 

I contacted CMG for comment regarding the publication of this slide deck, as it remains unclear if CMG has gone ahead — or plans to — with Active Listening.

Interview: The mismatch of the AI Bubble

We’ve talked often about the AI Bubble — essentially, the idea that, considering the enormous investment that generative AI requires, companies are struggling to see a return to match. There were two main papers that entered into this environment in recent weeks; first, the Sequoia paper, which argued that there is a $600 billion gap in the AI industry. 

The other is the Goldman Sachs report which argued that, not only are companies struggling to see returns on their AI spend, but also that AI as a technology — due to issues of reliability and the enormous cost required to power it — is not as transformative as it has been made to seem.

In the second quarter of this year, funding to AI companies more than doubled to $24 billion, according to Crunchbase data, the highest it’s been since the launch of ChatGPT in 2022. The sector raised $12.8 billion in May, $6.3 billion in June and $5.8 billion in July. 

Outlier spikes aside, and despite the slim month-over-month reductions, we’re seeing trends that indicate a steady increase in monthly funding to AI companies, rather than a decrease.

I spoke with Crunchbase’s senior data editor Gené Teare to try and reconcile these two aspects of the AI world. 

She told me that, in some ways, attempting to align revenues with high investments is “missing the point.” 

Noting that legal tech/AI company Clio clinched the biggest round of July — at $900 million — she said that “there is obviously massive potential in providing services to that sector, but layering in AI obviously delivers much more value to those companies. And so those very big rounds are driven by the promise of AI, and I think they're already seeing some of that promise today.”

As a barometer of that private market, Sarah Tavel, a general partner at venture firm Benchmark, recently wrote that the $600 billion hole will get larger, since the “prize and power of ‘winning’ is too great.” She believes language models will unlock significant economic value as they improve, adding that the “economic value of AGI is constrained only by our imaginations.” (AGI, of course, remains hypothetical technology). 

I don’t think that the bubble has burst. I think the reality is that there are a few bubbles within the industry: a private market bubble, a public market bubble and a general hype bubble. Like a Venn Diagram, the three are linked, but remain separate. 

I think the public market bubble is most liable to burst soon — Nvidia’s performance this week will be a very good indicator of where the public market is at when it comes to AI (if, for instance, Nvidia exceeds expectations — but not by enough — and the stock falls).

The hype train and the VC bubble are more closely linked; both seem to be in the early innings of the hype cycle.

🤔 Your thought process:

Selected Image 1 (Right):

“The left leg looked strange ... but it gets harder and harder to tell.”

Selected Image 2 (Left):

“Hard to tell, but in image 2 bike had the expected mechanics and the t-shirt wrinkles looked real. Image 1 was just vague and I wasn't convinced the bike had pedals, chain etc.”

💭 A poll before you go

Thanks for reading today’s edition of The Deep View!

We’ll see you in the next one.

Here’s your view on AI in music:

Nearly half of the musicians among you said you’d never use AI. Around a third said you would use it in targeted ways, but never for music creation.

More than 40% of the music listeners among you said if they couldn’t be bothered to make it, you won’t be bothered to listen. A third don’t care, so long as there are disclosures.

Down to use it (I’m a musician):