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Most People Can No Longer Tell the Difference Between AI and Human Voices 🗣

Sam Altman on Sora, Energy, and Building an AI Empire

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Welcome to another edition of Horizon AI,

A new study highlights one of the biggest concerns about AI’s rapid progress: just how blurred the line between real and artificial has become.

Let’s jump right in!

Read Time: 4.5’ min

Here's what's new today in the Horizon AI

  • Chart of the week: The Top Countries Driving ChatGPT Traffic in 2025

  • Most People Can’t Tell When a Voice Is AI Anymore

  • Free Resources

  • AI tools to check out

  • Video of the week

TOGETHER WITH TYPELESS

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Chart of the week

The Top Countries Driving ChatGPT Traffic in 2025

  • The graphic shows ChatGPT’s largest markets by country as of August 2025, based on data from Similarweb.

AI News

AI RESEARCH

Most People Can’t Tell When a Voice Is AI Anymore

A new study published in the PLoS One journal shows that most people struggle to tell AI voice clones from real human voices.

Details:

  • Researchers tested 80 voice samples split between human and AI, with the AI group including both generic synthetic voices and human voice clones.

  • Generic AI voices are easier to spot, but cloned voices were mistaken for human 58% of the time, nearly matching the 62% correct identification rate for real voices.

  • The lead author says realistic clones were made using off-the-shelf tools that are cheap and easy to use which raises the stakes for misuse and calls for stronger safeguards.

  • Voice cloning is already used in scams and deepfakes, with older adults at higher risk and rising concerns in politics, media, and entertainment over consent and ownership.

As AI capabilities advance at an alarming pace, similar issues are now surfacing with AI-generated videos and images as well. Recently, Salem police issued warnings about online “AI homeless pranks” that are going viral on platforms like TikTok and Instagram, where photos created with AI looked so realistic that some parents reported them to authorities, creating confusion and extra work for law enforcement.

AI Findings/Resources

📈 AI compute demand is now growing at more than twice the rate of Moore’s Law. To meet this demand, around $500 billion must be invested in data centers each year until 2030. What does this mean?

🤨 The most important OpenAI announcement you probably missed at DevDay 2025

👀 How the AI bubble is being created, according to Bloomberg

AI Tools to check out

💼 Mockin: An AI toolkit that helps UX/UI & Product Designers get clarity, feedback, and interview confidence.

💥 WorkPPT: Make AI presentations in seconds.

📽 Ovi: AI video generator with physics-accurate motion, synchronized audio, and realistic effects.

👀 Poppy AI: A Visual AI tool helps content creators , founders , and marketers make viral content & ads with AI.

 Bing image creator: Turn your words into stunning visuals and engaging videos in seconds — and for free.

Video of the week

Sam Altman on Sora, Energy, and Building an AI Empire

A deep-dive conversation with Sam Altman, covering the company's grand strategy and his outlook on the future of AI, energy, and human creativity.

Altman explains OpenAI's unique vertically integrated approach, combining a research lab, a massive infrastructure operation, and a consumer-facing product, to achieve its mission of building AGI.

He shares his belief that in the near future, AI will be capable of making major scientific discoveries (his personal "Turing test"), and he outlines his vision for how the exploding compute demands of AI will drive a major shift toward nuclear and solar energy.

He also touches on critical topics like the challenges of AI monetization, copyright, and the appropriate regulatory framework for superintelligence.

Some timestamps (you can find more in the video description and in the comments):

0:41 OpenAI’s vision and infrastructure

2:37 Business model and vertical integration

5:08 AGI, Sora, and societal co-evolution

8:01 The future of AI interfaces

9:12 AI scientists and scientific progress

11:44 Reflections on progress and model capabilities

16:17 Sam's experience as CEO & leadership lessons

25:05 Regulation, safety, and societal impact

28:33 Copyright, open source, and content creation

33:15 Energy, policy, and AI’s resource needs

37:07 Monetization and user behavior

43:03 The talent war and personal reflections

45:20 Advice for founders

That’s a wrap!

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Gina 👩🏻‍💻