GM Readers! ☀️

Welcome to the 5th issue of Evolving Internet Insights — a weekly newsletter curating the top stories and our insights on the “Evolving Internet,” which covers everything from AI, Web3 and everything in between.

This week we are seeing how widespread and how global emerging technology AI can be.

Thanks for reading!

Liang and Dan 🙌

P.S. This newsletter will evolve like the internet does, please give us feedback in the comments section or reply directly via email! 🙏

💾 Byte Sized Stories

This week’s top stories with our insights on top.

1. CoreWeave (AI Cloud Provider) Raises $2.3B in Debt ☁️

⚡️ TL;DR: CoreWeave, an AI cloud provider, raised $2.3B in debt. The company will use the funds to purchase more GPUs (high end computer chips for AI computing) to support the demand from the AI boom and build a data center in Texas to work with Nvidia. Nvidia, one of the leading AI chip makers globally, is also an investor in CoreWeave.

⚡️ So What: The most interesting part of the $2.3B raise is that it’s collateralized by the H100 chips (which are produced and manufactured by Nvidia). To scale AI computation and training on increasing amounts of data, companies need more highly specialized chips. But, given global supply issues, manufacturing hubs in Asia are having trouble meeting demand so the chips themselves have gone up in value enough to become precious collateral. Remember, that just this year Nvidia joined the $1T company club that counts less than 10 companies globally.

To give you a sense of how many GPUs are needed, here is a great tweet.👇 Training GPT5 might require all the H100 chips that major tech companies have. While a lot more needs to play out, it is clear that Nvidia is the real winner here. And their sought after chips can now be used to collateralize a $2.3B loan.

Steady folks, deploying more GPUs. 🛳

Read More Here, Here

2. Paypal Launches a Stablecoin 🪙

⚡️ TL;DR: PayPal, one of the largest payment companies, launched its own branded stablecoin PYUSD. A stablecoin is a cryptocurrency backed one-to-one by some real world asset, in this case US Dollars and short-term treasuries. Paxos Trust is the crypto company that will formally issue the stablecoin and manage the reserves backing the stablecoin. Customers will be able to use PYUSD like they use physical dollars, within and outside of PayPal’s ecosystem of apps.

⚡️ So What: It’s an interesting move for PayPal since customers can move their stablecoins easily to other platforms. Currently, users cannot send the funds they have on PayPal to another platform outside of the PayPal ecosystem. You would think the last thing a closed ecosystem wants to do is open up its ecosystem freely. But since there are other open payment ecosystems out there, this move allows PayPal to capture payments that they otherwise might not get. 

It’s PayPal telling its users, use it within our ecosystem, but if you must go outside of our ecosystem, you can now use PYUSD. To their credit, PayPal has been focusing on crypto for a while. In 2020, they introduced crypto services and in 2021, they announced Checkout with Crypto. PYUSD is just a part of a larger strategy to cement themselves as a key player in crypto as the asset becomes a more ubiquitous form of currency. After all, crypto struggles with adoption and PayPal has the secret sauce with 435M users. 🧂

Read More Here, Here

3. Google and Music Labels Want to Embrace AI Music and DeepFakes 🎶

⚡️ TL;DR: Google and Universal Music Group (one of the largest music labels) plan to develop a tool to allow creators to create AI generated music that incorporate the voices of artists and pay artists for using their voices. With the rise and proliferation of AI in creative industries, this is an issue that music labels want to get ahead of. A few months ago, a song made with AI that used Drake’s voice went viral and brought this issue front and center.

⚡️ So What: With generative AI’s pace of development and all the new tools being introduced that will allow anyone to make AI music, the music industry sees the writing on the wall and wants to get ahead of it this time. When Youtube became popular, the music industry spent years fighting copyright infringements because creators were adding unlicensed music to their videos. Eventually, the music industry and Youtube figured out a system to allow creators to pay for the use of that music. From the YouTube agreement alone, the music industry generates ~$2B per year.

At the artist level, some artists, like Grimes, have leaned into AI. Grimes launched an AI tool that allowed individuals to create a song and transform it into Grimes’ voice. She even said she is open to doing a 50/50 split of the royalties from AI songs that use her voice.

We feel that the music industry is finally embracing the old adage of, “if you can’t beat them, join them [and try to build a business model around it].” 😁

Read More Here, Here

📊 Let’s Get Graphic

One visual we couldn’t stop thinking about.

LatAm’s enthusiasm for AI  🤖

⚡️ Takeaway: Latin America (LatAm) as a region is more excited to embrace products and services that use AI as compared to the rest of the world. As we zoom out, emerging markets–usually with large and growing populations–represent massive opportunities for companies and startups to leverage emerging tech. These regions beat Frogger at his own game and leapfrog their “developed” counterparts when it comes to technological adoption. In the same way startups disrupt large companies, emerging markets are the “ones to watch” in this race. 🎮🐸🎮

🧠 Brain Food

One focus topic to feed your brain.

What’s Stopping Businesses from Fully Embracing AI? 🙅‍♀️🙅🏾

It’s clear AI will have widespread impacts on every single company. As a technology, it’s as foundational as the Internet. But like most technologies, who adopts first and who benefits is all over the map. 🗺

⚡️Adoption amongst businesses across different regions

McKinsey’s State of AI Report highlights that North America and Asia Pacific exhibit the highest percentages of companies “regularly using” generative AI tools for work. With North America companies leading the charge at 28% of them regularly using generative AI tools for work, that same figure is 20% for companies in developing markets.

If you ask executives today about AI, you’ll find it’s on the top of their agenda, particularly how to implement and use AI in their businesses. With this, you’d think that a greater percentage of companies would be using AI regularly. (Read: why is that “headline” number only 28%?)

There are two broad questions here:

• What is stopping companies from implementing AI to its fullest extent, especially if executives see AI as their highest strategic priority?

• What is driving the disparity across regions?

⚡️What is preventing companies from fully embracing AI?

Ethan Mollick, a professor at Wharton, outlined in his blog that one of the key reasons why companies are having trouble capturing the benefits from AI is that there aren’t policies that promote its use (read: what is AI and how is this thing going to help me?).

It sounds rather obvious but at the onset of new technologies, everyone tends to focus on the magic of the technology but forget about the other important things that enable and incentivize people within organizations to use the technology.

Technology without purpose leads to minimal adoption.

On the other side of the spectrum, Mollick highlights that some companies have banned their employees from using generative AI tools. This has pushed employees to use AI “in the shadows.” Mollick highlights that these policies ”are causing employees to bring their phones into work and access AI from personal devices.” Ironically, this makes organizations worse off because employees using it in the shadows actually puts more data at risk.

The big “So What” is: as with all new technologies, some folks lean into the change and adopt early, while others try to preserve the status quo. Those early adopters can reap the rewards ahead of their competitors. A “big, hairy, and audacious goal” for companies who understand the power of AI will be how to motivate their workforces to use the technology responsibly and to gain efficiency. Remember, innovation cannot be put back in a bottle. 🍾

⚡️ What is driving the disparity across regions?

There is tremendous interest in LatAm to use AI. In LatAm, 62% of people agree that “products and services using AI have more benefits than drawbacks” compared to 49% for the rest of the world. The challenge for LatAm-based entrepreneurs building with AI is the cost. Most startups use OpenAI and it costs about $0.03 per 750 words. While these figures may feel small at first glance, purchasing power is quite different across regions, and if you are a startup that is looking to use ChatGPT to create content for customers, this cost scales very quickly.

Compared to its North American counterparts, LatAm faces a different problem: they have the interest to adopt the technology, but the costs have not decreased enough for everyone to implement AI (fully) into their businesses.

The “So What” for founders is: emerging markets represent a huge opportunity to build companies that enable wider access to AI for all. While OpenAI may not get cheaper, there is an opportunity to leverage open source models and infrastructure products that meet the cost constraints of entrepreneurs in emerging markets.

Additional Readings: Here, Here

🐇 Down the Rabbit Hole

Some deeper dives to help you get smarter on emerging tech.

1. AI in Education: Great long read on how generative AI can impact education.

2. State of AI in Latam: A super detailed deep dive report highlighting the state of AI in Latam.

3. Supply and Demand of AI Chips: Deep dive report covering how the AI Chips and GPUs industry works.

🌊 Watercooler Talk

Overheard from our community.

Recently, business school friends of ours, many of them with their families in India, sent us this TIME magazine profile on Kayra, an “AI [startup] by the People, and for the People.” In essence, the company collects voice recordings in various mother tongues spoken regionally throughout India, a country with 1.4 billion people, 22 official languages, and at least 780 more indigenous dialects. What makes Kayra unique amongst its competitors is that as a nonprofit, workers are paid “an hourly wage of about $5, nearly 20 times the Indian minimum” and they have ownership of the voice data they create, meaning “whenever it is resold, the workers receive the proceeds on top of their past wages.” 🇮🇳🫰

We saw some great takes reacting to this story, but here were some of the standouts:

• “Nearly everyone in my family’s village uses this, and it has really allowed the elders to step back from their more physical work and take on these Kayra tasks with renewed purpose and pride.”

• “This is a great model, but I hope the team is doing the best it can to sell prospective clients on why their data should be used over others for reasons of bias, wages paid, etc… Otherwise, I do not see this growing past pockets of villages.”

P.S. Got some watercooler talk for us? Share your suggestions in our comments section!

📝 Elite Jobs Corner

From our networks, we curate and connect top founders and companies to rockstar recruits.

⚡️[Web3] Founding Engineer at Karma3 Labs

• What: Karma3 Labs is building the reputation layer for the Internet. As more of our lives continue to move online, knowing who can be trusted and who cannot will be critical.

• Who: Founding team has experience launching and scaling Web2 and crypto startups with successful exits. Deep technical and research talent. One of the Cofounders wrote the algorithm that powers how Google ranks pages. 🤯

⚡️[AI] Founding Lead Infrastructure Engineer at Konko.ai 

• What: Konko AI is a fully managed API that allows developers to easily access, evaluate, choose, fine-tune and deploy large language models (LLMs)

• Who: Founding team with operator and technical experience in AI, venture backed startups, consulting, both HBS grads 🤓

⚡️[VC] Post-Wharton MBA with Early-stage VC Investor Experience Looking for Full-time Role. Meet Stephanie Michael Silva 🇨🇱

• Who: Brings extensive global investment experience from early-stage venture capital to private equity, having interned at L’Attitude Ventures, Gilgamesh Ventures, and 1616 Ventures during her MBA and worked at MLC on late-stage and buyout deals across the fintech, SaaS, healthcare, and consumer sectors in the US and Europe

• Secret Sauce: While much of her career has been as an industry generalist, Stephanie utilized her MBA/MA to deepen her knowledge on Latin America fintech and emerging markets venture capital

• Fun Fact: She was a critical piece in an investment in Comp, a promising Brazilian pre-seed HR tech startup backed by the preeminent VCs in the region. Stephanie led market diligence, wrote the investment memo, participated in the IC, and assisted in allocation negotiations.

📣 Call to Action

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DISCLAIMER: This post is provided strictly for educational and informational purposes only. Nothing written in this post should be taken as financial advice or advice of any kind. The content of this post are the opinions of the authors and not representative of other parties. Empower yourself, DYOR (do your own research).