GenAI: Hype vs Reality?
A Statistical Analysis
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Tuesday, I publish “Insights” to digest the most relevant startup research & reports, and every Thursday, I publish “Essays” that cover hands-on insights about data-driven innovation & AI in VC. Follow along to understand how startup investing becomes more data-driven, why it matters, and what it means for you.
Current subscribers: 21,935, +220 since last week
Brought to you by VESTBERRY - Portfolio Intelligence Platform for data-driven VCs
Download this free template and create a comprehensive overview of your portfolio directly in Notion.
Our Notion template allows you to consolidate essential portfolio information in a tool many VCs love. Fuel any ad-hoc decision or LP discussion with portfolio data, accessible from anywhere through mobile or desktop.
I love it, you love it, we all love it: Fact-based analysis that help us understand the most pressing topics of our time. While we mostly leverage our data-driven tech stack for sourcing and screening of exciting investment opportunities, a core component of our work is also to spot and properly diligence market trends.
Today, I’m excited to have
share a thought-provoking guest article about the true state of AI. Daniel was one of DoorDash’s first 150 employees and among their first data science hires. As the author of , he regularly dissects the hottest topics with data-centric analysis and makes them digestible for you and me.Thanks a lot for sharing your insightful perspective on the hype around AI with us below, Daniel!
Is AI The Next "Next Big Thing"?
On November 2nd, 2022, crypto news site Coindesk published an article analyzing a balance sheet from Sam Bankman-Fried's trading firm, Alameda Research. The piece raised questions about the financial underpinnings of Bankman-Fried's crypto empire, inducing widespread fears of insolvency and the comingling of consumer funds. This 450-word article kicked off a series of events that led to Bankman-Fried's downfall and the rapid collapse of the industry's second-largest centralized exchange.
The ensuing media response saw news outlets dancing atop the crypto industry's metaphorical grave:
From Vox: Sam Bankman-Fried's trial pulled back the curtain on crypto
From the NYTimes: Crypto Goes on Trial, as Sam Bankman-Fried Faces His Reckoning
From Bloomberg: Court Is in Session for Sam Bankman-Fried, and Crypto
The Bankman-Fried saga proved an ostensibly definitive coda to years of prophecy surrounding the metaverse, decentralized finance, and the NFT-ization of all assets. Mainstream adoption was highly unlikely (at least any time soon). To many, crypto would be remembered as a sensationalistic fad.
Coincidentally, the same month as Bankman-Fried's collapse, a relatively unknown startup called OpenAI released a prototype chatbot called ChatGPT. Within two months, this no-frills tool had garnered over 100 million monthly active users. In February of this year, a reported $4.7 billion was invested in the AI sector, nearly 25% of all global venture funding. With the introduction of one spartan chatbot, artificial intelligence had become the next big thing.
And yet, despite the rapid mainstreaming of AI tools like ChatGPT, Perplexity, and DallE, skepticism abounds. Is this another instance of irrational exuberance? Is this going to be just like crypto?
Indeed, the arrival of large language models and generative AI has spawned many questions regarding the technology's usage, economic potential, and destructive power. So today, we'll examine AI's adoption and reception from two perspectives:
The Usage of AI Tools: Are large language models experiencing increased utilization? Is the AI hype (quantifiably) justified?
Widespread Interpretation of AI's Potential: How are people responding to this recent wave of innovation? What are the perceived future implications of today's progress?
Quantifying AI Adoption
Product enthusiasts often wax poetic about crafting "magic moments" for their users—an instant so delightful that it hooks consumers to that service for life. In my father's case, his ChatGPT magic moment involved a poem about 1980s baseball star Mike Schmidt (a decidedly obscure choice).
Until this point, my dad had primarily understood large language models through media coverage; naturally, he was skeptical. So he gave ChatGPT a prompt he thought impossible: "Write a poem about Philadelphia Phillies all-star third baseman Mike Schmidt in the style of Dr. Seus."
Watching a chatbot craft poetry about his baseball hero tinged with the whimsy of Dr. Seuss proved the most magical of magic moments. With a few catchy rhymes, my father had been converted into a ChatGPT believer.
Since its launch in late 2022, ChatGPT has been responsible for millions of magic moments. Despite the app's minimalist design, OpenAI's chatbot surpassed 1 million users just five days after launch and became the fastest app to acquire 100 million users (though Meta's Threads would break this record a year later). ChatGPT's surge into the mainstream was undeniable, but would the allure surrounding this wave of innovation fade? Would generative AI tools see continued adoption? The answer is yes.
Over the past year, ChatGPT and other popular LLMs have added tens of millions of users, rapidly integrating themselves into the workflows and hobbies of everyday consumers.
A significant driver of LLM adoption lies in their ease of use, as programs like Perplexity and Claude are functionally similar to query engines like Google and Bing. You don't need to understand decentralized wallets, blockchain addresses, and the nuances of staking tokens—you just need to type a prompt.
Over the past year six months, ChatGPT has experienced increased adoption across all age demographics—even in the +65 category. People want to know what all the fuss is about.
A significant portion of AI adopters use these tools frequently, with 22% of YouGov survey respondents reporting weekly or daily usage—an astounding figure for such nascent products.
In August 2023, vaunted research firm Gartner placed Generative AI in the "Peak of Inflated Expectations" segment of its Hype Cycle for Emerging Technologies report.
Gartner characterizes this "Peak" stage as follows: