I was recently going through a Gartner research that laid out the 3 big pillars of Web3. According to Gartner, they are the following:
- The Semantic Web, which is a way of organizing data on the Internet in a way that machines can understand its similarly to the way humans can.
- Artificial Intelligence (AI), which is the ability of machines to perform, learn, and design tasks normally performed by humans.
- Natural language processing, which is the ability of computers to understand human language by extracting meaning from context.
At first I wasn’t sure of how all this would relate to Web3, that I mainly associated to blockchain and the Metaverse technology, but then I understood that this third new wave of the internet and its technologies are all glued together by smarter and AI – especially generative AI, that is a branch of AI that refers to artificial intelligence that can generate brand new content, rather than simply analyzing or acting on existing data. Generative AI models produce text and images: blog posts, program code, poetry, and artwork.
This technology is already so good that it is seen as a potential threat to Google’s search engine business. How so?
Let’s admit it: if you haven’t heard about ChatGPT by OpenAI over the last months, you have likely been living under a rock. It has truly been THE hot topic by the end of 2022 and 2023, especially at a time when the FTX scandal and other not-so-good news have been ruining the reputation of crypto, and where the metaverse buzz has also been fading. That’s exactly when Generative AI, the exact type of AI that ChatGPT is, has been taking the stage. But let’s start off better understanding what this is about: how does Generative AI work?
A generative AI system is designed to produce something new based on its previous experience. Usually, this technology is developed with a technique called machine learning, which involves teaching an artificial intelligence to perform tasks by exposing it to lots and lots of data. The AI eventually learns how to mimic this information. ChatGPT, for example, was trained on an enormous quantity of text available on the internet, along with scripts of dialogue, so that it could imitate human conversations. Another example is Stable Diffusion is an image generator created by the startup Stability.AI that is able to produce an image for you based on text instructions, and was designed by feeding the AI images and their associated captions collected from the web, which allowed the AI to learn what it should “illustrate” based on the verbal commands it received.
While the particular approaches used to build generative AI models can differ, this technology is ultimately trying to reproduce human behavior, creating new content based on the content that humans have already created. In some ways, it’s like the smart compose features you see on your iPhone when you’re texting or your Gmail account when you’re typing out an email.
Let’s admit though that nothing is perfect. This method of building AI can be extremely powerful, but it also has its flaws. In one conducted test, for example, an AI model called Galactica that Meta built to help write scientific papers suggested that the Soviet Union was the first country to put a bear in space, among several other errors and fake news. (The company pulled the system offline in November, after just a few days.) Lensa AI’s Magic Avatar feature, the AI portrait generator, sometimes illustrates people with additional limbs. It also has the concerning tendency to depict women without any clothing.
Ok, but still, it works pretty well – and this is why it represents a potential threat to Google’s search business: The New York Times recently highlighted that Google CEO Sundar Pichai had grown increasingly concerned over the threat of ChatGPT.
Pichai declared ChatGPT’s threat as “code red.” As such, “he has upended the work of numerous groups inside the company to respond to the threat that ChatGPT poses”. Google is particularly concerned about the impact that ChatGPT could have on its search business model, which relies heavily on advertising revenue. ChatGPT can rethink search queries, understand context, and redirect users to other, more relevant sources, potentially rendering the traditional search model unnecessary. As a result, Google has decided not to use ChatGPT in its search algorithms or to integrate it into its search system.
Instead, the company is focusing on developing and releasing new AI-based projects in response to the threat posed by ChatGPT. These projects include a program for creating works of art and images based on descriptions and making the existing LaMDA chatbot technology available to more users.
You might know that ChatGPT is free of charge, so you might wonder: how will it survive? Or is it just made for philanthropic purposes? Well, not really. These systems are usually free because the companies building them want to improve their models and technology, and people playing around with trial versions of the software give these companies, in turn, even more training data. Operating the computing systems to build artificial intelligence models can be extremely expensive, and while companies aren’t always upfront about their own expenses, costs can stretch into the tens of millions of dollars. AI developers want to eventually sell and license their technology for a profit.
There are some of the insights about what this new generative AI industry could look like. OpenAI, which developed the DALL-E and ChatGPT systems, operates under a capped-profit model, and plans to receive $1 billion in revenue by 2024, primarily through selling access to its tech (outside developers can already pay to use some of OpenAI’s tech in their apps). Microsoft has already started to use the system to assist with some aspects of computer programming in its code development app. Stability AI, the Stable Diffusion creator, wants to build specialized versions of the technology that it could sell to individual companies. The startup raised more than $100 million this past October.
When it comes to Big Tech players, they are very interested in all of this, to the point that Microsoft has a very strong interest in investing into Open AI, reportedly putting 10 billion dollars and potentially launching a ChatGPT-enhanced version of Bing in 2023. Interestingly enough, CEO Satya Nadella & his team have been working on fusing OpenAI’s GPT technology into Bing since 2019. Considering the massive interest and signups for ChatGPT since its launch in late 2022, I believe Microsoft probably sensed an opportunity to accelerate its advertising ambitions.
Overall, it’s still too early to suggest that Microsoft’s accelerated work with Bing could see it gain significant share against Google in the near term. All we can say for sure is that ChapGPT has come to transform the way that Generative AI impacts businesses of all sizes and markets.
