Generative AI is Coming for Insurance May 2023 Fintech Newsletter Andreessen Horowitz

Already we are seeing some experimenters using generative AI more effectively than others. To make the most use of this new technology requires using a variety of tools and techniques and knowing how to bounce between them. We predict this will become a marketable skill, combining the creative vision of an artist with the technical skills of a programmer. What’s different now is the amount of computing power available, thanks to faster microprocessors and the cloud.

Over time, industry revenue and profits tend to migrate to whoever owns the end customer unless there is some proprietary and essential source material in the value chain. Nvidia has some of that today and is doing well, followed by the large cloud hosting providers, but these are sure to become commoditized. The AI model builders need to differentiate quickly, or they will soon be at the mercy of the applications that own the most customers. Many application companies can get started quickly by sourcing someone else’s model.

Google Prepares to Launch ‘Gemini’ Generative AI to Challenge OpenAI’s ChatGPT

There has been academic research in this area for a while, including this 2018 project to design levels in the first-person shooter game DOOM using Generative Adversarial Networks (GANs). An entire library of software has been built to assist with procedural generation. Unity’s SpeedTree helps developers generate virtual foliage which you might have seen in the forests of Pandora in Avatar or the landscapes of Elden Ring. Tapping into our desire for imaginative “doll house” play, the agents themselves could also be personalized. Players could craft an ideal agent based on themselves or fictional characters.

We just lived through a stunning example of this – banking reform after the 2008 global financial crisis. The Baptists told us that we needed new laws and regulations to break up the “too big to fail” banks to prevent Yakov Livshits such a crisis from ever happening again. So Congress passed the Dodd-Frank Act of 2010, which was marketed as satisfying the Baptists’ goal, but in reality was coopted by the Bootleggers – the big banks.

Game Dev of Color Expo 2023

Despite a lackluster investment climate in the cryptocurrency domain, Story Protocol’s fundraising signals a shift of focus towards artificial intelligence. Story Protocol, a San Francisco-based technology firm, has received $54 million in funding to combat copyright infringements exacerbated by generative AI technologies. Up until now, UX design has been about translating Yakov Livshits human commands into action, requiring structured, organized, tagged data and operational code. LLMs can consume data in its current form, without any translation necessary. They can consume both structured and unstructured data, which is where the game especially changed, since there’s more than 80 percent unstructured data in the world, primarily video.

There are countless resources—some better than others—attempting to explain how LLMs work. It’s difficult for AI experts to keep up with everything new being published, and Yakov Livshits even harder for beginners to know where to start. There are 32 million small businesses in the U.S., and they represent more than half of net new jobs created since 2000.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

In this post he explores using Stable Diffusion + Dreambooth, popular 2D generative AI models, to generate images of potions for a hypothetical game. The internet opened up a major consumer market by providing services more cheaply, and to more people, online. Now, AI is kicking off a colossal wave of opportunities for startups by making it possible to build scalable online experiences that replicate the benefits of being in person. With expanded context windows in particular, models will be able to process larger amounts of text and better maintain context, including maintaining continuity through a conversation.

Artificial intelligence and biotech are two of the sectors that have been able to buck the current sluggish pace of venture capital spending. So it’s not surprising a startup at the intersection of the two led this week off in a big way. The value of ChatGPT-like technology comes from bringing the cost of producing images, text and other creative projects close to zero, according to Andreessen Horowitz General Partner Martin Casado. With the new investment at hand, Zibra AI will expand its production capacity by hiring more tech engineers.

Models like Stable Diffusion and ChatGPT are setting historical records for user growth, and several applications have reached $100 million of annualized revenue less than a year after launch. Side-by-side comparisons show AI models outperforming humans in some tasks by multiple orders of magnitude. For many applications, AI is not competing with a traditional computer program, but with a human.

It’s tempting to believe that the biggest companies in generative AI will also be end-user applications. In other words, the companies creating the most value — i.e. training generative AI models and applying them in new apps — haven’t captured most of it. But we think the key thing to understand is which parts of the stack are truly differentiated and defensible. This will have a major impact on market structure (i.e. horizontal vs. vertical company development) and the drivers of long-term value (e.g. margins and retention).

Deploy the app

The AI companionship category also fits within this grouping, as the whole value of the product is the very human-like lack of predictability in the interactions; the loss of non-deterministic outputs would cripple the product experience. Another example in this space could include assisted shopping, as an AI’s unexpected and unusual clothing recommendations are exactly what can help shape one’s style and taste. As we move into the next wave of generative AI applications, we expect to see a shift in focus from the generation of information to the synthesis of information. Employees are paid to make decisions based on imperfect information, and not necessarily the quantity of content generated to execute or explain these decisions. Many startups are looking at using generative AI to create believable characters you can interact with, partly because this is a market with such wide applicability outside of games, such as virtual assistants or receptionists. Now compare Red Dead Redemption 2 to Microsoft Flight Simulator, which is not just big, it’s enormous.

Stable Diffusion, for example, is trained on more than 5 billion image/caption pairs, scraped from the web. We will be seeing new game genres invented that were simply not possible without generative AI. We already talked about Microsoft’s flight simulator, but there will be entirely new genres invented that depend on real-time generation of new content.

• Foundation models are a type of generative AI model characterized by their large scale and ability to perform multiple tasks.
• So even though there doesn’t seem to be obvious defensibility endemic to the tech stack (if anything, it looks like there remain perverse economics of scale), we don’t believe this will hamper the impending market shift.
• Each of the companies accepted into the program received an initial investment of $500K and pitched to investors at the Speedrun Demo Day held in Los Angeles in June 2023.
• Pany has assembled a team of experienced games and tech veterans from leading companies like Zynga, Machine Zone, Google, and Snap.
• There are 32 million small businesses in the U.S., and they represent more than half of net new jobs created since 2000.
• These companies often steer towards harder, grittier, and more complex problems or become services companies building bespoke solutions.