Investor Deep Dive: Generative AI

In recent years, artificial intelligence (AI) has made significant inroads, enhancing virtually every sector that has figured out how to apply and integrate the application to various endeavors. From predictive analytics to automation, Artificial Intelligence in general is revolutionizing the way industry participants interact with data.

One of the newest and most promising applications of AI’s development that has been broadcasted throughout the news lately: Generative Artificial Intelligence (AI). Generative AI is a type of AI that can learn to generate new data based on existing data sets. What the concept of Generative AI is set out to achieve, has enormous potential implications for firms and users of all shapes and sizes. In this insight, we'll explore what Generative AI is, how it works, and some of the exciting ways the investment community is participating.

Ever since the turn of the century, the developments made in AI alongside the maturing of the technology sector have been rather remarkable, growing almost hand in hand. On the technology side of the equation, hardware efficiencies and upgrades to microprocessors have achieved critical mass for AI to come to life. AI applications such as machine learning and neural networks are powered to churn mass amounts of data to solve new problems, and in turn, the ecosystem as a whole evolves in sophistication. The increasing sophistication of the ecosystem, coupled with the enormous amounts of data ingested, requires the engine powering AI – computing power – to increase in ability as well.

Computing power is the ability of a computer to perform a unique task with precision speed and accuracy. Since 2012, the growth in ability of AI computing power has achieved a doubling every 3.4 months, far exceeding that of Moore’s Law. Simply stated, Moore’s law is an empirical relationship linked to the gains from experience in production that states the number of transistors on a microchip will double every two years, ultimately leading to more computing power. Prior to 2012, on average computing power had only doubled every 2 years, so roughly a near 7x increase in efficiency of resources used. The parallel improvements to the hardware and thus computing power in essence create an impressive and mutually beneficial feedback loop with AI, where the improvement of one enhances the improvement of the other.

With the level of computing power we’ve achieved today, Artificial Intelligence has become increasingly versatile in today’s world, which is owed to the modern chips in today’s technology stack that are capable of performing trillions of calculations per second.1

One of the newest and most promising applications of AI’s development that seems to be broadcasted daily: Generative AI. Generative AI is a type of AI that can learn to generate new data based on existing data sets. This type of AI allows companies to analyze large datasets and make decisions which can be used to enhance a variety of outcomes. For example, Generative AI can be used by companies to appropriately price products or services based on data from similar organizations or market trends to help them operate at maximum efficiency. Additionally, AI-powered algorithms can assist businesses in predicting customer behavior and refine their marketing messaging accordingly. Generative AI builds on traditional AI to revolutionize how companies create and innovate products, while also finding innovative ways to add extra value to untapped applications. This form of technology automates tasks that would normally take significant time and resources from a company, leading to faster development cycles, cost efficiencies, and potentially more meaningful results. Recently, investing in Generative AI has become increasingly popular for businesses who wish to remain competitive and get ahead of the curve with groundbreaking technology.

Investor Interest in Generative AI is Soaring

With this new capabilities, Artificial Intelligence can lead to improved analysis and insights which unlock undiscovered potentials in a variety of industries far beyond its traditional uses. Some of the megacap behemoths including Microsoft, Google, IBM, Amazon and Intel are taking part in this new generation of growth through both a combination of in-house development, as well as participating in corporate venture funding rounds. Microsoft has invested heavily in Generative AI research and development to create a new class of cloud-based intelligent applications that they hope can help organizations gain insights from customer data faster than ever before. Recently in January, the company announced the completion of a $10 billion capital injection into OpenAI, whose application ChatGPT is a front runner in the AI driven Chatbot space.2 This company uses deep learning and natural language processing methods to build AI-driven applications such as automated bots. Google is also leveraging generative AI in its efforts to develop more powerful search algorithms and improve consumer experience. On top of significant resources utilized in developing in house applications such as Google Sparrow and Google Bard to improve customer experiences, the company announced in February it would be investing $300 million in OpenAI rival, Anthropic.3 IBM has been at the forefront of Generative AI for years, creating Watson-powered systems that are able to automate complex tasks such as natural language processing and machine learning. Amazon has used generative AI to power its Alexa voice assistant platform which can now be used for ordering goods online, as well as answering customer questions. Finally, Intel has also heavily invested in generative AI, using it to develop products such as its RealSense facial recognition technology and autonomous driving systems.

Fresh off the back of waning VC interest in Web3 companies, the investment community didn’t have to search long to find a new high profiled investment sector. Moving in a similar fashion to corporate investors, the recent deal activity in the space shows just how well rapid user increases coupled with a good deal of FOMO can light a fire. For reference, in 2020, many of us probably hadn’t heard of generative AI and there was only a mere $271 million invested across 65 companies in the sector. Flash forward to 2022, deal count in the space increased to 110 companies and totaled $2.65 billion.4

Whether it be Visual Media, Text, Speech & Audio, Generative interfaces, or Code – Key focus areas for Generative AI are birthing the next wave of unicorns. The most recent entrants to achieve unicorn status are Jasper AI, a content platform that allows individual users and teams to leverage artificial intelligence to scale their content strategy,5 and Stability AI, a visual art startup that designs and creates images based on text inputs.6

The allure of Generative AI has brought about many interesting headlines in recent days, and while we’ve seen the development of staunch support and backing from notable investors, unequivocally we’ve seen skeptics arise. Generative AI can be powerful and beneficial, but there are many associated risks and limitations that should not be overlooked. First and foremost, Compliance is essential; if ethical best practices are violated during the development or use of an AI system, the intended user could face potential legal liability for any harm caused. Next developers of the technology must also consider economic limitations, as Generative AI presents significant implementation costs and environmental costs that could hinder growth and/or may not be immediately recouped from market returns. Additionally, the technology poses familiarity limits; companies must have deep knowledge of algorithms and advanced computing infrastructure to properly implement generative systems, which is no easy order. As such, those who wish to utilize this technology and or invest in the startups developing it must carefully weigh these risks before making a decision.

Overall, Generative AI, while nascent, offers an interesting investment case for those looking to get involved in the next generation of AI growth. While it has the potential to transform how companies work and operate, it doesn't come without risks. Generative AI enables the creation of realistic data that is outside of a company's control and can’t necessarily be monitored or managed. This can create unforeseeable consequences if not discussed and managed upfront by both the business investing in Artificial Intelligence and its customers. The investment community should approach Artificial Intelligence while taking into consideration all possible implications that could occur with its use.

Sources:

1. Medium, April 2022. "Computing Power"
2. Bloomberg, Jan 2023. "Microsoft Investment in OpenAI"
3. FT, Feb 2023. "Google Investment in Anthropic"
4. CBInsights, Jan 2023. "Generative AI"
5. Crunchbase, Feb 2023. "Jasper AI"
6. Crunchbase, Feb 2023. "Stability AI"