Slauson Studies: Age of AI

Implications for Startups in 2024

Slauson & Co.
Slauson & Co.
4 min readMar 7, 2024

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In the last year, breakthroughs in artificial intelligence (AI) technology captivated the world, notably with the introduction of ChatGPT in late 2022. As the fervor around web3/cryptocurrencies began to wane, AI emerged as the frontier of innovation, drawing keen interest from startups and venture capital firms. But what is the state of AI in 2024, and how does it influence startups seeking venture capital investment?

As an early-stage venture capital firm, Slauson & Co. champions economic inclusion, striving to democratize access to entrepreneurship for underrepresented founders. This article is part of Slauson & Co.’s research efforts to stay informed while providing early-stage founders insight and resources as they navigate building their businesses.

Overview: The AI Landscape

AI is an umbrella term for technologies designed to make machines smarter, covering machine learning, natural language processing, robotics, and more. This rise in AI over the past year marks a once-in-a-decade technology shift, suggesting that AI integration into software and digital experiences is inevitable, much like the internet’s integration into our daily lives.

Terms and Definitions:

As of 2024, numerous AI technologies are finding applications across different sectors.

  • AI: An umbrella term encompassing technologies that enable machines to mimic human intelligence, including learning, reasoning, and adapting, across various applications. Occasionally outsmarting humans and giving us existential crises.
  • Machine Learning (ML): A subset of AI specializing in systems that learn and make decisions from data. Imagine you could teach your dog to fetch your slippers and predict which pair you’ll want based on the day’s weather. That’s machine learning — except, instead of slippers, it’s data; instead of your dog, it’s a computer.
  • Natural Language Processing (NLP): A subset of AI that enables computers to understand, interpret, and generate human language. It’s like teaching your computer to understand Shakespeare, sarcasm, and maybe even why cereal before milk is the correct answer, allowing systems like Siri or Alexa to communicate with you.
  • Deep Learning (DL): A subset of machine learning that utilizes neural networks to model complex patterns in data. It’s a computer’s way of mimicking the way our brain thinks and solves problems. But instead of neurons, it uses “layers”. Each layer works to solve a different puzzle piece, akin to detectives, forensics, police, coroners, and prosecutors working together to make sense of a crime scene.
  • Generative AI: A type of AI focused on creating new content, such as text, images, music, and more. Generative AI is the artist-in-residence among AI, capable of producing and designing your entire next album.
  • Large Language Models (LLM): Advanced AI models that process, understand, and generate human language, built on massive datasets. These models are like the encyclopedias of AI but with a twist. Instead of just storing information, they can write articles, answer your questions, and even come up with jokes — making them the Renaissance scholars of the AI world, but with a better sense of humor. (This definition was written by ChatGPT that utilizes an LLM)

AI’s impact on startups

AI presents both opportunities and challenges for startups. It can transform ordinary, unscalable ideas into viable investments and enable existing businesses to discover new efficiencies. However, as AI technologies become more accessible, particularly with the proliferation of open-source models, venture investors face the daunting task of sifting through a sea of startups to find those with genuinely innovative and sustainable ideas.

For startups, integrating AI isn’t just beneficial; it’s becoming essential. In the short term, AI can provide a competitive edge through cost savings and improved execution. Over the long term, it’s poised to become a cornerstone technology for the technology industry.

Despite the buzz surrounding AI, it can be difficult for founders to know how to best integrate AI into their businesses and communicate its value effectively. To navigate this, here’s a concise framework to guide founders in evaluating their AI strategy:

Strategy / Vision

  • Can your business stand out as unique, competitive, and scalable without AI?
  • What is your overarching AI strategy, and how will it drive tangible business outcomes?
  • Which areas of the business would benefit from AI enhancements (marketing, operations, IT/engineering, legal, customer service, sales)

Competitive Advantages

  • To what extent is AI integration crucial for your business to distinguish itself from competitors?
  • How does AI adoption enable your business to scale more efficiently, and what distinctive advantage does this offer over your competitors?

Hiring / Talent

  • What strategies will you employ to attract and develop top AI talent necessary to realize your AI vision?

This framework aims to help founders critically assess their AI initiatives and articulate their vision, ensuring their venture not only rides the wave of AI innovation but also stands out as a leader in its application.

We’re looking for exciting startups that leverage AI to enhance their product experience within our framework. If you are a founder or know someone who fits this description, we are interested in learning from you— reach out to us here.

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Slauson & Co.
Slauson & Co.

Slauson & Co. is a Los Angeles based venture capital firm focused on early stage technology investment driven by its mission of economic inclusion.