DataFramed

#147 The Past, Present & Future of Generative AI—With Joanne Chen, General Partner at Foundation Capital

Mon Jul 24 2023

AutomationAIInvestmentMarketingStartupsMedia TypesPrivacyData AccessVenture FundingPartnerships

Description

The episode discusses the importance of adopting automation and AI for companies to stay competitive. It covers various areas of AI investment, the impact of AI on different industries, and the opportunities and challenges in implementing AI solutions. The episode also explores the role of AI in marketing, startups, different media types, and automation. Additionally, it delves into venture funding trends, partnerships in the AI space, and the future of automation and AI.

Insights

Adopting Automation and AI is Crucial for Companies

To stay competitive in the future, companies need to invest in applied AI, rethink business models, and automate mundane tasks.

AI is Transforming Various Industries

AI has affected industries such as marketing, legal, engineering, and more, leading to innovation and new billing models.

Considerations for Implementing AI Solutions

Companies should balance AI augmentation with the fear of automation, focus on customer experience, and address privacy concerns and data access issues.

Opportunities and Challenges in AI Adoption

AI adoption presents opportunities for startups, but competition is increasing. Companies should evaluate whether to build or buy AI and understand the implications of different media types.

Venture Funding and Roles in AI Companies

Venture funds are taking longer to raise, and partnerships between major companies are growing in the AI space. Roles in AI companies include language model trainers, data engineers, and more.

The Future of Automation and AI

The number of people starting companies in the AI field is increasing, and organizations need to adopt automation and AI to survive in the future.

Chapters

The Importance of Automation and AI
Investing Strategy and AI Adoption
AI in Marketing and Startups
AI in Different Media Types and Automation
Venture Funding and Roles in AI Companies
The Future of Automation and AI

Summary

Transcript

The Importance of Automation and AI

00:00 - 07:44

To stay competitive in the future, companies need to adopt automation and AI.
Investing in applied AI is important for companies.
There are three broad areas of AI investment: application of AI, machine learning infrastructure, and cybersecurity.
Fast time-to-market strategies can give companies a competitive advantage.
Rethinking business models can lead to industry reinvention.
The legal industry could benefit from AI innovation and new billing models.
AI has affected various industries and sectors.
There are opportunities to automate mundane engineering tasks.
Finding quality companies at the early stage requires a founder-first perspective.

Investing Strategy and AI Adoption

07:20 - 14:50

Investing strategy focuses on founder qualities, team dynamics, and problem statements.
References and customer network are used for due diligence.
Problem areas are extensively researched before investment.
Promising companies in the portfolio include AnyScale and ReBros.
AI is causing changes at various levels of the market.
Consider business metrics and end user problems when buying AI products or services.
Balance between AI augmentation and fear of automation is important culturally.
Hybrid approach with human interface layer is common in AI solutions.
Customer experience should be a goal when integrating AI into processes.

AI in Marketing and Startups

14:20 - 21:42

Using AI can free up time for marketers to focus on brand, interface between marketing and sales, community building, and other aspects.
Founders should quantify and qualify the importance of each person's role in adopting AI tools.
Privacy concerns and issues around data access will require a tooling layer to manage them, creating opportunities for startups.
Deciding whether to build or buy AI depends on engineering resources and organizational capabilities.
Investors behind AI startups can indicate their financial health and longevity.
GPT was a significant moment for the mass market to see the power of AI, leading to more entrepreneurs and companies exploring its applications.
There will be a larger fragmentation of available AI technologies with diverse models created by different players.
Competition in the AI space is increasing, benefiting everyone except previous market leaders.
Companies may continue to focus on specific media types like text, image, or video but there could be crossover in the future.

AI in Different Media Types and Automation

21:15 - 28:09

Companies are focusing on different media types like tech generation, image, and video.
Enterprises adopting AI solutions will want multimodal assets for dealing with different data types.
The compute cost for image and video is more significant than text.
Technology innovation for video is still at the forefront.
Creating videos automatically will likely become less expensive in the future.
AI agents go beyond traditional chatbots and have potential for automation in various industries.
Agents combined with machine learning and workflow building can enhance job performance.
Interface integration and other considerations need to be addressed when implementing AI agents.
Fully automating someone's job or tasks is a serious challenge that requires additional development beyond technology capabilities.
AI companies typically charge per API usage or offer subscription-based pricing models.
There hasn't been significant business model innovation yet in terms of changing how AI companies monetize their products or services.
AI businesses are tools that can make processes more efficient but are not standalone businesses themselves.
High inflation and interest rates have affected investment markets, leading to hesitation in venture capital funding.
Venture funds are taking longer to raise due to increased caution.

Venture Funding and Roles in AI Companies

27:45 - 34:50

Venture funds are taking longer to raise, slowing down transactions and putting emphasis on quality.
Partnerships between companies like Microsoft, Amazon, and Google are increasing in the AI space.
Hyperscalers are becoming foundation model providers and may monetize or use these models to sell other products.
Roles in AI companies include language model trainers, data engineers, and engineers who put AI outputs into context.
Customer service skills and engineering skills are highly valued in the AI industry.
Transitioning from data science to AI involves staying up-to-date with the latest innovations and understanding research papers.
Fundamentals of machine learning still apply in AI; it's just a matter of using different methods for prediction.
The speaker does not have a favorite AI company but is excited about the growing number of people starting interesting ventures in the field.

The Future of Automation and AI

34:30 - 36:30

The number of people and entrepreneurs looking to start a company has exploded, which is a net benefit to the ecosystem.
The speaker is excited about this global benefit rather than any individual companies.
They are making investments in Applied AI for the last 15 years and are open to chatting with early-stage companies at the formation stage.
The speaker advises organizations to adopt automation and AI or risk competing in a world with knives.
In the future, it will be rare to see companies that do not leverage technology like AI.
Organizations should understand their own capabilities, talent pool, and low-hanging fruits to start working on adopting automation and AI.
Evolution and adoption of technology are necessary for organizations to survive.