Ankur’s note: Hey there, and welcome back to Pioneers.

I wanted to start off with a warm welcome to the new subscribers who have joined us in recent weeks. Pioneers is our daily content series at Multimodal. You can view it here and follow on LinkedIn. Let’s dive in to today’s episode with Cory Janssen, Co-CEO of AltaML and former Co-Founder of Investopedia.

As AI technologies advance, companies across various industries are investing heavily to gain a competitive edge. In 2023 alone, AI and generative AI companies raised nearly $50B. However, as the AI industry matures, access to state-of-the-art algorithms and infrastructure is no longer the sole differentiator for success.

Cory Janssen emphasizes that unique, high-quality datasets will be the key to success and outsized advantages. As AI algorithms become more commoditized, the competitive advantage will shift towards companies possessing clean, proprietary datasets tailored to their specific industries. When combined with domain expertise and effective AI strategies, these datasets will enable companies to build powerful, differentiated AI applications that drive real value.

In today’s deep dive with Cory, we will explore the factors contributing to the growing importance of data in the AI landscape and the strategies you can adopt to capitalize on this trend.

In today’s newsletter, I’ll share some key takeaways from our discussion with a link to read the full article and listen to the full interview. Additionally, we are hosting a special episode of Pioneers live from InsurTech NYC on March 20 and 21. During it, we'll interview multiple high-profile attendees about their experience with Generative AI.

How You Can Win the AI Race With the Best Data, Not the Best Algorithms, With Cory Janssen, Co-CEO at AltaML and Former CEO of Investopedia

TLDR

• The competitive landscape for AI is shifting away from a focus on algorithms and infrastructure and towards access to unique, high-quality data.

• The commoditization of AI algorithms and infrastructure has made it easier for companies to get started but harder to maintain a competitive edge based on algorithms alone.

• Industry-specific data holds immense potential for developing powerful, differentiated AI applications that drive real business value.

• Acquiring and leveraging industry-specific data comes with challenges, such as the proprietary nature of datasets, data quality issues, and more.

• Collaborations between data owners (industry domain experts) and AI providers can unlock the full potential of AI in specific sectors.

The Commoditization of AI Algorithms and Infrastructure

In recent years, we’ve witnessed a significant shift towards the commoditization of AI algorithms and infrastructure. What was once the domain of a few tech giants and research institutions is now becoming increasingly accessible to a wider range of companies. This trend is driven by the open-source movement, which has made many cutting-edge AI algorithms freely available; and the rise of cloud computing, which has democratized access to powerful computing resources.

One of the key drivers of this commoditization is the growing availability of open-source AI frameworks and libraries. Projects like TensorFlow, PyTorch, and Keras have made it easier than ever for developers to build and deploy AI models without having to start from scratch. As Cory notes in our interview, "Going back five or six years ago, it was like the wild west, with all these open-source tools... and then all of a sudden you wake up one day and you're like, 'Oh crap, Microsoft just threw a hundred engineers working on this for six months, and now my entire product is a feature.'" This highlights how quickly the AI landscape is evolving and how easily algorithmic advantages can be eroded.

Another major factor in the commoditization of AI is the role of hyperscalers like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. These cloud computing giants have made significant investments in AI infrastructure, offering a wide range of services and tools that make it easier for companies to build, train, and deploy AI models at scale.

"The hyperscalers want to be the utilities over the next 20 or 30 years,” said Cory, “and the best workflows are AI." By providing access to powerful computing resources and pre-built AI services, he says, hyperscalers have lowered the barriers to entry for companies looking to leverage AI.

While the commoditization of AI algorithms and infrastructure has made it easier for companies to get started with AI, it has also made it harder to maintain a competitive edge based on algorithms alone. Instead, the real differentiator will be the ability to access and leverage unique, high-quality data to train industry-specific models.

"There's datasets that don't exist on the internet,” said Cory, “so unless you have a deep understanding of the workflow and unique edges on data, you're not going to have solutions that work in that industry."

As the AI landscape continues to evolve, the focus will shift towards data as the key differentiator, with companies that can access and leverage proprietary datasets being best positioned to succeed.

Multimodal @ Plug and Play: We Made the Final Cut!

On February 27, we presented Multimodal’s unique automation approach at Plug and Play’s exclusive, invitation-only Fintech & Crypto Selection Day. Great news - we made the final cut!

We’ve been selected for P&P’s Fintech Program which connects selected startups with major corporations.

Here’s what that means:

• We’ll get to work with more enterprise clients.

• We’ll deepen our understanding of their core AI / automation challenges.

• We’ll be able to share even better, more valuable, and more practical insights with YOU.

We’re super excited about what’s to come and can’t wait to share our learnings. Stay tuned!

Get Interviewed On Pioneers Live From InsurTech

We are hosting a special episode of Pioneers live from InsurTech on March 20 and 21. During it, we'll interview multiple high-profile attendees about their experience with Generative AI.

If you’re attending, consider spending 15 minutes either day with us. You’ll get a chance to share your thoughts with our 4K+ regular (and many more irregular) listeners, viewers, and readers and exchange ideas with our team.

We will work with you in advance to prepare our Q&A. No surprises or gimmicks.

Please schedule your best time here or get more details at the link below. We are looking forward to meeting you.