Erica Andersen

Join the Community

21,469

Expert opinions

43,716

Total members

378

New members (last 30 days)

131

New opinions (last 30 days)

28,520

Total comments

Join Sign in

Marketing

smartR AI

Member since

08 Jul

Location

Edinburgh

Latest opinions

Uncovering Genuine AI Insights for Financial Services

Conversational AI and Document Querying: A Path to Business Benefit, Data Control, and Cost Management In the digital age, financial institutions are constantly seeking new ways to leverage technology for extracting valuable insights from their data. The rise of conversational AI and document querying has stirred excitement among financial profess...

13 August 2024 Analytics in Banking

The software ownership dilemma

Software ownership has undergone an interesting evolution. Traditionally, software producers retained ownership, through licensing or the use of Software as a Service (SaaS). However, the AI era provides an opportunity to bring about a significant shift. A key difference in the AI era is the increasing customization of software for individ

12 August 2024 Artificial Intelligence and Financial Services

Data Chaos? AI can save the day

In the era of big data, organizations are increasingly relying on vast amounts of information to drive their decision-making processes. The rapid growth of digital technologies, coupled with the proliferation of data sources, has led to an unprecedented increase in the volume, variety, and velocity of data. However, the reality is that a signific

08 August 2024 Artificial Intelligence and Financial Services

See all 6 opinions by Erica

Latest comments

The software ownership dilemma

Thank you, Ketharaman, for your insightful comment. Your perspective, rooted in decades of enterprise software sales experience, is invaluable.

I agree with your assessment of how COTS and SaaS vendors have historically maintained ownership of their software, including customer-specific data and customizations. Your point about vendors merging these customizations into future versions is astute and often overlooked.

Regarding GenAI, I concur that the initial models contain vast amounts of vendor-supplied training data. However, I believe the situation becomes more complex when we consider model specialization using proprietary company data.

Unlike traditional SaaS products, fine-tuning an AI model with company-specific data fundamentally alters the model itself. The weights of the neural network are adjusted, effectively embedding aspects of the proprietary data into the model's structure. This creates a unique challenge: the data becomes inseparable from the "software" (i.e., the model).

This inseparability is where I foresee potential issues. If a vendor were to use this specialized model for another client, they would inadvertently be transferring knowledge derived from one customer's proprietary data to another. This scenario is fundamentally different from traditional software customizations, where features can be more easily isolated and repurposed.

That said, I appreciate your prediction that GenAI vendors will find it easier to maintain total ownership. It's certainly possible that they will develop novel strategies to navigate these complexities.

Perhaps the solution lies in developing more sophisticated methods of model specialization that can clearly delineate between base knowledge and customer-specific insights. This could allow vendors to maintain control while ensuring customer data privacy.

I'm curious about your thoughts on potential solutions to this dilemma. How do you envision GenAI vendors balancing ownership rights with the need to protect customer-specific knowledge?

15 Aug 2024 08:51 Read comment