There are some inherent traits of transformer-based language models that make them unsuitable for certain SaaS applications. These inherent traits are not bugs or problems that can be fixed or patched away as LLMs scale and become smarter.
In my previous blog post, I shared that I was very honored to be chosen as one of the 60 leaders on …more
In 2021, I was privileged to be invited to contribute to an e-book: 60 Leaders on AI. This e-book was put together …more
PROS has fortified its market position through a combination of common moats. With a renowned brand, proprietary AI, strategic customer relationships, and robust R&D investment, we stand as a formidable player. But PROS also has a very distinctive moat – the unique synergy between our Travel and B2B.
The simple and fundamental truth is that not all moats are created equal. The traditional barriers to entry, such as brand recognition, network effects, and economies of scale, while effective in their own right, are still vulnerable to the relentless march of time and competition. Nvidia and TSMC had developed highly unique moats.
Most successful companies that stand the test of time usually have some kind of moat. Cost (economy of scale, efficient supply chain, low-cost supplier, efficient operation), intangible assets (brand, regulation, IPs), and switching cost (network effect, integration complexity) are some common moat strategies.
