The most important question for many startups is 'Why now?' The excitement around large language models is driving this interest, as we now have capabilities we didn't have before.

As AI and large language models evolve, startups may need to hire more software engineers who understand these technologies to automate processes and drive growth post-product market fit.

Many highly skilled professionals are leaving their jobs to start new ventures because they believe large language models (LLMs) are powerful tools for innovation.

By allowing models to think longer, large language models can leverage more compute on the fly, enhancing their intelligence for complex problems.

I believe we are nearing the upper limits of large language models, as the future will likely involve many smaller, specialized models rather than a few large ones. We're at the upper end of large language models, and they're rapidly becoming a commodity as they mature.

Using large language models as prototyping tools can be effective; they allow for rapid development and testing of ideas before creating more specialized models tailored to specific tasks.

The emergence of large language models has allowed us to create a conversational partner that we couldn't build before, enhancing the user experience.

Future breakthroughs in large language models will likely include extending context windows, allowing for more information to be processed and enhancing capabilities.

Large language models are becoming significantly larger and smarter, with AI labs adopting a strategy of scaling more parameters, data, and compute to improve model performance.