Researching a company from a science, technology, and market perspective takes a lot of time. In this article, you’ll learn how Mergeflow helps you accelerate this process substantially.
For this article, I estimated the ROI of Mergeflow (1) on time saved exploring topics, and (2) on time spent monitoring of new updates.
Applying large-scale language models outside language: Examples from materials discovery, cybersecurity, and building management
Large language models like GPT or AI21 enable tools for writing texts, chatbots, and other applications. But these models have other applications as well, for example in materials discovery, cybersecurity, and building management.
How can you spot emerging technology innovation at public companies? And how could you do this at scale? Here’s a first, data-driven, attempt at these questions.
Learn how you can use AI-based methods and advanced analytics to discover unmet needs for your technologies or products.
Our first customer at Mergeflow was a very accomplished science entrepreneur. Learn the methods he used to beat “not invented here” syndrome in his organization.
Several companies now use CO2 to make concrete and cement, jet fuel, textiles, plastics, lenses, laundry detergents, and other materials.
What kinds of data can you use for tech maturity estimates? What are the benefits? And how can you use data to spot hypes?
Analyzing yourself into an abyss? Read more about how analysis paralysis happens, why having more information does not always help, and how you can effectively beat analysis paralysis.