AI tools like GPT-3 are capable of reading and understanding what an entire customer base is saying and becoming their best advocate.
In the rising excitement about large language models, particularly ChatGPT, people are taking sides. What is largely missing is any critical analysis of what these failures and successes tell us about the relationship between these models and intelligence.
Large language models like ChatGPT are inconsistent at math. Here's why it matters.
ChatGPT is Polanyi's paradox in reverse. It can tell, but it doesn't know.
A new blog post by Sam Altman explains OpenAI's updated roadmap for artificial general intelligence. He answers some questions and leaves many others unanswered.
To understand the power and limits of large language models (LLM), we must separate “formal” from “functional” linguistic competence.
Despite constant developments, the eSIM still has much more to offer. Only time will tell how far the technology can evolve and what exciting benefits it could have stored for us in the future.
The AI competition between Microsoft and Google can have positive results for online search. But it also has bad outcomes for AI research and even uglier results for users.
Google's $300-million investment in Anthropic AI is exemplary of how the arms race between tech giants is affecting AI labs.
With the introduction of low-code/no-code development, the doors of software development are finally being unlocked, enabling anyone to build custom apps regardless of their technical experience or literacy.