A new study byStanford University suggests that the emergent abilities of large language models (LLM) are caused by a poor choice of evaluation metrics.
At I/O 2023, Google showed that it can catch up with Microsoft/OpenAI in generative AI. But new markets are yet to emerge.
Until recently, it seemed that big tech companies would monopolize the market for large language models. Open-source LLMs are changing that.
Mind the limitations and capabilities of AI from the very beginning, and beware of prototyping an “AI-based” product with a human behind a curtain. Otherwise, there might be no place for AI in such a product in the end.
Three years later after investing in OpenAI, Microsoft has turned the partnership into a successful business with billions of dollars in profits.
By Shalu Jaiswal Image source: 123RF The digital world we live in has never been bigger and more influential. Many fundamental tasks and activities have moved...
From Amazon’s new AI products to the merger of Google Brain and DeepMind, here’s a recap of the latest developments in the AI arms race and their implications.
In the absence of critical analysis, any incidence of cognitive skills in a large language model is a manifestation of word probability patterns, nothing more.
All you need to know about LLaMA, Alpaca, Vicuna, and other open-source alternatives to ChatGPT, OpenAI's flagship large language model (LLM).
ChatGPT represents a major advance in self-learning AI. But to make the leap to AGI, researchers must shift their focus to biologically plausible systems.