AI is all the rage — particularly text-generating AI, also known as large language models (think models along the lines of ChatGPT). In one recent survey of ~1,000 enterprise organizations, 67.2% say that they see adopting large language models (LLMs) as a top priority by early 2024. But barriers stand in the way.
“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.
A Step-by-Step Guide to Replicating LLaMA Architecture
We’re proud to have 100+ accepted papers At NeurIPS 2023, plus 18 workshops. Several submissions were chosen as oral presentations and spotlight posters, reflecting groundbreaking concepts, methods, or applications. Here’s an overview of those submissions.
The post NeurIPS 2023 highlights breadth of Microsoft’s machine learning innovation appeared first on Microsoft Research.
'AI will evolve to become an undercover operating system for professionals, particularly when it comes to using the technology for research and idea generation.'
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.
Iterating prompts can end up with a super detailed classification context; trying to nail edge cases, to better describe our intent, like in our previous example, not to rely on the LLM definition for ‘ malicious’ but instead to explain how we see malicious snippets.
Consider for example a classic use case — Spam Detection; the base approach will be to train a simple BOW classifier which can be deployed on weak (and therefore cheap) machines or even just to inference on edge devices (totally free).