Large Language Models (LLMs) are absolute powerhouses when it comes to generating top-notch #GenAI responses. Yet, #LLMs lack that in-depth, domain-specific knowledge that can make all the difference in certain use cases. Additionally, let's not forget the hefty computing resources and expertise required to develop and deploy them. In my latest article, I delve into why Small Language Models (SLMs) are becoming the go-to choice for specific tasks. With their more focused approach, #SLMs are more efficient than LLMs, and have a smaller compute footprint. Thus, they are more suitable to run locally on workstations or on-prem servers. Check out my article 👇 and ‘d love to hear your thoughts about it https://lnkd.in/diRYaNXF #DellTechEMEA #iWork4Dell #AMD, #Intel, #NVIDIA
Tony Habash
6mo
Interesting take Raed. Thank you.
Cai Gwinnutt
4mo
If "delve" was an intentional inclusion.. kudos
Sam Berberi
6mo
Very informative
Can't wait to start reading your research paper my dear friend Raed Hijer
Shanavas Hameed
6mo
Interesting!
Husband, Father, Development Engineering Manager, Principal Program Manager
6moHi Raed. Perfect timing on your post. I am slowly developing my AI acumen and I had the thoughts... "What if you don't need or can't afford a LLM? Wonder how we asses the minimal sized xLM needed for a given level of quality needed?" Off I go to read your article. Cheers sir and I hope you're doing well.