With our research talk webinar with Dyah Adila on Friday, let's look back at a recent visit we had with Yifan Mai, lead maintainer of the HELM project at Stanford’s CRFM. Mai talked with our researchers about multi-axis LLM evaluation. Read more here:
RESEARCH
-
Cerebras March Newsletter: AI Day Announcements and Insights
By
–
Our March Newsletter is here! Check out the following information: Learn about our announcements leading up to Cerebras AI Day Watch our keynotes, panelist discussions, and fireside chats Read a few articles published about Cerebras Enjoy!
-
Claude 3 excels at summarizing long books but struggles with fact-checking
By
–
"Talk to your documents" is a big use case for AI. This paper tested how good AI was at working with long, new books (like The Fourth Wing). Claude 3 does very well in SUMMARIZING big books. But none of the models do a good job FACT CHECKING claims about books made by others.
-
Technical Knowledge Matters for LLM Understanding and Limitations
By
–
I am not sure the technical explanations are needed to use LLMs well (in fact I am pretty sure they aren’t) but they are useful for understanding their power and limitations.
-
AI Targeting System Gaza: Probabilistic Bias Ethics Concerns
By
–
AI IDing human targets in Gaza based on probabilistic stereotypes (37K people!). People familiar w/AI know how inaccurate such assessments are. Targets' homes are then bombed at night when they (their family, neighbors, pets) are most likely to be home https://
972mag.com/lavender-ai-is
raeli-army-gaza/
… -
AI Ethics and Compassionate Healthcare Innovation
By
–
AI Meets Ethics: Crafting a Compassionate Future in Healthcare https://
linkedin.com/pulse/ai-meets
-ethics-crafting-compassionate-future-healthcare-babin-4golf
…
#ArtificialIntelligence #healthcare #ethics #innovation #technology @PawlowskiMario @JolaBurnett @Fabriziobustama @Shi4Tech @pierrepinna @CurieuxExplorer @stratorob @AkwyZ @antgrasso @enilev -
Essential Mathematics for Machine Learning: GitHub Repository Guide
By
–
Probability, Statistics, Linear Algebra and Calculus. Checkout the Github Repo → http://
github.com/afshinea/stanf
ord-cs-229-machine-learning
… -
ROBOSHOT: Optimizing Foundation Models Without Fine-Tuning
By
–
Coming up this Friday! PhD student Dyah Adila will explain how data scientists can get better performance out of foundation models without any additional fine-tuning. The technique, called ROBOSHOT, applies a kind of lens to model outputs Register now!
-
Deep Learning: Essential Tips and Tricks for Machine Learning
By
–
Deep Learning, Tips and Tricks in Machine Learning
-
Stanford releases comprehensive cheatsheets for ML and advanced mathematics
By
–
Stanford University has released cheatsheets on Machine Learning, Deep Learning, Statistics, and Linear Algebra: