From accelerating drug discovery to enabling personalized medicine, global healthcare organizations are turning to Claude for solutions to some of their biggest challenges.
RESEARCH
-
AI Spotlight Series Launches Free Journalist Training Program
By
–
I'm so thrilled to announce the launch of The AI Spotlight Series, a program I designed with the @pulitzercenter to train 1,000 journalists on AI reporting over the next two years. All trainings will be FREE & mostly virtual. Register now to join us! https://
pulitzercenter.org/focus-areas/in
formation-and-artificial-intelligence/ai-spotlight-series
… -
AI Transforms Mental Health Care: Innovation and Applications
By
–
Embracing AI: The New Frontier in Mental Health Care https://
linkedin.com/pulse/embracin
g-ai-new-frontier-mental-health-care-nicolas-babin-jbjkf
…
#healthcare #ArtificialIntelligence #mentalhealth #innovation #technology @PawlowskiMario @JolaBurnett @Fabriziobustama @CurieuxExplorer @Shi4Tech @Khulood_Almani @AkwyZ @antgrasso @smaksked @enilev -
AI Data Extraction Accuracy Requires Human Review
By
–
I included the date mistake (assuming 2019 not 2024) in the video to try to help illustrate that – it's generally great at extracting things correctly if everything is present in the text, but you still have to review what it did because there are many ways things could go wrong
-
GPT-3 training parallels with current AI developments
By
–
Same could have been said after we trained GPT-3.
-
Mixtral 8x22B Released: Training Models from Bed
By
–
Woke up sick today, but Mixtral 8x22B is out. Guess I’m training models from bed.
-
Data Preprocessing for RAG Systems and LLM Applications
By
–
Data preprocessing is critical for building effective RAG systems. Our new short course, Preprocessing Unstructured Data for LLM Applications, taught by @mrobinson0623 of @UnstructuredIO, demonstrates important but sometimes overlooked aspects of RAG systems:
— Andrew Ng (@AndrewYNg) 10 avril 2024
– How to extract… pic.twitter.com/mfhHoc2QfZData preprocessing is critical for building effective RAG systems. Our new short course, Preprocessing Unstructured Data for LLM Applications, taught by @mrobinson0623 of @UnstructuredIO
, demonstrates important but sometimes overlooked aspects of RAG systems: – How to extract -
Griffin vs RecurrentGemma: Recurrence and Global Attention in 2B LLMs
By
–
Recurrence vs global attention in 2B LLMs. Griffin ~= RecurrentGemma
-
Next Gen Products: Leaders’ Claims Require External Audit
By
–
This is a news story about what leaders of these companies claim their next gen products will be able to do. When they’re out on the market, we can/will audit those claims with external opinions as we always do. Re: my book, do read and decide for yourself – and share your views!
-
Grok 2 and 3 need 20k and 100k H100 GPUs
By
–
More info on Grok 2 and 3: The training of Grok's version 2 model required as many as 20,000 Nvidia H100 GPUs, and Musk anticipates that future iterations will demand even greater resources, with the Grok 3 model needing around 100,000 Nvidia H100 chips to train.