Josh Kim’s Post

With a vision to cut PV costs by 50% with superhuman accuracy, IQVIA’s Uwe Trinks shares how generative AI can make sense of a mountain of data – condensing one week’s work into a single day. Find out more in this fascinating piece for Drug Discovery Trends! https://bit.ly/4jDEQEM

With a vision to cut PV costs by 50% with superhuman accuracy, IQVIA’s Uwe Trinks shares how generative AI can make sense of a mountain of data – condensing one week’s work into a single day. Find out more in this fascinating piece for Drug Discovery Trends! https://bit.ly/41rykKU

Artificial intelligence is transforming the way we approach discovering, designing, and testing new medicines. In the season finale of Two Scientists Walk Into a Bar, we bring Season 5 full circle with a deep dive into machine learning in drug discovery with our expert, Rich Bonneau. In this episode, Rich shares insights on promising AI applications and how his team also carefully considers their data and training sets to navigate existing biases. Check out the full episode: http://spkl.io/6049fZdAh

We asked Sandra Kublik: how do you see the evolution of RAG-based models, and where does Cohere stand within that context? TL;DW ↓ → Cohere is focused on solving big enterprise pain points, not chasing the AGI. Especially building scalable models. → The recently released Command R+ model is big enough to be competitive in terms of reasoning capabilities but small enough to be very cost-effective. → Although Cohere mostly covers text modality use cases, multimodal paths are also in their interests. — (link to the full interview in the comments) #generativeai #genai #llm #rag

🚀 GT Protocol AI Digest No. 2 is here! 🎉 Dive into our latest edition, where we break down the hottest AI trends and news you need to know! From revolutionary healthcare innovations and ethical debates to groundbreaking tech advancements, this digest covers it all. Whether you're a tech enthusiast or just curious, we've got something for everyone! 🔍 Highlights: 🧬 AI-designed proteins transforming healthcare 📚 AI's growing role in education and workforce dynamics 🛑 Ethical concerns with AI-generated content 🚀 Exciting AI innovations in visual tech and industry Don’t miss out—stay ahead in the AI game by reading the full digest now! 👉 Read AI Digest No. 2: https://smpl.is/9kfa5

⭐ Weekly Roundup! ⭐ This week’s article lineup is packed with insights on AI agents. Whether you're a beginner or an experienced practitioner, these pieces will help you navigate the essentials and make informed decisions about integrating agents into your workflows. 🖊️ by Julia Winn, Tarik Dzekman, Tula Masterman, Gadi Singer + more #AIAgent #DataScience

Gen AI is getting all the buzz now. Machine Learning is where the magic happens. Machine Learning draws accurate conclusions from data that we didn't even know that we should consider. How will ML bring your business to the next level? What are you waiting for?

Earlier this week I attended the annual Absolutely Interdisciplinary conference hosted by the Schwartz Reisman Institute for Technology and Society to get myself in the habit of thinking about the social implications of deploying AI technologies. A big theme is how to get an autonomous agent to make ethical decisions when the machine decision has real human consequences? One researcher designs AI to match organs to patients. In such systems, is it ethical for the machine to deny a patient whose quality of life would improve with the transplant but would still have low chances of surviving for a long time? Bonus: interesting slide from a talk on mechanistic interpretability, shows what can go wrong

Artificial intelligence is transforming the way we approach discovering, designing, and testing new medicines. In the season finale of Two Scientists Walk Into a Bar, we bring Season 5 full circle with a deep dive into machine learning in drug discovery with our expert, Rich Bonneau. In this episode, Rich shares insights on promising AI applications and how his team also carefully considers their data and training sets to navigate existing biases. Check out the full episode: http://spr.ly/6040sNDyy