DeepLearning.AI

🚀 Introducing the new DeepLearning.AI GitHub repository! Ever wished your favorite DeepLearning.AI resources, developer tools, and course artifacts were centralized in one place? We've launched a public GitHub repository designed to help learners and developers easily access: ✅ Developer tools and resources ✅ Supplemental course artifacts ✅ A master course catalog with direct links to course materials ✅ Future updates and community resources Follow the repository and give it a ⭐ to stay up to date with new additions. 🔗 https://hubs.la/Q04kSHDt0

New short course: Fast & Efficient LLM Inference with vLLM, built in partnership with Red Hat and taught by Cedric Clyburn. Learn to quantize an open-source LLM, serve it with vLLM, and benchmark your deployment across speed, cost, and accuracy. Free to enroll: https://hubs.la/Q04jXtMZ0

A vague prompt gives vague advice. Context changes the quality of the answer. The more clearly you explain your situation, constraints, priorities, and goals, the more useful AI becomes for complex decisions. Learn practical prompting techniques in AI Prompting for Everyone with Andrew Ng: https://lnkd.in/edYpmxsS

AI agents seem to be increasingly capable of performing economically valuable tasks, but current benchmarks measure this capability only narrowly. Zora Z. Wang and colleagues at Carnegie Mellon University and Stanford University mapped examples drawn from agent benchmarks to statistics that represent U.S. labor. The mapping revealed a mismatch between the tests, which generally emphasize software development, and the more varied work most people do. Read the full article in The Batch: https://hubs.la/Q04hYSXQ0

China halted Meta’s planned acquisition of Manus, asserting tighter government control over strategically important AI technology. The decision disrupts a popular strategy among Chinese AI startups: relocating abroad to attract Western investment and partnerships. Learn more in The Batch: https://hubs.la/Q04hHRVH0

A few weeks ago I was invited by DeepLearning.AI to give a talk at their AI Dev 26 conference, as kind of a follow-on from the Spec Driven Development course. What a wonderful event brought to us by wonderful people. It was a different kind of talk. It's up now. I'll do some follow-on posts to unpack some of the ideas. https://lnkd.in/eAeNFPbP

“Budget” and “financials” are different words, but embeddings understand they’re related. That’s the foundation behind semantic search and one of the core building blocks of modern multimodal systems. Learn how embeddings power retrieval across text, audio, images, and video in Building Multimodal Data Pipelines: https://hubs.la/Q04hHKC00

📣 New course alert! Excited to share that AI Agents for Image and Video Generation is officially live on DeepLearning.AI! The era of simple text prompts is evolving. This course is built to show developers how to move beyond basic generation and build agentic media workflows. What you’ll learn hands-on: - Prompt Enhancement and Evaluation: Techniques to improve model outputs - Media Agents: Build agents capable of both generating and evaluating images and videos - Agent Skills: Learn how to seamlessly integrate custom skills into your agent workflows A massive thank you to Wafae Bakkali, PhD, Andrew Ng, and Esmaeil Gargari for their incredible partnership in bringing this course to life. 🔗 Enroll and get started today: https://lnkd.in/gHcqba5i

Studies found that Google’s AI system for detecting breast cancer in mammograms identified slightly more cancers than human radiologists. The system caught some cases doctors initially missed. Trials also showed the system could reduce radiologists’ workload. But researchers noted that trust remains a major barrier to clinical adoption. Read our summary of the paper in The Batch: https://hubs.la/Q04hzZxv0

Your AI image generator needs a critic. In our new short course built in collaboration with Google Cloud, you’ll build agents that generate images and video, judge their own outputs, and iterate to improve results. This course explores what happens when AI starts evaluating AI. Taught by Katie Nguyen and Wafae Bakkali, PhD. Enroll for free: https://hubs.la/Q04hkdhM0