Build reliable agents for long-running tasks.
Loop Engineering with @LangChain Deep Agents: add loops that check output, trigger runs on events, and improve the harness from traces across runs. Taught by @sydneyrunkle and @EAGar123.
Enroll for free:
📰From The Batch:
🔄Meta returns to open weights. Muse Spark Open is now the strongest open weights model from outside China, and it takes text, images, video, and audio as input. 🎥
It even runs on two high-memory desktops. 💻
📬
#DeepLearningAI#OpenWeights#AIEngineering
🧟 700 test agents broke into Hugging Face to seize its data.
🧛 Agents sucked up private user data and posted it to the open web.
The cause in both cases was weak test setups and too much access. Read more about AI fears and how to face them in the Halloween issue of our weekly AI newsletter, The Batch:
#DeepLearningAI#AIAgents#AISafety
Have you ever wanted a guide that explains how to maximize results with #DeepLearning? Introducing The Deep Learning Tuning Playbook, which describes a systematic approach to training and tuning neural networks. Check it out ↓
Building an agent that works once is easy, but the real challenge is keeping it reliable in production. Yann LeCun, Andrew Ng + Engineers from @OpenAI, @BlackRock@huggingface, @neo4j and are teaching at AI Dev NYC on:
• Evaluation-driven development
• Building agentic systems
• Scaling and operating in production
📅Nov 30–Dec 1 · Chelsea Piers, NYC
🎟Get your tickets:
#AIDev#DeepLearningAI#AIEngineeringSkills
OpenAI launched new study tools for ChatGPT for Teens. The same day, Common Sense Media gave the app its lowest safety rating. 🔍
In testing, parental alerts didn't reliably fire, and Study Mode often gave away answers. OpenAI disputed the results and asked for a retest.
📬
#DeepLearningAI#ResponsibleAI#AIEngineering
This is the best 2 hours on graph engineering ever recorded, Andrew Ng breaking down how to build agentic knowledge graphs from scratch:
9:14 - your first working agent
33:11 - how loops actually work
1:02:46 - turning loops into working graphs
1:30:15 - agents that improve their own code
1:49:05 - a system that runs the whole thing for you
I've seen $500 courses that teach less than this video alone.
Watch it, then take it further with my step-by-step guide on graph engineering below.
Reconstructing scene depth from video with moving subjects can be very challenging. Now there’s a #DeepLearning approach that generates accurate 3D depth maps from ordinary video, even when both camera and subjects are in motion. Learn more at →
PyTorch 2.15 is out. The rewritten NCCL backend is now the default, with a flight recorder that dumps state on hangs.
Also: faster 4-bit LLM decoding on Nvidia Blackwell, and on Apple Silicon, FP8 plus a MoE decode path that runs 1.32–1.34x faster.
#PyTorch#DeepLearning
Salil Sethi, Applied AI Lead for Strategic Startups at OpenAI, is speaking at AI Dev NYC on building and deploying AI applications, drawing on his work with startups shipping on OpenAI's models.
📅 Nov 30 to Dec 1, Chelsea Piers NYC
🎟️ Tickets:
#DeepLearningAI#AIDevNYC#AIEngineering
NVIDIA Research developed a #deeplearning model that turns rough doodles into photorealistic masterpieces. Like a smart paintbrush, this GANs based tool converts segmentation maps into life-like images: #GTC19
