Intel

ComfyUI Full Workshop — first workshop from ComfyAnonymous himself!

Jul 19, 2025 · 51:25

ComfyAnonymous and Yedrick Kosinski present ComfyUI, an open-source node-based canvas for generative AI that has become the top 150 most popular GitHub repos with 78,000 stars and 3 to 4 million active users. Started as a personal project in January 2023, it now supports image, video, audio, 3D, and text models, with 22,000 custom nodes from 3,000 developers. A key feature is embedding full workflows into generated files for easy sharing. The team discusses its story, including ComfyAnonymous's time at Stability AI and founding ComfyOrg, and addresses questions on CFG, VAEs, LoRAs, control nets, API nodes for remote generation, and future plans for cloud inference and improved onboarding.

Foundry Local: Cutting-Edge AI experiences on device with ONNX Runtime/Olive — Emma Ning, Microsoft

Jun 27, 2025 · 22:52

Emma Ning, Principal PM at Microsoft, presents Foundry Local, a platform for building cross-platform on-device AI applications using ONNX Runtime and Olive. She argues local AI is essential for low-bandwidth, privacy-sensitive, cost-efficient, and real-time latency scenarios, noting that modern hardware and optimized models like Phi-4-mini and DeepSeek make it viable. Ning demonstrates Foundry Local's CLI, model benchmarking (Qwen 1.5B at 90 tok/s vs. Phi-4-mini with richer output), and a cross-platform document summarization app built with JavaScript SDK, running identically on Windows and macOS. She also previews a local agent with MCP servers (file system and OCR) that extracts receipt totals using Phi-4-mini. Customer testimonial from Sava (CEO of Pieces) highlights improved memory management and tokens-per-second, while another partner underscores ease of install and hybrid cloud-local solutions.

LLM Safeguards: Security Privacy Compliance Anti Hallucination: Daniel Whitenack

Dec 31, 2024 · 34:10

Daniel Whitenack of Prediction Guard outlines a practical checklist for deploying secure and accurate LLMs in enterprise, addressing hallucination, supply chain vulnerabilities, flaky model servers, data breaches, and prompt injection. He proposes a factual consistency model fine-tuned to detect inconsistencies between AI output and ground truth, rather than relying solely on RAG. For supply chain risks, he recommends a trusted model registry and industry-standard libraries. Data breaches are mitigated via PII detection filters and confidential computing (e.g., Intel SGX) to encrypt server memory. Prompt injection is countered with a custom firewall layer using ensembled classification models. In Q&A, he discusses latency trade-offs using smaller NLP models, pre-production testing for visibility, data access controls via role-based database queries, SIEM integration for monitoring new artifacts like model caches, and additional challenges with agents such as excessive agency, proposing dry-run approvals.