Update index.md

index.md

@@ -68,7 +68,7 @@ Large language models (LLMs) have revolutionized a wide range of domains. In par
 | Sept 30 | **Enterprise trends for generative AI, and key components of building successful agents/applications** <br> Burak Gokturk, Google <br> <a href="https://rdi.berkeley.edu/llm-agents-mooc/slides/Burak_slides.pdf">Slides</a> [Original Recording](https://bcourses.berkeley.edu/courses/1535641/external_tools/90481) [Edited Video](https://www.youtube.com/live/Sy1psHS3w3I) | - [Google Cloud expands grounding capabilities on Vertex AI](https://cloud.google.com/blog/products/ai-machine-learning/rag-and-grounding-on-vertex-ai?e=48754805) <br> - [The Needle In a Haystack Test: Evaluating the performance of RAG systems](https://towardsdatascience.com/the-needle-in-a-haystack-test-a94974c1ad38) <br> - [The AI detective: The Needle in a Haystack test and how Gemini 1.5 Pro solves it](https://cloud.google.com/blog/products/ai-machine-learning/the-needle-in-the-haystack-test-and-how-gemini-pro-solves-it?e=48754805) |          
 | Oct 7 | **Compound AI Systems & the DSPy Framework** <br> Omar Khattab, Databricks <br> <a href="https://rdi.berkeley.edu/llm-agents-mooc/slides/dspy_lec.pdf">Slides</a> [Original Recording](https://bcourses.berkeley.edu/courses/1535641/external_tools/90481) [Edited Video](https://www.youtube.com/live/JEMYuzrKLUw) | - [Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://arxiv.org/abs/2406.11695) <br> - [Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together](https://arxiv.org/abs/2407.10930) |          
 | Oct 14 | **Agents for Software Development** <br> Graham Neubig, Carnegie Mellon University <br> <a href="https://rdi.berkeley.edu/llm-agents-mooc/slides/neubig24softwareagents.pdf">Slides</a> [Original Recording](https://bcourses.berkeley.edu/courses/1535641/external_tools/90481) [Edited Video](https://www.youtube.com/live/f9L9Fkq-8K4) | - [SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://arxiv.org/abs/2405.15793) <br> - [OpenHands: An Open Platform for AI Software Developers as Generalist Agents](https://arxiv.org/abs/2407.16741)  |          
-| Oct 21 | **AI Agents for Enterprise Workflows** <br> Nicolas Chapados, ServiceNow | - [WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?](https://arxiv.org/abs/2403.07718) <br> - [WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks](https://arxiv.org/abs/2407.05291) <br> - <a href="https://rdi.berkeley.edu/llm-agents-mooc/assets/tapeagents.pdf">TapeAgents: a Holistic Framework for Agent Development and Optimization</a> |          
+| Oct 21 | **AI Agents for Enterprise Workflows** <br> Nicolas Chapados, ServiceNow <br> <a href="https://rdi.berkeley.edu/llm-agents/assets/agentworkflows.pdf">Slides</a> | - [WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?](https://arxiv.org/abs/2403.07718) <br> - [WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks](https://arxiv.org/abs/2407.05291) <br> - <a href="https://rdi.berkeley.edu/llm-agents-mooc/assets/tapeagents.pdf">TapeAgents: a Holistic Framework for Agent Development and Optimization</a> |          
 | Oct 28 | **Towards a unified framework of Neural and Symbolic Decision Making** <br> Yuandong Tian, Meta AI (FAIR) | - [Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping](https://arxiv.org/abs/2402.14083) <br> - [Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces](https://arxiv.org/abs/2410.09918v1) <br> - [Composing Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets](https://arxiv.org/abs/2410.01779) <br> - [SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems](https://arxiv.org/abs/2210.12547) |          
 | Nov 4 | **Foundation Agent** <br> Jim Fan, NVIDIA |  |          
 | Nov 11 | **No Class - Veteran's Day** |          |