Magic, a startup building AI software engineer coworkers just had a major breakthrough. Per The Information, Magic has claimed to have made a technical breakthrough that could enable “active reasoning” capabilities similar to Q* by OpenAI. They can also process up to 3.5
AGENTS
-
Actor Reflection with Episodic Memory for Agent Learning
By
–
2/ Reflexion The actor reflects on each response, using citations for more actionable critique. Reflections stored in chat history as an "episodic memory buffer" to help the agent learn from past iterations. This better steers the generator in responding to the feedback.
-
Language Agent Tree Search: Balancing Exploration and Reward
By
–
3/ Language Agent Tree Search (LATS) Algorithm combines reflection and Monte-Carlo tree search to find the “best” trajectory for a task. The search process balances exploration and expected reward. It has 4 main steps: 1. Select: pick the best next actions based on the
-
LLM Reflection Architecture: Generator and Reflector Pattern
By
–
1/ Basic Reflection Two LLM nodes: a generator and a reflector. The generator tries to answer the request, while the reflector offers constructive criticism. Python: https://
github.com/langchain-ai/l
anggraph/blob/main/examples/reflection/reflection.ipynb
…
Youtube: https://
youtube.com/watch?v=v5ymBT
XNqtk&t=48s
… -
Reflection Agents Improve AI System Success Rates
By
–
Reflection Agents Reflection can improve the success rate of agents and similar AI systems by instructing the agent to explicitly critique and learn from past actions. This has been shown to improve outcomes across a number of domains, from program synthesis to multi-step
-
AI Agents Reasoning Code at Scale GTC24
By
–
Discover the next wave of #AI on Wednesday, March 20 at #GTC24. Join @imbue_ai CEO Kanjun Qiu and NVIDIA VP of Applied Deep Learning Research Bryan Catanzaro for a discussion on AI agents that reason code at scale. https://
nvda.ws/48jEAEm -
Gemini 1.5’s 10M Context Window Enables Personalization Without Fine-tuning
By
–
With Gemini 1.5's nearly perfect 10 million context you can:
– give entire code bases, 100+ papers, documents
– give it all the information about me (emails, writing examples etc) and have it act entirely like me WITH 0 fine tuning Your entire life can be in its context window -
JSON Agents with Mixtral: Open Source Graph Database Navigation
By
–
JSON Agents with @ollama & LangChain Explore the cutting-edge application of the Open Source Mixtral model from @MistralAI to an agent that navigates a graph database in our latest blog. Authored by @tb_tomaz from @neo4j
, this insightful post demonstrates how leveraging a -
Chat LLMs and AI Agents Webinar Next Week
By
–
If you missed out on our previous Chat LLMs & AI Agents Webinar you can tune in next week! Learn how you can build an AI brain for your organization using our ML and LLM Ops Platform! We will cover the following topics:
•Chat LLMs – customize a ChatGPT like interface and -
Deploy ChatLLMs and AI Agents at Scale with RAG
By
–
WEBINAR Feb. 27: https://
eventbrite.com/e/chat-llms-ai
-agents-use-gen-ai-to-build-ai-systems-and-agents-at-scale-tickets-835992194157?aff=oddtdtcreator
…
—
Use #GenerativeAI to build Chat #LLMs and #AI Systems & Agents at scale.
—
Learn how to deploy the @AbacusAI ChatLLM solution and #RAG techniques to build AI agents that can transform your enterprise tasks (internal and customer-facing)