Reflection finally delivers its work: 501B-parameter model Beam unveiled, still trailing China’s latest leading open-source models.

Beating AI Express: Hugging Face has open-sourced a Multi-harness reinforcement learning (RL) framework that enables direct integration of existing coding agents such as Claude Code, Codex, and OpenCode into RL workflows for training its open-source models, eliminating the need to build separate training environments for each agent. Large language model firms like OpenAI have long trained models within their proprietary agent environments. Hugging Face has now made this capability a general open-source tool, allowing other teams to leverage existing agents for RL directly. Models no longer need to be trained in only one agent: a single training run can cycle through Claude Code, Codex, OpenCode, and Mini-SWE-Agent to complete tasks, helping the same model adapt to different prompts, tools, and execution logic, and reducing the "specialization bias" that only works well with a single harness. The team tested the framework on a 2.6-billion-parameter small model from Liquid AI. When using identical model weights but switching agents, task pass rates dropped from approximately 62% to 33%. After training across four agent environments, the average pass rate rose from 42.2% to 54.2%, with more balanced performance improvements across different agents compared to training in a single environment.

Beating AI Insight News Brief: a16z has released its 7th edition Consumer AI Ranking. The biannual list tracks the most popular AI products, compiling the top 50 web and mobile AI tools by monthly visits and monthly active users (MAUs) respectively. The new edition has revised its rules: AI products primarily used for adult content will no longer be included in the ranking. This is not due to waning usage – quite the opposite. a16z noted that if the original rules were retained, these products would account for over 20% of the web top 50, or at least 10 spots. As a result, the firm decided to categorize them as an independent segment, excluding them from the overall consumer AI ranking. Mainstream AI assistants like ChatGPT and Claude have strict restrictions on adult content, creating demand for these specialized tools.

Beating AI Express News: AI programming firm Cognition has rolled out Memory and Dreaming features for its AI coding agent Devin. Memory enables Devin to retain user preferences, corrections, and project experience across sessions, while Dreaming automatically reorganizes these memories in the background daily. Users can directly view what Devin has memorized, as well as recent modifications made by Dreaming. These memories are stored in a personal Memory Drive, essentially a persistent Git repository, with content organized primarily in Markdown files. A short MEMORY.md file serves as an entry point and index, loaded into the context at the start of each new session. Devin then searches for relevant memory files based on the current task, similar to how it queries code repositories, eliminating the need to feed the entire memory bank into prompts. Multiple Devin sessions can read and write to the same memory set simultaneously. Each session has its own Git checkout; after modifying memories, changes are committed and merged back into the Memory Drive. In case of concurrent edits, Git flags conflicts, preventing sessions from overwriting each other’s work. Dreaming itself is a background session that runs automatically daily. It reviews past conversations and existing memories, merges duplicate content, deletes temporary or long-unused information, and fills in previously unrecorded experience. Cognition has also open-sourced this framework as the Agent Memory Repo. Other agents like Claude Code and Cursor can similarly store long-term memories as files and manage them via Git. However, the open-source version only provides the memory structure and workflow; features like Devin’s daily automatic Dreaming run require additional configuration.

According to BIT (bit.com) market data, US stocks opened with the Dow Jones Industrial Average up 0.39%, the S&P 500 Index gaining 0.47%, and the Nasdaq rising 0.58%. AI chip stocks rallied broadly: AMD (AMD.O) climbed 2.5%, while Nvidia (NVDA.O), Broadcom (AVGO.O), and Microsoft (MSFT.O) all advanced more than 1%. Constellation Energy rose roughly 10% following the company’s signing of a 20-year power purchase agreement with Google.

Beating AI News: McDonald’s AI Pricing System Faces Antitrust Lawsuit An Illinois customer named Michael Thomas has sued McDonald’s in Chicago federal court, seeking to file a class-action lawsuit on behalf of potentially millions of U.S. consumers. The complaint alleges the fast-food giant used AI to coordinate menu prices between its franchise and company-owned locations, violating U.S. antitrust laws. The suit claims McDonald’s aggregated non-public transaction data from all its stores into a single machine learning “pricing engine” to provide price recommendations to each location. The plaintiff argues franchisees are independent competitors that should set their own prices, adding that pooling rival data and issuing recommendations via a single system could reduce existing price competition between stores. The complaint also directly cites a prior Reuters investigation into the system. McDonald’s denied the allegations, calling the claims “speculative and based on a misunderstanding of the facts.” The company emphasized the AI does not directly set prices for Big Macs or other menu items, noting franchisees retain final pricing authority. McDonald’s previously also published a statement clarifying that price recommendations are merely advisory, and franchisees may choose not to adopt them.

According to market data from BIT (bit.com), the S&P 500 index rose 0.6%, breaking through the previous high set in August to reach a new intraday all-time high.