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Block open-sources AI coding agent Goose, benchmarked against Claude Code and completely free
Block's open-source AI coding agent Goose offers functionality similar to Claude Code, but can run entirely locally, with no subscription fee and no rate limits. Goose has gained over 26,100 stars on GitHub, with 362 contributors and 102 releases, the latest version 1.20.1 released on January 19. It supports any LLM, can run locally via Ollama with open-source models such as Qwen 2.5, and integrates MCP to connect to external services; the trade-off is that model quality, context window, and speed still fall short of commercial solutions such as Claude 4.5 Opus.
Block's open-source AI coding agent Goose offers functionality similar to Claude Code, but can run entirely locally, with no subscription fee and no rate limits. Goose has gained over 26,100 stars on GitHub, with 362 contributors and 102 releases, the latest version 1.20.1 released on January 19. It supports any LLM, can run locally via Ollama with open-source models such as Qwen 2.5, and integrates MCP to connect to external services; the trade-off is that model quality, context window, and spe
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Copilot, Agent Skills and Spreadsheets: TLDR AI's Weekly Roundup
Microsoft launched Copilot Readiness Packages in Microsoft 365, providing administrators with guided assessments and secure deployment presets, and added automatic issue detection and Copilot-driven suggestions in the Teams admin center. Anthropic launched reusable Agent Skills for Claude for Enterprise, which can encode processes such as brand tone, email formatting, and Jira task creation; the standard is open, and there is no additional charge beyond a normal Claude subscription. OpenAI released GPT-5.2 for professional and enterprise use, focusing on long context, structured outputs, and multi-step projects, offering three variants.
Microsoft launched Copilot Readiness Packages in Microsoft 365, providing administrators with guided assessments and secure deployment presets, and added automatic issue detection and Copilot-driven suggestions in the Teams admin center. Anthropic launched reusable Agent Skills for Claude for Enterprise, which can encode processes such as brand tone, email formatting, and Jira task creation; the standard is open, and there is no additional charge beyond a normal Claude subscription. OpenAI relea
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Daily AI Briefing: Zhipu Open-Sources GLM-4.7; MiniMax and Zhipu Pass HKEX Hearings
Zhipu AI has launched and open-sourced GLM-4.7, achieving a state-of-the-art score of 73.8% on SWE-bench Verified and 87.4 on the tool-calling task τ²-Bench, surpassing Claude Sonnet 4.5. MiniMax and Zhipu successively passed Hong Kong Stock Exchange hearings; the former's 2024 revenue grew 782% year-over-year to $30.5 million, while the latter is valued at 24.4 billion yuan, with average daily token consumption reaching 4.2 trillion in November. In the same period, OpenAI released GPT-5.2-Codex, and Google launched Gemini 3 Flash, with response speed improved 3x.
Zhipu AI has launched and open-sourced GLM-4.7, achieving a state-of-the-art score of 73.8% on SWE-bench Verified and 87.4 on the tool-calling task τ²-Bench, surpassing Claude Sonnet 4.5. MiniMax and Zhipu successively passed Hong Kong Stock Exchange hearings; the former's 2024 revenue grew 782% year-over-year to $30.5 million, while the latter is valued at 24.4 billion yuan, with average daily token consumption reaching 4.2 trillion in November. In the same period, OpenAI released GPT-5.2-Codex
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The Shape of AI Capabilities: Jagged Frontiers, Bottlenecks, and Reverse Protrusions
In an article, Ethan Mollick points out that AI capabilities remain distributed in a jagged pattern, that weak spots such as memory have long shown no marked improvement, and that the system as a whole is constrained by its worst link. Taking Google's Nano Banana Pro as an example, he explains that image generation quality was once a bottleneck, and that after it was broken through, NotebookLM could directly generate full-page slides from source materials; he argues that judging where AI is heading should focus on bottlenecks rather than benchmark scores.
In an article, Ethan Mollick points out that AI capabilities remain distributed in a jagged pattern, that weak spots such as memory have long shown no marked improvement, and that the system as a whole is constrained by its worst link. Taking Google's Nano Banana Pro as an example, he explains that image generation quality was once a bottleneck, and that after it was broken through, NotebookLM could directly generate full-page slides from source materials; he argues that judging where AI is head
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Copilot Gets Rolled Out, Gemini Wants Your Calendar
Microsoft Copilot Business launched globally on December 1, offering meeting notes, document drafting, and productivity tools such as Outlook to small and medium-sized businesses at a lower price. Google's Gemini, meanwhile, provides AI summaries for Docs, Sheets, and Slides, and supports audio overviews of PDFs in Drive. OpenAI CEO Sam Altman put ChatGPT into "code red" status, pushing the team to accelerate improvements.
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Ethan Mollick: An opinionated guide to using AI right now
Ethan Mollick has published an opinionated guide to using AI right now, suggesting that people use OpenAI's published real-world usage data to judge when to use free models and when to upgrade to paid. He points out that the four most advanced systems are Claude, Gemini, ChatGPT, and Grok, with paid tiers at $20 per month or about $200 per month; the former suits most people, while the latter is aimed at complex technical and programming needs. For serious work, he recommends manually selecting an Agent model, such as GPT-5 Thinking Extended or GPT-5 Thinking Heavy.
Ethan Mollick has published an opinionated guide to using AI right now, suggesting that people use OpenAI's published real-world usage data to judge when to use free models and when to upgrade to paid. He points out that the four most advanced systems are Claude, Gemini, ChatGPT, and Grok, with paid tiers at $20 per month or about $200 per month; the former suits most people, while the latter is aimed at complex technical and programming needs. For serious work, he recommends manually selecting
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Ethan Mollick: AI agents can now complete real work
In an article in One Useful Thing, Ethan Mollick argues that AI agents have crossed the threshold of being able to complete real work with economic value. He had Claude Sonnet 4.5, using only the paper text and replication data, read the paper on its own, organize files, convert STATA statistical code to Python, and check each item one by one; it successfully reproduced multiple research results, which he then double-verified with GPT-5 Pro. He believes the improvement in agent capability stems from the fact that a small gain in accuracy is enough to complete more steps, and from new models' ability to self-correct; at the same time, he warns that using them without judgment may also produce 17 PowerPoints that nobody needs.
In an article in One Useful Thing, Ethan Mollick argues that AI agents have crossed the threshold of being able to complete real work with economic value. He had Claude Sonnet 4.5, using only the paper text and replication data, read the paper on its own, organize files, convert STATA statistical code to Python, and check each item one by one; it successfully reproduced multiple research results, which he then double-verified with GPT-5 Pro. He believes the improvement in agent capability stems
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Neural Algorithmic Reasoning: Teaching Neural Networks to Execute Classical Algorithms
The Gradient published an article exploring neural algorithmic reasoning, that is, using deep neural networks to capture the computations of classical algorithms such as shortest paths and sorting. The article points out that MIT's "What Can Neural Networks Reason About?" demonstrates that the better the algorithmic alignment, the better the generalization; GNNs are naturally aligned with dynamic programming and outperform architectures with weaker inductive biases on DP execution benchmarks. The author also cautions that algorithmic alignment does not mean one can arbitrarily apply any highly expressive GNN, and out-of-distribution performance remains a key challenge.
The Gradient published an article exploring neural algorithmic reasoning, that is, using deep neural networks to capture the computations of classical algorithms such as shortest paths and sorting. The article points out that MIT's "What Can Neural Networks Reason About?" demonstrates that the better the algorithmic alignment, the better the generalization; GNNs are naturally aligned with dynamic programming and outperform architectures with weaker inductive biases on DP execution benchmarks. Th
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HeyDATA.org builds the personalized AI assistant DATA with Replit Deployments
Steve Moraco built the iPhone digital assistant DATA with Replit, using Apple Shortcuts to invoke OpenAI GPT by voice as a Siri replacement, and integrating Apple Maps, Mail, Calendar, and Notion. DATA includes built-in shortcuts such as Data Mems on-device long-term memory and Whisper audio transcription, and setup only requires a phone number and an OpenAI API key. The service reached over $216,000 in ARR within a few months.
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North Carolina State University team develops self-resetting soft ring jumping robot that jumps continuously over 1,000 times under constant illumination
A research team at North Carolina State University in the United States has published a new self-resetting soft ring jumping robot in the Proceedings of the National Academy of Sciences. It requires no manual resetting or complex control system, relying solely on the "physical intelligence" of liquid crystal elastomer materials and a ring structure, and jumps continuously more than 1,000 times under constant infrared illumination, with a maximum vertical jump height of up to 80 times its own height. The robot can also be adapted for "jump—swim—jump again" amphibious locomotion, and is expected in the future to be used for sensing and monitoring in complex environments such as grasslands, gravel, and shallow water.
A research team at North Carolina State University in the United States has published a new self-resetting soft ring jumping robot in the Proceedings of the National Academy of Sciences. It requires no manual resetting or complex control system, relying solely on the "physical intelligence" of liquid crystal elastomer materials and a ring structure, and jumps continuously more than 1,000 times under constant infrared illumination, with a maximum vertical jump height of up to 80 times its own hei
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English translation is being prepared.
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