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- 🤖 Anthropic launches "Cowork" for non-coding tasks
🤖 Anthropic launches "Cowork" for non-coding tasks
🦾Plus: 📱 Apple taps Google Gemini to power next-gen Siri
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Hey folks! Let’s get into Big Data and AI craziness…
In today's edition: What's Shaping the Future of Data?
🧠How to Choose the Right ML Model for Your Data?
🔢10 Ways to Use Embeddings for Tabular ML Tasks
🤖AI Agent Memory is done; self-learning is here
🧩Qwen's new open-source multimodal RAG stack
📱 Apple taps Google Gemini to power next-gen Siri
📊 Microsoft details growing AI adoption gap
💡 AI Tutorial:How to Convert Any Image Into a Reusable JSON Prompt
🤖 AI Tools and Data Tools to checkout
Anthropic released Claude Cowork, a AI agent feature designed to handle file-based tasks beyond coding, expanding Claude's reach into everyday workflows. Cowork allows users to grant Claude access to a local folder, where the chatbot can read, edit, and create files.
Better prompts. Better AI output.
AI gets smarter when your input is complete. Wispr Flow helps you think out loud and capture full context by voice, then turns that speech into a clean, structured prompt you can paste into ChatGPT, Claude, or any assistant. No more chopping up thoughts into typed paragraphs. Preserve constraints, examples, edge cases, and tone by speaking them once. The result is faster iteration, more precise outputs, and less time re-prompting. Try Wispr Flow for AI or see a 30-second demo.
In this detailed guide, we shall examine the basic steps and requirements that should be considered when selecting the most appropriate machine learning model. From a beginner’s viewpoint and with the furthering of one’s knowledge through a machine-learning course, this guide will serve as a helpful resource to aid in making informed decisions when it comes to model choice.
This article uncovers 10 insightful uses of embeddings to leverage data at its fullest in a variety of machine learning tasks, models, or projects as a whole. Initial Setup: Some of the 10 strategies described below will be accompanied by brief illustrative code excerpts. An example toy dataset used in the examples is provided first, along with the most basic and commonplace imports needed in most of them.
Agno, the open-source AI agent framework, just shipped Learning Machines, a framework that reframes agent memory as an active learning process. The system uses a simple five-function protocol that lets you build custom "learning stores" in about 50 lines of code, whether for user profiles, legal docs, or sales pipelines, with built-in modes ranging from invisible background learning to human-approved updates.
Qwen just dropped their multimodal embedding suite - Qwen3-VL-Embedding and Qwen3-VL-Reranker, built on their Qwen3-VL foundation model. The two-stage pipeline handles text, images, screenshots, and video inputs, with the 8B embedding model scoring 77.8 on MMEB-V2 (currently first place). Both models come in 2B and 8B sizes, support 30+ languages, and let you customize task-specific instructions for that 1-5% performance bump.
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👨💻 Data Tools, Libraries
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AI News:
Apple has signed a multi-year agreement to use Google’s Gemini AI model to power a more capable version of Siri, expected to launch later this year across iPhones and other devices. The partnership is designed to accelerate Apple’s delayed AI roadmap, after internal development setbacks raised concerns that Siri was falling behind rival assistants from Google, OpenAI, and Anthropic.
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Chinese AI lab DeepSeek is reportedly preparing to launch its next model, V4, which could outperform rivals like OpenAI and Anthropic on code generation, according to The Information. It is expected to launch in mid-February 2026. However, the exact date has not been officially confirmed, and sources caution that the timeline could still shift. The release would further strengthen the open-source AI ecosystem as open models continue to narrow the gap with closed systems.
1X has integrated its new video-pretrained world model, 1XWM, into its NEO robot platform. The 1XWM model predicts robot actions by generating text-conditioned video rollouts and then translating them into motion commands through an Inverse Dynamics Model. It uses a 14B parameter generative video model as a backbone, with inference currently taking about 11 seconds per rollout.
OpenAI acquired Torch, a healthcare startup that unifies lab results, medications, and visit recordings. Bringing this together with ChatGPT Health opens up a new way to understand and manage your health.
After failing to compete with Apple and Meta, Amazon acquired Bee to extend Alexa’s reach beyond the home. The wearable records conversations and uses them to suggest to-dos, follow-ups, and insights about how you’re changing over time.
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AI Tutorial
How to Convert Any Image Into a Reusable JSON Prompt
Open Gemini and upload any image.
Paste this instruction: “Convert this image into a JSON prompt, including size and all visual details.”
Let Gemini generate the JSON prompt.
Copy the JSON output.
Edit only the parts you want to change (colors, background, objects, text, style).
Use the modified JSON prompt to recreate or tweak the image.
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A.I. Generated Image of the Day
👀 mental mapping
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