Learn the Roadmap to making $100k using LinkedIn & AI (for free)🚀

In just 90 minutes, you’ll learn how to:

👉 Automate lead generation to grow your business effortlessly.
👉 Master LinkedIn's $100K strategy to increase revenue while saving time.
👉 Use AI to secure high-paying roles, bypassing endless applications.

Join Vaibhav Sisinty, a LinkedIn influencer with over 400K followers, who’s transformed the LinkedIn strategies of over 200,000 professionals. Normally valued at $399, this workshop is free for the first 100 readers.

Welcome to AI_Distilled. Today, we’ll talk about:

Techwave

Customize how Claude responds: Concise, Explanatory, or Formal

RunwayML: Introducing Frames

Anthropic introduces the Model Context Protocol:

SmolVLM - small yet mighty Vision Language Model

Cursor announces new code editor UI and agent

Awesome AI:

Paperguide: AI Research Assistant & Chat with PDF

CapGo AI: Spreadsheet That Fills Itself

AI Code Review for Developers | Trag

Conversational AI Survey with Real-time Follow ups

SagaLabs: Earn 200x More with In-context AI translation from the world

Masterclass:

ControlNets for Stable Diffusion 3.5 Large — Stability AI

Automatically generating cloud configurations: Introducing RAGformation

Boost your Continuous Delivery pipeline with Generative AI | Google Cloud

Creating with Video to Video on Gen-3 Alpha and Turbo – Runway

Model-Based Transfer Learning for Contextual Reinforcement Learning

HackHub:

Andrew Ng releases an open-source Python framework to swap between LLMs with one line of code

OpenInterpreter/open-interpreter: A natural language interface for computers

ItzCrazyKns/Perplexica: Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI

souzatharsis/podcastfy: An Open Source Python alternative to NotebookLM's podcast feature: Transforming Multimodal Content into Captivating Multilingual Audio Conversations with GenAI

black-forest-labs/flux: Official inference repo for FLUX.1 models

Cheers!

Shreyans Singh

Editor-in-Chief, Packt

Scale your scrapers with Apify’s Black Friday Boost plan

Get a 30% prepaid usage bonus on Apify this Black Friday. Scrape data for app integrations, performance tracking, competitive research, or custom pipelines. Use pre-built scrapers, build your own from scratch, or use quick-start code templates. The Boost plan ends December 5 - grab it while you can!

Customize how Claude responds: Concise, Explanatory, or Formal

Anthropic has introduced a new feature for its Claude AI assistant that allows users to customize its writing style to match their own or adjust it for specific tasks. Users can choose from three preset styles—Formal, Concise, and Explanatory—or create personalized styles by uploading sample text for Claude to mimic. This feature aims to make interactions feel more natural and tailored, whether for technical documents, professional emails, or casual chats.

RunwayML: Introducing Frames

Runway's new image generation model, Frames, offers advanced stylistic control and visual fidelity, allowing creators to design consistent yet creatively flexible visuals. Integrated into Gen-3 Alpha and the Runway API, Frames helps users craft detailed aesthetic worlds, from cinematic portraits to retro-inspired designs. Frames aims to redefine creative workflows by enabling precise and imaginative visual storytelling.

Anthropic introduces the Model Context Protocol:

Anthropic has introduced the Model Context Protocol (MCP), an open-source standard aimed at improving how AI assistants access and use data from various sources, like business tools and content repositories. MCP enables two-way connections between AI models and data systems through "MCP servers" and "MCP clients," simplifying integration and reducing the need for custom connectors. promising to create more seamless and scalable AI integrations, MCP faces competition from proprietary alternatives like OpenAI’s "Work with Apps,".

SmolVLM - small yet mighty Vision Language Model

SmolVLM is a highly efficient and compact 2-billion-parameter Vision-Language Model (VLM) that delivers state-of-the-art performance for its size and memory usage. Designed for speed, memory efficiency, and ease of customization, SmolVLM is fully open-source under the Apache 2.0 license, with tools, training recipes, and datasets readily available. Its three variants—Base, Synthetic, and Instruct—support fine-tuning and out-of-the-box applications. By optimizing image token encoding and leveraging innovative architecture, SmolVLM runs effectively on smaller devices like laptops, offering fast inference and low GPU memory usage.

Cursor announces new code editor UI and agent

Cursor's 0.43 update transforms the AI-powered code editor into a more efficient and developer-friendly tool. Key features include a unified workspace with the redesigned Composer UI, advanced automation for debugging and package installation via the Composer Agent, and enhanced semantic search for faster, context-aware results. The update also introduces proactive debugging with the experimental BugFinder tool, visual cues for easier file management, and context-aware coding suggestions.

Paperguide: AI Research Assistant & Chat with PDF

CapGo AI: Spreadsheet That Fills Itself

AI Code Review for Developers | Trag

Conversational AI Survey with Real-time Follow ups

SagaLabs: Earn 200x More with In-context AI translation from the world

ControlNets for Stable Diffusion 3.5 Large — Stability AI

Stable Diffusion 3.5 Large introduces three new ControlNets—Blur, Canny, and Depth—designed to enhance image generation precision. Blur enables high-fidelity upscaling for detailed visuals, Canny uses edge maps for structured illustrations, and Depth leverages depth maps for architectural and 3D applications. These models are free for non-commercial and small-scale commercial use.

Automatically generating cloud configurations: Introducing RAGformation

RAGformation is an open-source AI tool designed to simplify cloud configuration by automating the selection of services, cost estimation, and architecture design. Using natural language input, it generates tailored cloud setups, including visual flow diagrams, pricing details, and a comprehensive blueprint. Powered by Retrieval-Augmented Generation (RAG) and tools like LlamaIndex and Pinecone, RAGformation dynamically adjusts recommendations based on user preferences and budgets.

Boost your Continuous Delivery pipeline with Generative AI | Google Cloud

Generative AI, such as Google Cloud's Gemini models, enhances software development by automating repetitive tasks and improving code quality throughout the development lifecycle. Beyond assisting in coding within IDEs, AI can streamline continuous delivery pipelines by automating code reviews, generating release notes, and detecting potential issues early. For example, integrating Gemini into a CI/CD pipeline allows developers to receive AI-driven feedback on pull requests and summaries of code changes, reducing manual effort and boosting productivity. Tools like the "friendly-cicd-helper" demonstrate how AI can complement traditional processes, freeing developers to focus on strategic tasks while maintaining high-quality standards.

Creating with Video to Video on Gen-3 Alpha and Turbo – Runway

The Gen-3 Alpha and Turbo models offer an enhanced "Video to Video" feature, allowing users to transform the style of videos using text prompts. The Turbo model is faster and more cost-effective, supporting resolutions up to 1280x768 and videos of up to 20 seconds. To use this feature, select a model, upload a supported video, and draft a detailed prompt to define the desired style. Additional settings, like structure transformation and aspect ratio, allow for customization. Once configured, the tool generates stylized videos, with results saved in the Generative Video folder for easy access.

Model-Based Transfer Learning for Contextual Reinforcement Learning

This paper introduces Model-Based Transfer Learning (MBTL), a framework to improve generalization in contextual reinforcement learning (RL). Traditional RL approaches often fail with minor environmental changes, and existing training methods are either too resource-intensive or prone to negative transfer. MBTL addresses this by modeling generalization performance with Gaussian processes and linear functions to predict and minimize performance gaps when transferring policies to new tasks. By integrating these models with Bayesian optimization, MBTL strategically selects training tasks, achieving up to 50x better sample efficiency in benchmarks like urban traffic. This approach paves the way for more reliable and efficient RL training methods.

Andrew Ng releases an open-source Python framework to swap between LLMs with one line of code

OpenInterpreter/open-interpreter: A natural language interface for computers

ItzCrazyKns/Perplexica: Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI

souzatharsis/podcastfy: An Open Source Python alternative to NotebookLM's podcast feature: Transforming Multimodal Content into Captivating Multilingual Audio Conversations with GenAI

black-forest-labs/flux: Official inference repo for FLUX.1 models

📢 If your company is interested in reaching an audience of developers and, technical professionals, and decision makers, you may want toadvertise with us.

If you have any comments or feedback, just reply back to this email.

Thanks for reading and have a great day!