Google is winning on every AI front

Google DeepMind has made a significant comeback in the AI field with its Gemini 2.5 model, which is currently considered the best in the world, outperforming other models in various benchmarks and tasks. The company's dominance extends beyond text-based models, with impressive advancements in other areas such as music, image, and video generation, as well as agent technology, solidifying its position as a leader in the AI industry.

Read more

AI can't stop making up software dependencies and sabotaging everything

The rise of AI-powered code generation tools is introducing new risks to the software supply chain, as these tools often "hallucinate" and suggest code that incorporates non-existent software packages. Malicious actors can exploit this by creating fake packages with the same names, which can then be installed and executed, potentially leading to security breaches. This type of attack has been dubbed "slopsquatting," a form of typosquatting that takes advantage of AI-generated code suggestions.

Read more

The Solid-State Shift: Reinventing the Transformer for Modern Grids

Transformers, which have been the backbone of power grids for over a century, are facing limitations in meeting the dynamic demands of modern grids, including the integration of renewable energy and electric vehicles. Solid-state transformers (SSTs) are emerging as a potential solution, offering compact, efficient, and intelligent power solutions that can revolutionize how electricity is distributed and managed, with features such as high-frequency operation, advanced power electronics, and real-time monitoring and control.

Read more

Dear Big Tech, Stop Shoving AI into Operating Systems

Big tech companies like Microsoft, Apple, and Google are aggressively integrating AI into their operating systems, but this push is more about hype than practicality, and may compromise user experience with unnecessary bloat and invasive features. Users prefer a stable, private, and customizable OS, and the current AI integrations, such as Microsoft's Copilot and Apple's Apple Intelligence, may not provide significant benefits to justify their inclusion.

Read more

Why training AI can't be IP theft

The author is discussing the question of whether people have the right to train AI models using copyrighted material without the consent of the original creators, with some arguing that this constitutes copyright infringement. However, the author believes that while the complaint is legitimate, the argument that training AI on copyrighted material is a copyright violation is "dangerously wrong" and could have disastrous consequences if enforced as a new intellectual property right.

Read more

Transfer between Modalities with MetaQueries

MetaQueries is a set of learnable queries that connects multimodal language models (MLLMs) to diffusion models, enabling knowledge-augmented image generation by leveraging the MLLM's understanding and reasoning capabilities. This method simplifies training, requires minimal data and objectives, and can be easily fine-tuned for advanced applications such as image editing and subject-driven generation, all while preserving the MLLM's state-of-the-art multimodal understanding capabilities.

ArXiv

Robustly identifying concepts introduced during chat fine-tuning with crosscoder

Model diffing, which studies how fine-tuning changes a model's representations, can be improved with the crosscoders method, but it has issues that can misattribute concepts as unique to the fine-tuned model. The introduction of Latent Scaling and a new loss function, BatchTopK, helps mitigate these issues, allowing for the identification of genuinely chat-specific and interpretable concepts, such as false information and personal questions, in fine-tuned language models.

ArXiv

Show HN: A toy MCP for AI agents to code, run, and see output of GPU code safely

There is no text to summarize. The provided input appears to be an error message indicating that a README file could not be retrieved.

Repo

Show HN: I built a tool that uses AI to turn Git commits into Discord updates

DCS is a tool that monitors a local Git repository, generates AI-powered summaries of recent commits, and sends them to a Discord channel, automating the process of keeping a community updated with project developments. The tool features robust error handling, optional email notifications, and can be run manually or automated via cron jobs or as a GitHub Action.

Repo

Show HN: AI wrote the python code. pyhunt tells you what it really does.

Pyhunt is a lightweight logging tool that visually represents logs for quick structural understanding and debugging, allowing users to automatically trace function calls and display logs in their terminal with a simple decorator. It features automatic function tracing, rich colors and tree-structured logs, multiple log levels, and optimized support for AI workflows, making it easy to debug and understand code execution.

Repo

Concept explorer: uses local AI to dive endlessly deeper into a concept

The Concept Explorer is a terminal-based tool that visually maps connections between ideas, starting from a single root concept and expanding into a tree of interconnected ideas across different domains. It features interactive visualization, contextual exploration, and customizable parameters, allowing users to control the exploration depth, diversity bias, and model used, with results exportable as a text file.

Repo

Vexa: Open-Source Transcription API for Product Builders

Vexa is an API for real-time meeting transcription that uses meeting bots and direct streaming from web and mobile apps to extract knowledge from various platforms, including Google Meet, Zoom, and Microsoft Teams. The API is designed with a scalable architecture to support thousands of simultaneous users and concurrent transcription sessions, and it aims to be an enterprise-grade solution with features such as real-time multilingual transcription, speaker identification, and meeting knowledge extraction.

Repo