Open models by OpenAI

OpenAI offers open models, including gpt-oss-120b and gpt-oss-20b, which are advanced open-weight reasoning models that can be customized for any use case and run anywhere. These models are supported by the Apache 2.0 license, allowing for free use and customization, and have undergone thorough safety training and evaluation to help developers keep users safe.

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Things that helped me get out of the AI 10x engineer imposter syndrome

The author, an engineer, recently experienced imposter syndrome due to claims of 10x productivity gains from using AI, feeling pressure to learn and adapt to new technologies to remain employable. However, after diving into AI coding and trying various tools, they found that AI's capabilities, while useful for certain tasks, are not as revolutionary as claimed, and that their own skills and experience remain valuable.

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Monitor your security cameras with locally processed AI

Frigate is an open-source NVR (network video recorder) that uses locally processed AI object detection to monitor security cameras, eliminating the need for cloud processing and reducing false positives. It offers features such as custom models, real-time object tracking, and integration with home automation platforms like Home Assistant, allowing for precise notifications and automation.

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Genie 3: A new frontier for world models

Genie 3 is capable of simulating and modeling various aspects of the world, including physical properties, natural phenomena, and ecosystems, as well as generating fantastical scenarios and animated characters. The system can create realistic and immersive environments, from volcanic landscapes and oceanic scenes to fantastical forests and whimsical creatures, demonstrating its ability to tap into imagination and create expressive and dynamic scenarios.

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AI is propping up the US economy

Microsoft has reached a $4 trillion valuation, driven largely by its cloud computing business, which is benefiting from the AI boom, with the company selling cloud compute in bulk to clients like OpenAI. The AI industry as a whole is experiencing historic levels of investment, with spending on AI infrastructure exceeding that of the dot-com boom and acting as a "private sector stimulus program" that is propping up the US economy, but some experts warn that this is unsustainable and may be a sign of an AI bubble.

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Quantum machine learning via vector embeddings

Quantum Support Vector Machines face scalability challenges, but a proposed quantum-classical pipeline using Vision Transformer embeddings achieves accuracy improvements of up to 8.02% over classical SVMs on certain datasets. The choice of embedding is critical, with Vision Transformer embeddings uniquely enabling quantum advantage, while CNN features show performance degradation, revealing a fundamental synergy between transformer attention and quantum feature spaces.

ArXiv

Rod Burstall: In Memoriam

Rod Burstall was a renowned computer scientist with a career spanning over 40 years, primarily at Edinburgh University, where he made significant contributions to programming languages, software development, and correctness proofs. His work included pioneering efforts in algebraic specification languages, categorical techniques, and automated proof support systems, and he played a key role in the development of influential programming languages such as POP-2, HOPE, and Standard ML.

ArXiv

The Super Weight in Large Language Models

Researchers have found that removing a single key parameter, known as a "super weight," from a Large Language Model (LLM) can significantly degrade its performance, and have developed a method to identify these crucial parameters. Preserving these super weights and corresponding large activations can also improve the efficiency of model quantization methods, allowing for more effective compression of LLMs.

ArXiv

Beyond Statistical Learning: Exact Learning Is Essential for AGI

Current AI systems, despite advancements in areas like math and science, struggle with deductive reasoning tasks due to their statistical learning approach. To achieve reliable deductive reasoning, researchers must shift towards an "exact learning" paradigm that prioritizes correctness on all inputs, rather than just optimizing for statistical performance on specific distributions of problems.

ArXiv

From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs

This paper introduces a three-stage pipeline for deploying large language models (LLMs) in a cost-efficient manner, addressing the trade-off between performance and expense. The pipeline, which includes prototyping, knowledge transfer, and model compression, enables the creation of smaller, high-performing models that reduce costs and complexity while maintaining effectiveness across various NLP applications.

ArXiv

Llama.cpp: Add GPT-OSS

Llama.cpp is a C/C++ implementation of large language models (LLMs) that enables inference with minimal setup and state-of-the-art performance on various hardware. The project supports a wide range of models, including LLaMA, GPT, and others, and provides bindings for multiple programming languages, as well as tools and UIs for interacting with the models.

Repo

Show HN: A benchmark + latency sim for LLM db queries: ClickHouse / Postgres

This benchmark measures the impact of database performance on LLM chat interactions, comparing OLAP (ClickHouse) and OLTP (PostgreSQL) using LLM-style query patterns, with results showing ClickHouse is up to 16.8x faster at 10M records. The repository provides a setup to run chat simulations and bulk tests, with detailed configuration options and output files containing timing data and confidence intervals.

Repo

Show HN: Tambo – build generative UX web apps

Tambo AI is a React package that enables developers to build AI-powered applications with generative UI, allowing users to interact through natural language. The package provides a set of tools and components that can be used to create dynamic and interactive user interfaces, and includes features such as AI-generated components, message threads, and tools for the AI to make decisions and take actions.

Repo

Show HN: Tezcat – local-first AI recall in Obsidian via a remembrance agent

Tezcat is an Obsidian plugin that uses artificial intelligence to index thoughts and surface related content fragments and notes as you write, enhancing creative recall. It offers search implementation options, including vector search and hybrid search, and can be used with local AI models via Ollama or proprietary embedding models like OpenAI, allowing users to insert links, content, and open parent pages.

Repo

OpenAI GPT-OSS

OpenAI has released two open-weight models, gpt-oss-120b and gpt-oss-20b, designed for powerful reasoning and versatile developer use cases, with features such as permissive Apache 2.0 licensing, configurable reasoning effort, and full chain-of-thought. These models can be used with various frameworks, including Transformers, vLLM, PyTorch, and Triton, and can be downloaded from the Hugging Face Hub.

Repo