Being a developer in the age of reasoning AI

The launch of OpenAI's o3 has raised questions about the role of developers in an era where AI can generate code and outperform 99.8% of developers in competitive coding. With o3, AI can think like a developer, generating algorithms on the fly and executing them to solve problems, potentially changing the way developers write code and interact with AI-generated code.

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Prosecutors in Washington State Warn Police: Don't Use Gen AI to Write Reports

Prosecutors in Washington State's King County have instructed police not to use generative artificial intelligence (genAI) to write police reports due to concerns about errors and potential perjury. The King County Prosecuting Attorney's Office has deemed the technology not yet reliable enough to be used in official reports.

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Generative AI still needs to prove its usefulness

Generative AI, despite its initial hype, has yet to prove its usefulness, with many systems struggling with accuracy and fact-checking. The technology's limitations and lack of profits have led to disillusionment, with companies like OpenAI facing significant operating losses and dwindling profits.

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AI PC revolution appears DOA – AI PCs and smartphones is a bust, analyst says

According to a prominent analyst, the AI PC and smartphone "supercycle" is a bust, as Micron's Q3 earnings and guidance for the second quarter of 2025 indicate a weaker market than expected for memory products for PCs and smartphones. Multiple reports have also suggested that the AI PC "revolution" is not happening, with demand driven by the general desire to upgrade rather than AI-powered features.

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ByteDance INFP: The AI That Brings Images to Life

Bytedance has introduced INFP, a powerful AI that can turn any single image into a lively character that can talk, sing, and interact with its surroundings. This technology has various use cases, including bringing historical figures to life, enabling real-time communication between AI agents, simulating realistic interviews, and creating virtual performances.

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Offline Reinforcement Learning for LLM Multi-Step Reasoning

Offline Reasoning Optimization (OREO) is proposed as an offline reinforcement learning method to improve large language models' multi-step reasoning abilities, addressing limitations of existing methods like Direct Preference Optimization. OREO outperforms existing offline learning methods on various benchmarks, including mathematical reasoning and embodied agent control tasks, and can be extended for further performance boosts.

ArXiv

Artificial Intelligence in the Knowledge Economy [pdf]

The integration of Artificial Intelligence (AI) into the knowledge economy can transform problem-solving by enabling AI agents to assist or replace humans in various roles. The impact of AI on firms and individuals varies depending on the level of autonomy, with advanced autonomous AI leading to larger and more productive firms, but primarily benefiting the most knowledgeable individuals.

ArXiv

Exploring Prime Number Classification with Machine Learning

Researchers developed a novel approach combining a sparse encoding method with neural networks to classify prime and non-prime numbers, achieving high accuracy in identifying primes (99%) and non-primes (79%) from a large series of integers. The model showed rapid convergence and promising results, despite being limited by memory capacity, and aims to contribute to the application of machine learning in prime number analysis.

ArXiv

Tokenisation Is NP-Complete

Researchers proved that two tokenisation variants, direct tokenisation and bottom-up tokenisation, are NP-complete problems. These variants involve compressing a dataset to a limited number of symbols using either vocabulary selection or a sequence of merge operations.

ArXiv

Specification-Driven Code Translation Powered by LLMs: How Far Are We?

Researchers investigated using natural language specifications as an intermediate step in translating code between programming languages using Large Language Models. The results showed that using natural language alone did not improve performance, but combining it with source code led to slight improvements in certain language pairs.

ArXiv

Show HN: GitHub-assistant – Natural language questions from your GitHub data

github-assistant is a proof-of-concept project built using Relta and assistant-ui, allowing users to interact with GitHub data through a text-based interface. The project is available to try at github-assistant.com, with setup instructions and requirements listed for those interested in running the project locally.

Repo

RAG Logger: An Open-Source Alternative to LangSmith

RAG Logger is an open-source logging tool designed for Retrieval-Augmented Generation (RAG) applications, providing comprehensive pipeline logging, structured storage, and metadata enrichment. It allows users to track queries, retrieval results, LLM interactions, and performance monitoring, storing logs in a JSON-based format with daily organization and automatic file management.

Repo

When AI Beats Us in Every Test We Can Do: A Simple Definition for Human-Lvl AGI

A system has reached human-level AGI when it becomes impossible for humans to create any benchmark where humans reliably outperform the system. The author suggests that based on current trends, this point may be reached as early as 2025, at which time humans will no longer be able to create tasks where they outperform AI systems.

Repo

Show HN: Workout app for mobile, web and desktop

Fit Main Character A is a cross-platform, open-source workout application available on multiple platforms, helping users track workouts and stay motivated. The app currently has a limited selection of exercises, but welcomes contributions to expand its library and improve visualization.

Repo

Building Effective Agents with Pydantic AI

This project provides code examples for building effective agents using Pydantic AI, inspired by the article "Building Effective Agents" by Erik Schluntz and Barry Zhang of Anthropic. The examples include notebooks for basic workflows, orchestrator and workers, and evaluator and optimizer, and can be set up by copying a .env file and filling in API keys for LLM providers.

Repo