Author HubMaximilian Schreiner

Max is the managing editor of THE DECODER, bringing his background in philosophy to explore questions of consciousness and whether machines truly think or just pretend to.

AI research

Sep 17, 2025

OpenAI outperforms humans and Google at the world's top collegiate programming contest

AI in practice

Sep 15, 2025Sep 15, 2025

New data from OpenAI and Anthropic show how people actually use ChatGPT and Claude

AI in practice

Aug 7, 2025Aug 7, 2025

OpenAI launches GPT-5 as a unified system with adaptive reasoning for complex tasks

AI in practice

Jul 14, 2023Jul 14, 2023

Short

Is GPT-4 getting worse? Peter Welinder, VP Product at OpenAI, comments on the rumors: "No, we haven't made GPT-4 dumber. Quite the opposite: we make each new version smarter than the previous one," says Welinder. His hypothesis: "When you use it more heavily, you start noticing issues you didn't see before."

Still, he asked on Twitter for examples of where users felt GPT-4's performance had regressed. OpenAI will look into this, Welinder promises. One example from the comments, where GPT-4 only gives the correct answer after a second attempt, he claims is a bug.

Field reports of GPT-4 performance degradation have been around for a few weeks now, often pointing to a performance difference between access via API and via ChatGPT, where the OpenAI language model integration is regularly adjusted. The opacity of this process may also contribute to uncertainty among users.

No, we haven't made GPT-4 dumber. Quite the opposite: we make each new version smarter than the previous one.

Current hypothesis: When you use it more heavily, you start noticing issues you didn't see before.

— Peter Welinder (@npew) July 13, 2023

AI in practice

Jul 13, 2023Jul 13, 2023

Pentagon seeks solutions to counter growing threat of cheap AI-powered weapons

AI research

Jul 13, 2023

Objaverse-XL brings 10 million 3D objects to generative AI training

AI in practice

Jul 12, 2023Jul 12, 2023

Short

AI tool RFdiffusion, a neural network developed by the University of Washington, can rapidly design custom proteins with potential applications in vaccines, therapeutics, and biomaterials. The tool borrows principles from neural networks that generate realistic images, such as Stable Diffusion, DALL-E, or Midjourney, creating complex and diverse protein shapes when it "denoises" a random assortment of amino acids.

Although the designs show promise in early experimental tests, researchers are still working to improve the AI's ability to design proteins with more complex active sites and specific reactions. RFdiffusion is available on GitHub.

Nature

AI research

Jul 11, 2023Jul 11, 2023

Update

GPT-4 architecture, datasets, costs and more leaked

AI research

Jul 11, 2023

Short

A team of Chinese researchers has developed an AI tool capable of designing a working RISC-V CPU in just five hours. It successfully ran the Linux operating system and performed comparably to the human-designed Intel 80486SX CPU from 1991. According to the team, with a working chip in just under five hours, the AI was able to design the chip 1,000 times faster than a human team. The AI was also able to autonomously make discoveries in computer design, uncovering the von Neumann architecture first invented in 1945.

The authors suggest that their approach, outlined in a study titled "Pushing the Limits of Machine Design: Automated CPU Design with AI" could revolutionize the semiconductor industry by significantly shortening the design cycle.

Arxiv

AI and society

Jul 10, 2023

Unicorn startup Character.AI struggles with waifus and copyrights

AI in practice

Jul 10, 2023Jul 10, 2023

Short

GPT Researcher is an AI-based autonomous agent for conducting comprehensive online research on a variety of tasks. The tool, inspired by AutoGPT and the "Plan-and-Solve" prompting, seeks to improve on speed and determinism issues found in current language models, "offering a more stable performance and increased speed through parallelized agent work, as opposed to synchronous operations."

According to the team, GPT Researcher facilitates research by generating relevant research questions, aggregating data from over 20 web sources, and leveraging both GPT3.5-turbo-16k and GPT-4 to create comprehensive research reports. The project aims to address the time-consuming nature of manual research tasks and the biases that result from limited resource usage in alternative approaches such as ChatGPT + WebPlugin. It includes a web interface and provides an export function for research reports in various formats.