OpenAI’s o3 Worse Than o3-preview?

OpenAI’s latest o3 model has fallen in need of expectations in recent evaluations, particularly in reasoning tests. The ARC Prize Foundation found that o3 scored 41% on low compute and 53% on medium compute for ARC-AGI-1, significantly behind the 76% and 88% results of the December 2024 preview version. This drop is linked to changes within the model’s architecture, with the brand new multimodal, smaller o3 optimised for chat and product use somewhat than advanced reasoning.

Despite outperforming earlier models like o1, the o3 model still struggles on more difficult benchmarks, scoring under 3% on ARC-AGI-2. The more cost-efficient o4-mini model, in contrast, delivers solid performance at a fraction of the worth. This highlights a critical gap between AI and human reasoning, in addition to the undeniable fact that more computational effort doesn’t at all times correlate with higher results.

Meanwhile, CEO Sam Altman addressed growing criticism of GPT-4o’s overly agreeable responses, calling it “sycophant-y and annoying.” Altman acknowledged the feedback and confirmed that OpenAI is working on immediate updates, with further adjustments expected over the week. Changes will introduce more conversational flexibility. Read more.

Google has expanded its generative AI offerings, with 601 use cases now available through Google Cloud, up from 101 last 12 months. Major firms like Uber, Citi, and Mercedes-Benz are leveraging AI models powered by Vertex AI and Gemini for tasks including customer support and healthcare diagnostics.

As well as, Google Photos has introduced a shortcut to bypass the slow “Ask Photos” feature. Users can now double-tap the search icon on Android devices to quickly switch to the classic search mode. This improvement addresses user concerns over the speed of “Ask Photos,” which uses Gemini AI for deeper natural language queries.

Alphabet’s Q1 2025 results exceeded expectations, with $90.23 billion in revenue. CEO Sundar Pichai highlighted AI-driven features like “AI Overviews,” utilized by 1.5 billion people monthly. Google can be experimenting with multimodal search and enhancing visual tools. The corporate’s concentrate on cost efficiency, driven by custom Tensor Processing Units (TPUs), positions it as a cheaper alternative to Nvidia GPUs. Google continues to prioritize flexibility and interoperability over a more integrated approach like OpenAI’s partnership with Microsoft. Read more.

NYU researchers have introduced RUKA, a tendon-driven, 3D-printable robotic hand that’s open-source and costs under $1,300. It features 15 degrees of freedom and might perform 31 out of 33 grasps in a regular grasp taxonomy. The hand may be assembled in under 7 hours by first-time builders and offers precise control through a data-driven approach, utilizing a MANUS glove to map fingertip positions to motor commands.

RUKA operates at 40 Hz for control and 25 Hz for teleoperation using devices like motion-capture gloves or VR headsets. A calibration script ensures consistency across builds, and the project provides detailed assembly instructions and support for community engagement. Read more.