Will OpenAI Have Its Biggest Release Ever Today?

Genesis, an open-source physics engine, redefines simulation speed and flexibility for robotics and embodied AI. In a 24-month collaboration across 20+ research labs, it achieves as much as 80 times faster simulations than traditional GPU-driven platforms like Isaac Gym and Mujoco MJX, all while maintaining precision.

• 430,000x faster than real-time physics, processes 43M FPS on an RTX 4090

• Unified framework with multiple physics solvers: Rigid body, MPM, SPH, FEM, PBD, Stable Fluid

• Easy installation via pip: pip install genesis-world

• Supports robots: arms, legs, drones, soft robots; compatible with MJCF, URDF, obj, glb

• Photorealistic ray-tracing rendering

• Inbuilt Python, 10-80x faster than Isaac Gym GPU solutions

• Cross-platform: Linux, MacOS, Windows with CPU, NVIDIA, AMD, Apple Metal support

• Upcoming “.generate” method/generative framework

• 26 seconds to coach transferrable robot locomotion policies

• Fully open-sourced physics engine and simulation platform

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ChatGPT Expands to Phones and MacOS in OpenAI’s Penultimate Shipmas Rollout

In the ultimate stretch of OpenAI’s Shipmas rollout, ChatGPT broadens its accessibility and functionality. Day 10 introduces expanded access with ChatGPT’s toll-free phone service within the U.S., offering 15-minute monthly sessions for each mobile and landline users. Moreover, global WhatsApp integration now enables text-based interactions with ChatGPT, with upcoming features like image recognition within the pipeline.

For Day 11, OpenAI enhances its macOS desktop app, enabling ChatGPT to read content from applications equivalent to Apple Notes, Xcode, and Git repositories. Nevertheless, resulting from the shortage of write-back functionality, users must manually transfer responses. These updates highlight OpenAI’s continued effort to serve a broad spectrum of users—from those without smartphones to developers—further solidifying its rapid expansion in the course of the Shipmas rollout.

Google has introduced its experimental “reasoning” AI model, Gemini 2.0 Flash Considering Experimental, designed to tackle complex tasks in fields like programming, math, and physics. Hosted on AI Studio, it guarantees advanced multimodal reasoning, pausing to think about interrelated prompts before generating a solution. While it excels in abstract problem-solving, it falters on easy tasks—like counting letters in a word.

Built on the Gemini 2.0 Flash framework, it shares the self-correcting capabilities of other reasoning models, helping it avoid common pitfalls. Nevertheless, its heavy computational load raises questions on scalability and long-term performance. Though early results show promise, the actual challenge will likely be maintaining this momentum without exhausting resources. Read more.