$270,000 Drug. One Competitor. Billion-Dollar Market.

Phase 3 trial targets recurrent pericarditis with an oral therapy that could disrupt the only approved treatment. And their heart failure program launches in 2026.

Nvidia Open-Sources AI That Helps Self-Driving Cars Think Like Humans

Anusuya Lahiri
December 02, 2025

Nvidia Corp. (NASDAQ:NVDA) is expanding its open-source artificial intelligence portfolio with a sweeping set of new models, datasets, and development tools designed to accelerate progress in both digital and physical AI.

The company unveiled the offerings at the NeurIPS AI research conference, highlighting how open access to advanced technology can speed breakthroughs in fields from autonomous driving to medical intelligence.

A centerpiece of the announcement is Nvidia DRIVE Alpamayo-R1 (AR1), the first industry-scale open reasoning vision-language-action model built for autonomous vehicle research.

Also Read: Nvidia’s Core Approach Is Enabling Broader AI Industry: Analyst

Unlike earlier systems that struggled to handle unpredictable real-world traffic, AR1 uses chain-of-thought reasoning to choose safer, more adaptive driving paths.

It evaluates multiple possible trajectories and then uses contextual cues, from bike lanes and crowds of pedestrians to sudden lane closures, to determine the best move.

Researchers can customize AR1 for non-commercial experimentation thanks to its foundation built on Nvidia Cosmos Reason, and Nvidia reports that reinforcement learning post-training significantly improves its reasoning abilities.

The model will be accessible through GitHub and Hugging Face, with supporting datasets and an evaluation framework called AlpaSim also being released.

Physical AI Expansion Through Nvidia Cosmos

Nvidia is extending this physical AI push through Cosmos, its platform for building intelligent systems that interact with the real world.

The company has released a Cosmos Cookbook to guide developers through every step of model creation, including data collection, synthetic data generation and evaluation, and demonstrated new tools such as LidarGen for generating high-fidelity lidar data, Omniverse NuRec Fixer for repairing artifacts in neural scene reconstructions, and ProtoMotions3 for developing physically realistic humanoid robots.

Nvidia says companies, including Voxel51, 1X, Figure AI, Foretellix, Gatik, Oxa, PlusAI, and X-Humanoid, are already using Cosmos world models for advanced robotics and autonomous systems.

Advances in Digital AI and Speech Intelligence

Alongside its physical AI advancements, Nvidia is bolstering its digital AI stack.

The company introduced MultiTalker Parakeet, a speech AI system capable of recognizing multiple overlapping voices in real time.

It also showcased Sortformer, which can identify and separate speakers within a fast-moving conversation.

New tools for AI safety and synthetic data, including a reasoning-based content moderation model and an audio dataset designed to detect unsafe content, bring stronger guardrails to emerging agentic AI applications.

Nvidia also open-sourced its NeMo Data Designer Library, giving developers an end-to-end toolkit to generate high-quality synthetic datasets for fine-tuning and evaluation.

Highlights include Audio Flamingo 3, which can reason over long segments of speech and sound; Minitron-SSM, a compression method that cuts model size in half while improving accuracy; and ProRL, a prolonged reinforcement-learning approach that significantly expands large-model reasoning capabilities.

Analyst Outlook and Market Perspective

Nvidia, the biggest company in terms of market cap, has gained 34% year-to-date.

Bank of America Securities analyst Vivek Arya argued that recent doubts about AI spending are overstated, calling the pullback a healthy pause in a strong long-term growth cycle.

He said the sector sell-off stemmed from macro noise like shutdown fears and tariff volatility, not from weakening AI demand.

Arya pointed to Nvidia’s more than $500 billion data center order outlook for 2025–2026 as clear evidence that hyperscalers remain committed to accelerated computing upgrades.

He said Nvidia looks especially compelling with potential 2026 sales and earnings growth of roughly 50% and 70% year over year while still trading at about 24x earnings.

Even if global AI capex reaches only half of Nvidia’s projected $3–$4 trillion by 2030, Arya believes the company could earn over $40 per share, meaning today’s valuation prices in only modest industry expansion.

He added that concerns about China restrictions have little bearing on Nvidia’s near- or mid-term fundamentals.

Arya also flagged two catalysts ahead. A U.S. Supreme Court tariff case that could aid industrial and auto chipmakers, and Advanced Micro Devices, Inc.’s (NASDAQ:AMD) analyst day, where he expects management to outline a stronger long-term GPU and CPU roadmap tied to AI growth.

NVDA Price Action: Nvidia shares were up 0.63% at $181.05 during premarket trading on Tuesday, according to Benzinga Pro data.

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