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AI models are increasingly incorporating reasoning capabilities, offering step-by-step explanations that enhance transparency and trust. This development is crucial as concerns grow about AI going out of control, and it meets ethical requirements for auditable decision-making.
Grok’s Reasoning Advancements
Grok, developed by xAI, has seen significant progress with its latest version, Grok-3, launched in February 2025. It features a “Think” mode that allows it to reason through problems, achieving an impressive Elo score of 1402 in the Chatbot Arena, outperforming rivals in math and coding tasks. This unexpected detail shows Grok-3’s potential to rival established models, making it a strong contender in the AI race.
ChatGPT’s Reasoning Capabilities
OpenAI’s ChatGPT, particularly GPT-4o, has enhanced reasoning for complex tasks like math and coding. While it shows improvements, accuracy can vary, especially in logical reasoning, which is an area of ongoing refinement. This ensures users can verify answers, aligning with ethical transparency needs.
DeepSeek’s Contributions
DeepSeek, a Chinese startup, introduced DeepSeek-R1 in January 2025, an open-source model that matches top performers like OpenAI’s o1 in reasoning tasks. Using reinforcement learning, it’s cost-effective and accessible, democratizing advanced AI for researchers and developers.
Ethical and Transparency Benefits
These reasoning capabilities provide an audit trail, allowing users to check reliability and ensure answers come from credible sources. This transparency addresses ethical concerns, reducing fears of AI going rogue by making decision-making processes clear and verifiable.
Survey Note: The Evolution of Reasoning in AI: Grok, ChatGPT, and DeepSeek Leading the Way
In the rapidly evolving landscape of artificial intelligence, the integration of reasoning capabilities into AI models marks a pivotal shift. Models like Grok from xAI, ChatGPT from OpenAI, and DeepSeek’s R1 are at the forefront, each contributing uniquely to this advancement. This survey note explores their developments, focusing on how they enhance reasoning, the ethical implications of transparency, and the broader impact on AI’s future, as observed in recent research and discussions.
Background and Importance of AI Reasoning
AI reasoning refers to the ability of models to process information logically, drawing conclusions step by step, akin to human thought processes. This capability is essential for tackling complex tasks beyond simple pattern recognition, such as solving mathematical problems, coding, and scientific reasoning. The push for reasoning in AI stems from the need for transparency and trust, especially as concerns about AI’s potential to go out of control grow. By providing an audit trail, reasoning models allow users to verify the reliability of answers, ensuring they stem from credible sources and aligning with ethical standards.
Recent developments, as of March 2025, highlight a competitive race among tech giants and startups to enhance reasoning, driven by user demand for explainable AI. This is particularly relevant in sensitive sectors like healthcare, finance, and law, where decision-making must be justifiable and auditable.
Grok’s Approach to Reasoning
Grok, developed by xAI and founded by Elon Musk, has evolved rapidly, with Grok-3 marking a significant milestone. Launched in February 2025, Grok-3 is described as “an order of magnitude more capable” than Grok-2, blending superior reasoning with extensive pretraining knowledge. According to xAI’s blog post, “Announcing Grok-3” (Announcing Grok-3), the model was trained on the Colossus supercluster with 10x the compute of previous state-of-the-art models, showing improvements in reasoning, mathematics, coding, and world knowledge.
A key feature is the “Think” mode, which enables Grok-3 to reason for seconds to minutes, correcting errors and exploring alternatives, as noted in an Engadget article, “xAI launches Grok 3 AI, claiming it is capable of ‘human reasoning'” (xAI launches Grok 3 AI, claiming it is capable of ‘human reasoning’). This mode is supported by large-scale reinforcement learning, achieving a 93.3% score on the 2025 American Invitational Mathematics Examination (AIME) with high test-time compute. A YouTube video, “Grok 3 Tested | The Best Reasoning Model?” (Grok 3 Tested | The Best Reasoning Model?), further demonstrates its capabilities, showing it outperforming rivals in blind testing, with an Elo score of 1402 in Chatbot Arena, an unexpected detail given its late entry into the market.
ChatGPT’s Reasoning Capabilities
OpenAI’s ChatGPT, particularly GPT-4o, has also advanced in reasoning, building on the foundation laid by GPT-4. GPT-4o, introduced in May 2024, is multimodal, handling text, images, and audio, and shows significant improvements in reasoning tasks like math and coding, as discussed in TechTarget’s article, “GPT-4o explained: Everything you need to know” (GPT-4o explained: Everything you need to know). It excels in benchmarks like GPQA (biology, physics, chemistry) and MATH, though accuracy can vary, especially in logical reasoning, as noted in community discussions on OpenAI’s Developer Community (On the logical reasoning ability of GPT-4).
The model’s chain-of-thought approach mimics human problem-solving, enhancing transparency by breaking down reasoning steps. However, challenges remain, with some users reporting inconsistencies in fraction comparisons and complex arithmetic, indicating ongoing refinement. This aligns with the user’s concern for auditable answers, ensuring users can verify reliability, a critical aspect for ethical AI deployment.
DeepSeek’s Contributions to AI Reasoning
DeepSeek, a Chinese AI startup, has disrupted the field with DeepSeek-R1, launched in January 2025. This open-source model matches the performance of OpenAI’s o1 on reasoning benchmarks for math and coding, as detailed in the MIT Technology Review article, “How Chinese company DeepSeek released a top AI reasoning model despite US sanctions” (How Chinese company DeepSeek released a top AI reasoning model despite US sanctions). The research paper, “DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning” (DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning), explains its use of pure reinforcement learning (RL) without supervised fine-tuning, enabling autonomous reasoning emergence.
DeepSeek-R1’s efficiency, using fewer chips and being 96% cheaper, democratizes access, challenging the resource-intensive approaches of Western giants. It employs a chain-of-thought process, enhancing transparency by articulating reasoning steps, which is vital for ethical considerations and user trust, especially in global contexts where AI accessibility is a concern.
Comparative Analysis
To better understand these models, consider the following table comparing their reasoning capabilities:
| Model | Developer | Key Feature | Benchmark Performance | Transparency Level |
| Grok-3 | xAI | Think mode, high compute power | Elo 1402 in Chatbot Arena | High, step-by-step reasoning |
| GPT-4o | OpenAI | Multimodal, chain-of-thought | Strong in GPQA, MATH | Moderate, varies by task |
| DeepSeek-R1 | DeepSeek | Open-source, RL-based | Matches o1 in math, coding | High, chain-of-thought |
This table highlights Grok-3’s lead in user preference benchmarks, GPT-4o’s versatility, and DeepSeek-R1’s cost-effectiveness, each contributing to the reasoning race.
Ethical Considerations: Transparency and Trust
The integration of reasoning in AI models addresses ethical concerns by providing transparency, crucial for mitigating fears of AI going rogue. By offering an audit trail, users can verify the reliability of answers, ensuring they stem from credible sources, as noted in the user’s query. This aligns with the need for explainable AI, reducing biases and enhancing trust, especially in sensitive applications.
However, controversy exists around reasoning accuracy and potential biases, with debates on whether models can truly reason or merely simulate it. The lack of transparency in some training data, as seen with DeepSeek’s closed datasets, adds complexity, while Grok-3’s open-source promise post-maturity could shift the landscape, fostering community scrutiny.
Conclusion and Future Prospects
As of March 2025, the AI reasoning race is intensifying, with Grok, ChatGPT, and DeepSeek pushing boundaries. Grok-3’s high benchmarks, GPT-4o’s multimodal enhancements, and DeepSeek-R1’s efficiency suggest a future where AI is more intelligent and trustworthy. The focus on transparency meets ethical needs, but ongoing research is needed to address accuracy and bias, ensuring AI benefits society while remaining accountable.
Key Citations
- Announcing Grok-3 xAI blog post
- xAI launches Grok 3 AI, claiming it is capable of ‘human reasoning’ Engadget article
- How Chinese company DeepSeek released a top AI reasoning model despite US sanctions MIT Technology Review article
- Grok 3 Tested | The Best Reasoning Model? YouTube video
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning research paper
This article was written by Dr John Ho, a professor of management research at the World Certification Institute (WCI). He has more than 4 decades of experience in technology and business management and has authored 28 books. Prof Ho holds a doctorate degree in Business Administration from Fairfax University (USA), and an MBA from Brunel University (UK). He is a Fellow of the Association of Chartered Certified Accountants (ACCA) as well as the Chartered Institute of Management Accountants (CIMA, UK). He is also a World Certified Master Professional (WCMP) and a Fellow at the World Certification Institute (FWCI).
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World Certification Institute (WCI) is a global certifying and accrediting body that grants credential awards to individuals as well as accredits courses of organizations.
During the late 90s, several business leaders and eminent professors in the developed economies gathered to discuss the impact of globalization on occupational competence. The ad-hoc group met in Vienna and discussed the need to establish a global organization to accredit the skills and experiences of the workforce, so that they can be globally recognized as being competent in a specified field. A Task Group was formed in October 1999 and comprised eminent professors from the United States, United Kingdom, Germany, France, Canada, Australia, Spain, Netherlands, Sweden, and Singapore.
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