Existing approaches to mathematical reasoning with large language models (LLMs) rely on Chain-of-Thought (CoT) for generalizability or Tool-Integrated Reasoning (TIR) for precise computation. While efforts have been made to combine these methods, they primarily rely on post-selection or predefined strategies, leaving an open question: whether LLMs can autonomously adapt their reasoning strategy based on their inherent capabilities. In this work, we propose TATA (Teaching LLMs According to Their Aptitude), an adaptive framework that enables LLMs to personalize their reasoning strategy spontaneously, aligning it with their intrinsic aptitude. TATA incorporates base-LLM-aware data selection during supervised fine-tuning (SFT) to tailor training data to the model's unique abilities. This approach equips LLMs to autonomously determine and apply the appropriate reasoning strategy at test time. We evaluate TATA through extensive experiments on six mathematical reasoning benchmarks, using both general-purpose and math-specialized LLMs. Empirical results demonstrate that TATA effectively combines the complementary strengths of CoT and TIR, achieving superior or comparable performance with improved inference efficiency compared to TIR alone. Further analysis underscores the critical role of aptitude-aware data selection in enabling LLMs to make effective and adaptive reasoning decisions and align reasoning strategies with model capabilities.

The inevitable march toward automation continues, analysts from the McKinsey Global Institute and from Tata Communications wrote in separate reports this week. Artificial intelligence's growth comes as no surprise -- a survey from Narrative Science and the National Business Research Institute conducted earlier this year found that 61 percent of businesses implemented AI in 2017, up from 38 percent in 2016 -- but this week's findings lay out in detail the likely socioeconomic impacts in the coming decade. The McKinsey models predict that 70 percent of companies will adopt at least one form of AI -- whether computer vision, natural language, virtual assistants, robotic process automation, or advanced machine learning -- by 2020. And Tata found unbridled enthusiasm among business leaders for an AI-dominated future; in a survey of 120 of them, 90 percent said they expect AI to enhance decision-making. McKinsey and Tata both contend that's a good thing.

The inevitable march toward automation continues, analysts from the McKinsey Global Institute and from Tata Communications wrote in separate reports this week. Artificial intelligence's growth comes as no surprise -- a survey from Narrative Science and the National Business Research Institute conducted earlier this year found that 61 percent of businesses implemented AI in 2017, up from 38 percent in 2016 -- but this week's findings lay out in detail the likely socioeconomic impacts in the coming decade. The McKinsey models predict that 70 percent of companies will adopt at least one form of AI -- whether computer vision, natural language, virtual assistants, robotic process automation, or advanced machine learning -- by 2020. And Tata found unbridled enthusiasm among business leaders for an AI-dominated future; in a survey of 120 of them, 90 percent said they expect AI to enhance decision-making. McKinsey and Tata both contend that's a good thing.

Eighty-four percent of large companies around the world say they are using artificial intelligence, and 62% say AI is important to remaining competitive in the year 2020. Tata Consultancy Services polled 835 executives and IT managers in North America, Europe, Asia Pacific and South America at companies that averaged $20 billion in revenues. It found AI to be almost universally important, but the average investment in it was one-third of one percent of revenues, or $67 million. Only 7% said they spent $250 million or more in 2016. The average was $67 million; the median for the whole group, only $3 million.

Ratan Tata, chairman emeritus of Tata Sons pumped an undisclosed amount in Bangalore-based artificial intelligence startup niki.ai. Along with Mr. Tata, Existing investor, Ronnie Screwvala's Unilazer Ventures also participated in this funding round. Unilazer had invested in the chat App back on October 2015 and had made a commitment of a follow-on investment round of up to Rs 5 crore. "Chatbots have now picked up globally and Niki has been at the forefront of this innovation, building the technology for over a year now. We continue to support the team as we believe in their vision to simplify transactions for consumers," said Screwvala.