Call it a reasoning renaissance. In the wake of the release of OpenAIs o1, a so-called reasoning model, theres been an explosion of reasoning models from rival AI labs. In early November, DeepSeek, an AI research company funded by quantitative traders, launched a preview of its first reasoning algorithm, DeepSeek-R1. That same month, Alibabas Qwen team unveiled what it claims is the first open challenger to o1.So what opened the floodgates? Well, for one, the search for novel approaches to refine generative AI tech. As my colleague Max Zeff recently reported, brute force techniques to scale up models are no longer yielding the improvements they once did.Theres intense competitive pressure on AI companies to maintain the current pace of innovation. According to one estimate, the global AI market reached $196.63 billion in 2023 and could be worth $1.81 trillion by 2030.OpenAI, for one, has claimed that reasoning models can solve harder problems than previous models and represent a step change in generative AI development. But not everyones convinced that reasoning models are the best path forward.Ameet Talwalkar, an associate professor of machine learning atAI companies have financialincentives to offer rosy projections about the capabilities of futureversions of their technology, Talwalkar said. We run the risk of myopically focusing a single paradigm which is why its crucial for the broader AI research community to avoid blindly believing the hype and marketing efforts of these companies and instead focus on concrete results.Two downsides of reasoning models are that theyre (1) expensive and (2) power-hungry. For instance, in OpenAIs API, the company charges $15 for every ~750,000 words o1 analyzes and $60 for every ~750,000 words the model generates. Thats between 3x and 4x the cost of OpenAIs latest non-reasoning model, GPT-4o.O1 is available in OpenAIs AI-powered chatbot platform, ChatGPT, for free with limits. But earlier this month, OpenAI introduced a more advanced o1 tier, o1 pro mode, that costs an eye-watering $2,400 a year. The overall cost of [large language model]reasoningis certainly not going down, Guy Van Den Broeck, a professor of computer science at UCLA, told TechCrunch. One of the reasons why reasoning models cost so much is because they require a lot of computing resources to run. Unlike most AI, o1 and other reasoning models attempt to check their own work as they do it. This helps them avoid some of thepitfallsthat normally trip up models, with the downside being that they often take longer to arrive at solutions.OpenAI envisions future reasoning models thinking for hours, days, or even weeks on end. Usage costs will be higher, the company acknowledges, but the payoffs from breakthrough batteries to new cancer drugs may well be worth it.The value proposition of todays reasoning models is less obvious. Costa Huang, a researcher and machine learning engineer at the nonprofit org Ai2, notes that o1 isnt a very reliable calculator. And cursory searches on social media turn up a number of o1 pro mode errors.These reasoning models are specialized and can underperform in general domains, Huang told TechCrunch. Some limitations will be overcome sooner than other limitations.Van den Broeck asserts that reasoning models arent performing actual reasoning and thus are limited in the types of tasks that they can successfully tackle. Truereasoningworks on all problems, not just the ones that are likely [in a models training data], he said. That is the main challenge to still overcome.Given the strong market incentive to boost reasoning models, its a safe bet that theyll get better with time. After all, its not just OpenAI, DeepSeek, and Alibaba investing in this newer line of AI research. VCs and founders in adjacent industries are coalescing around the idea of a future dominated by reasoning AI.However, Talwalkar worries that big labs will gatekeep these improvements.The big labs understandably have competitivereasons to remain secretive, but this lack of transparency severely hinders the researchcommunitys ability to engage with these ideas, he said. As more people work on this direction, I expect [reasoning models to] quickly advance. But while some of the ideas will come from academia, given the financial incentives here, I would expect that most if not all models will be offered by large industrial labs like OpenAI.