Cognition Labs has set its sights on becoming the next multibillion-dollar AI startup. The company, which is developing an AI tool for code writing, is currently in talks with investors to secure funding at a valuation of up to $2 billion, according to The Wall Street Journal (WSJ) on Sunday (March 31). The report indicates that this funding round, if successful, would raise Cognition's valuation to nearly six times what it was just weeks ago. Sources reveal that venture firms in Silicon Valley, including Founders Fund, who are already shareholders, are engaging in discussions to invest in the round. Cognition initially started as a cryptocurrency company but made a shift to AI due to the growing popularity of the technology. Earlier this month, the company unveiled its AI coding tool, Devin, which is said to be capable of autonomously completing complex coding tasks, such as creating customized websites. The WSJ also noted that some investors view Devin as a significant breakthrough in AI intelligence and believe it could lead to widespread automation in software development. This funding round takes place amidst a trend of AI companies aiming for substantial increases in valuation. For instance, Canadian AI startup Cohere recently entered advanced discussions to raise $500 million, potentially reaching a valuation of $5 billion. Last June, Cohere's valuation stood at $2. 2 billion following a $220 million funding round. Similarly, French AI model developer Mistral experienced a valuation jump of approximately seven times in late 2021, reaching $2 billion from the previous year. Meanwhile, major tech giants such as Google, Microsoft, and Meta are actively developing their own AI large language models (LLMs), as highlighted by PYMNTS.

These companies are not sitting idly by, and while they hold an advantage, the race for AI supremacy extends beyond the industry leaders. Progress in AI often necessitates substantial investments in computational power and research talent. Gil Luria, a senior software analyst at D. A. Davidson & Co. , explained in an interview with PYMNTS, "The hurdle for building a broad foundational model is that training on increasingly large data sets is extraordinarily expensive. The only reason OpenAI can afford to do so is the backing of Microsoft and the Azure resources it makes available to OpenAI. The broad models, such as the ones leveraged by ChatGPT, have ingested huge portions of human knowledge and continue to train on new content, which is what makes them so versatile in many domains of expertise. "