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Big Tech CEOs have long praised ideas of AI agents that can use software programs to perform jobs for humans on their own.However, you will soon see how restricted the technology is if you try out any of today’s consumer AI agents, such as Perplexity’s Comet or OpenAI’s ChatGPT Agent.It might require a new set of methods that the industry is still learning to make AI agents more resilient. Reinforcement learning (RL) environments, which are meticulously modeled workspaces where agents can be educated on multi-step tasks, are one of such methods. RL settings are beginning to appear as a crucial component in the creation of agents, much way labeled datasets drove the previous wave of AI. Leading AI laboratories are increasingly requesting more RL environments, and there are plenty of firms looking to provide them, according to AI researchers, founders, and investors who spoke to TechCrunch. A new generation of well-funded firms, such Mechanize and Prime Intellect, have emerged in response to […]

Anyone who read business tech news seven or eight years ago may have heard the term “the race to produce autonomous vehicles.” During my private meetings with startup founders and firm executives, they occasionally described the commercialization of autonomous car technology as “a race.” During that period, the phrase permeated reportage, including several of my pieces. We now know that this is not so much a race as it is a lengthy, winding, and broken route, more akin to the fan of an alluvial plain than a racetrack, to develop and demonstrate the technology’s viability and turn it into a lucrative enterprise. It is more of an internal struggle with existential stakes than a race against other people. However, that does not mean that there are not actual conflicts among individuals developing the

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