Here are some noteworthy happenings and use-cases of AI in the current week.<\/p>\n\n\n\n
In many instances, a human expert must carefully design a reward function, which is an incentive mechanism that gives the agent motivation to explore. The human expert must iteratively update that reward function as the agent explores and tries different actions. This can be time-consuming, inefficient, and difficult to scale up, especially when the task is complex and involves many steps. Researchers from MIT, Harvard University, and the University of Washington have developed a new reinforcement learning approach that doesn\u2019t rely on an expertly designed reward function. Instead, it leverages crowdsourced feedback, gathered from many nonexpert users, to guide the agent as it learns to reach its goal. Read more here.<\/a><\/p>\n\n\n\n Elon Musk has integrated \u2018X\u2019 with \u2018Grok\u2019, his LLM which is being trained on the latest sentiments posted on X. Just imagine the confusion that could be created by this. There are sentiments expressed on X by all sorts of people at the extreme ends of the political, ideological, national and other spectra. There is no charge on posting on X, so some people engage in slanging matches and other ways to pass time. Will the genuine voices of the public be drowned out by this<\/a>?<\/p>\n\n\n\n One powerful use-case for AI is building intelligent supply chains for business. According to a 2020 CGE report, companies which commit to digitizing their supply chains can expect to save up to 50 percent on supply-chain costs; besides, a 20% reduction in procurement costs, apart from an increase in revenue of over 10%\u200a\u2014\u200aresulting from incremental competitive advantage. ( Source: Center for Global Enterprise (CGE) in partnership with CREATe.org<\/a>). Read more here<\/a>.<\/p>\n\n\n\n <\/p>\n\n\n\nPublic opinion being eroded by AI threat?<\/h3>\n\n\n\n
Data-driven, AI powered supply chains critical for businesses<\/h3>\n\n\n\n