Automation Leverage in Turnaround Strategy

Automation Leverage in Turnaround Strategy Turnaround work is often described as a crisis discipline: reduce costs, preserve cash, stabilize operations and buy time. Those moves matter, but they are not enough. A durable turnaround also needs leverage: better systems, clearer information flows and repeatable execution. For Livio Andrea Acerbo , AI automation is useful in turnaround strategy when it improves the operating rhythm of a company. The point is not to add tools. The point is to remove friction from decisions that must happen every week. From cost control to operating clarity Cost control can stop the bleeding, but operating clarity creates the next phase. Teams need to know which products are profitable, which customers deserve attention, where working capital is trapped and which workflows create avoidable delay. Automation helps when it turns scattered data into a management cadence. Dashboards, exception reports, document summaries, pipeline reviews and cash visibi...

Google’s updated privacy policy states it can use public data to train its AI models

Google has updated its privacy policy to state that it can use publicly available data to help train its AI models. The tech giant has changed the wording of its policy over the weekend and switched "AI models" for "language models." It also stated that it could use publicly available information to build not just features, but full products like "Google Translate, Bard, and Cloud AI capabilities." By updating its policy, it's letting people know and making it clear that anything they publicly post online could be used to train Bard, its future versions and any other generative AI product Google develops.The tech giant has highlighted the changes to its privacy policy on its archive, but here's a copy of the pertinent part:GoogleCritics have been raising concerns about companies' use of information posted online to train their large language models for generative AI use. Recently, a proposed class action lawsuit was filed against OpenAI, accusing it of scraping "massive amounts of personal data from the internet," including "stolen private information," to train its GPT models without prior consent. As Search Engine Journal notes, we'll likely see plenty of similar lawsuits in the future as more companies develop their own generative AI products. Owners of websites that could be considered public squares in the digital age have also taken steps to either prevent or profit from the generative AI boom. Reddit has started charging for access to its API, leading third-party clients to shut down over the weekend. Meanwhile, Twitter put a restriction on how many tweets a user sees per day to "address extreme levels of data scraping [and] system manipulation."This article originally appeared on Engadget at https://www.engadget.com/googles-updated-privacy-policy-states-it-can-use-public-data-to-train-its-ai-models-095541684.html?src=rss

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