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Artificial intelligence (AI) chatbots are terrible at remembering things — both between separate conversations and even during the same conversation. But two recent breakthroughs might completely change this. If you talk to a large language model (LLM) like OpenAI's ChatGPT for long enough, it will begin to forget crucial pieces of information — especially if the conversation stretches on for more than 4 million words of input. Its performance then begins to deteriorate rapidly.  Meanwhile, ChatGPT and other LLMs can't retain information between conversations. For example, if you finish one conversation and reboot ChatGPT a week later, the chatbot won't remember anything from the previous exchange.  But two separate teams have potentially found solutions to these memory issues. A team of scientists led by the Massachusetts Institute of Technology (MIT) have pinpointed the reason AI forgets things mid-conversation and come up with a method to fix it, while dev...

A pair of scientists at Google's artificial intelligence subsidiary DeepMind is in talks with investors to form an AI startup in Paris, Bloomberg News reported on Friday, citing people familiar with the conversations. Scientists Laurent Sifre and Karl Tuyls, who have already given notice to leave DeepMind, have held discussions with investors about a financing round that could raise over 200 million euros ($217.84 million), the report said. The company, known at the moment as Holistic, may be focused on building a new AI model, the report added. Google and DeepMind did not immediately respond to Reuters' requests for comment. DeepMind was acquired by Alphabet-owned Google around a decade ago to fuel AI research and has now deployed its own offerings in the race to com Pet e with generative AI chatbots like Microsoft-backed ChatGPT. Paris-based Mistral AI, co-founded by a former DeepMind researcher, said in December it had raised 385 million euros ($419.34 mil...

KARACHI: A team of Pakistani scientists has made a significant scientific breakthrough by developing an artificial intelligence (AI)-based visual classification method that accurately assesses the sweetness of native citrus fruits. Led by Dr Ayesha Zeb from the National Centre of Robotics and Automation at the National University of Sciences and Technology (NUST), the team successfully predicted fruit sweetness with over 80 per cent accuracy, without damaging the fruit in the process. To conduct their experiment, the researchers selected 92 citrus fruits, including Blood Red, Mosambi, and Succari varieties, from a farm in the Chakwal district. They utilised a handheld spectrometer to obtain spectra, which are patterns obtained from the bouncing light, from marked regions on the fruits' skin. The team employed near-infrared (NIR) spectroscopy, a technique that enables the analysis of non-visible light spectra, to examine the fruit samples. Of the 92 fruits, 64 were used for cal...