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Pep Guardiola’s joy at winning the Champions League may have been trumped by a message of congratulations from one of his idols Julia Roberts. Manchester City said on social media that “@PepTeam will be buzzing at this!” after Hollywood star Roberts used Instagram to applaud the Spaniard for masterminding Saturday’s 1-0 victory over Inter Milan. “Congratulations @pepteam for leading your team to be UCL champions. #pep #soccermom” said the Ocean’s Twelve and Pretty Woman actor. It is the acknowledgement that Guardiola has been desperately seeking after he revealed in March the angst caused when Roberts once chose to visit Manchester United rather than watch his City team. “If I win the Champions League three times in a row I will be a failure,” said Guardiola after RB Leipzig had been thrashed 7-0 to secure a place in the quarter-finals. “I have three idols in my life. Michael Jordan, Tiger Woods, and Julia Roberts. These are my three idols. “Julia Roberts years ago came to Manchester – not in the 90s when Sir Alex (Ferguson) was winning titles and titles and titles. She came in the period where we were better than United, in these four or five years, right? “And she went to visit Man United. She didn’t come to see us. That’s why even if I win the Champions League it will not compare for the fact that Julia Roberts came to Manchester and didn’t come to see us. “Even if I win the Champions League it will not compare to this disappointment I had.” Gareth Southgate believes England can benefit from Manchester City’s clinching the Champions League for the first time. Southgate has included five members of Pep Guardiola’s side in his squad for this month’s Euro 2024 qualifiers against Malta and North Macedonia, with John Stones, Jack Grealish, Phil Foden, Kyle Walker and Kalvin Phillips all due to join up with the squad after enjoying their celebrations. With City’s success coming after Declan Rice lifted the Europa Conference League with West Ham earlier in the week, Southgate said it can be good for the national team. “It’s absolutely brilliant for all our guys who have been involved,” boss Southgate said in a video on England’s social media. “To start with Declan, his first experience of lifting a trophy so… fabulous for him. You can see the emotion having been at the club for so long and what it meant to him. “Then the boys at Manchester City have had a phenomenal season, an absolutely incredible season, and of course that’s been the Holy Grail for them to get this final trophy that they hadn’t won up until now. “I’m delighted for all of them. It’s great to see them enjoying themselves and also it’s brilliant for us as a group. “We’ve got so many experiences now of individual players winning big trophies, and that’s so important for our development as a team. It’s fantastic on all counts.” Read More Charity boss speaks out over ‘traumatic’ encounter with royal aide Ukraine war’s heaviest fight rages in east - follow live Tottenham progressing in bid to sign Brentford goalkeeper David Raya Sir Alastair Cook strikes 74th first-class century as Essex dominate Somerset French Open day 15: Major history for Djokovic, third final defeat for Ruud

ChatGPT’s creators have attempted to get the system to explain itself. They found that while they had some success, they ran into some issues – including the fact that artificial intelligence may be using concepts that humans do not have named for, or understanding of. Researchers at OpenAI, which developed ChatGPT, used the most recent version of its model known as GPT-4 to try and explain the behaviour of GPT-2, an earlier version. It is an attempt to overcome the so-called black box problem with large language models such as GPT. While we have a relatively good understanding of what goes into and comes out of such systems, the actual work that goes on inside remains largely mysterious. That is not only a problem because it makes things difficult for researchers. It also means that there is little way of knowing what biases might be involved in the system, or if it is providing false information to people using it, since there is no way of knowing how it came to the conclusions it did. Engineers and scientists have aimed to resolve this problem with “interpretability research”, which seeks find ways to look inside the model itself and better understand what is going on. That has often required looking at the “neutrons” that make up such a model: just like in the human brain, an AI system is made up of a host of so-called neutrons that represent parts of the data it uses. Finding those is difficult, however, since humans have had to pick through the neurons and manually inspect them to find out what they represent. But some systems have hundreds of billions of parameters and so actually getting through them all with people is impossible. Now, researchers at OpenAI have looked to use GPT-4 to automate that process, in an attempt to more quickly pick through the behaviour. They did so by attempting to create an automated process that would allow the system to provide natural language explanations of the neuron’s behaviour – and apply that to another, earlier language model. That worked in three steps: looking at the neuron in GPT-2 and having GPT-4 try and explain it, then simulating what that neuron would, and finally scoring that explanation by comparing how the simulated activation worked with the real one. Most of those explanations went badly, and GPT-4 scored itself poorly. But researchers said that they hoped the experiment showed that it would be possible to use the AI technology to explain itself, with further work. The creators came up against a range of “limitations”, however, that mean the system as it exists now is not as good as humans at explaining the behaviour. Part of the problem may be that explaining how the system is working in normal language is impossible – because the system may be using individual concepts that humans cannot name. “We focused on short natural language explanations, but neurons may have very complex behavior that is impossible to describe succinctly,” the authors write. “For example, neurons could be highly polysemantic (representing many distinct concepts) or could represent single concepts that humans don’t understand or have words for.” It also runs into problems because it is focused on specifically what each neuron does individually, and not how that might affect things later on in the text. Similarly, it can explain specific behaviour but not what mechanism is producing that behaviour, and so might spot The system also uses a lot of computing power, the researchers note. Read More Google to unveil major new AI AI robots figure out how to play football in shambolic footage White House asks hackers to break ChatGPT White House reveals plan to ‘protect’ citizens from danger of AI DeepMind boss says human-level AI is just a few years away Regulator to probe use of artificial intelligence such as ChatGPT

Craig Counsell's postgame comments suggest that he may be on his way out after the end of the Brewers season.

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Carolina Panthers linebacker Shaq Thompson has a broken right leg and is expected to miss the remainder of the season, according to coach Frank Reich

KAMPALA Uganda's President Yoweri Museveni said late on Saturday there had been casualties during an attack by Somalia's