Dele Alli salvaged a late point for Tottenham against Watford as VAR took centre stage in the Premier League on Saturday.
Abdoulaye Doucoure swept home Daryl Janmaat’s cross to open the scoring but when Hornets goalkeeper Ben Foster flapped at a late cross, Alli controlled the ball with his shoulder before firing into the unguarded net.
The video assistant referee gave the goal following a review, but the big screen inside the Tottenham Hotspur Stadium indicated that Alli’s strike had been disallowed. After a period of confusion, the goal was eventually given and Watford were denied their first win of the season.
Quique Sanchez Flores’ side also had a strong claim for a penalty turned down by the video assistant referee after Gerard Deulofeu was brought down by Jan Vertonghen in the first half.
Second-placed Manchester City narrowed the gap on leaders Liverpool with a routine 2-0 win at Crystal Palace in Saturday’s late game.
Wayne Hennessey produced fine saves to deny Bernardo Silva and Ilkay Gundogan in the first half, but two goals in quick succession from Gabriel Jesus and David Silva gave Pep Guardiola’s side a comfortable lead at the break.
Christian Benteke powered a header against the crossbar in the second half, while Kevin de Bruyne struck the post with a header of his own as City moved to within five points of Jurgen Klopp’s charges in the standings.
At the King Power Stadium, Chris Wood’s late goal was ruled out by VAR as Leicester City marked the anniversary of former owner Vichai Srivaddhanaprabha’s death with a 2-1 victory over Burnley.
Wood’s powerful header opened the scoring for the Clarets, but goals from Jamie Vardy and Youri Tielemans either side of half-time put the Foxes in the driving seat.
The Burnley forward thought he had salvaged a draw for his side eight minutes from time, but the video assistant referee ruled that the 27-year-old had accidentally tripped Jonny Evans in the build-up.
Marcos Alonso scored the only goal of the game as Chelsea beat Newcastle to claim their fifth successive league victory and move into the top four.
Frank Lampard’s side struggled to create clear-cut chances in an even first half at Stamford Bridge, but Alonso’s superb angled drive earned Frank Lampard’s team all three points with 17 minutes remaining.
In the day’s early game, Everton lifted the pressure on boss Marco Silva with a deserved 2-0 victory over a disappointing West Ham at Goodison Park.
Bernard finished a flowing Toffees move from a tight angle to open the scoring, before second-half substitute Gylfi Sigurdsson sealed the win with a marvellous drive from the edge of the penalty area.
Matt Targett also scored late on to earn Aston Villa a 2-1 win over 10-man Brighton at Villa Park. Adam Webster broke the deadlock for the Seagulls with a free header, but Aaron Mooy was dismissed for a second bookable offence late in the first half.
Conor Hourihane had a goal chalked off by VAR soon afterwards, but Jack Grealish fired home Frederic Guilbert’s cross before Targett clinched the win for the hosts with virtually the last kick of the game.
Raul Jimenez’s penalty cancelled out Danny Ings’ strike to earn Wolves a 1-1 draw at home to Southampton.
Ings found the bottom corner to give the Saints the lead eight minutes into the second half, but Jimenez – whose first-half strike was disallowed by VAR for an apparent handball – slotted home from the penalty spot after Pierre-Emile Hojbjerg had tripped Matt Doherty.
At the Vitality Stadium, Norwich City held Bournemouth to a goalless draw to claim their first away point since gaining promotion to the top flight.
Liverpool travel to Manchester United in Sunday’s only game (16: 30 BST), before Sheffield United welcome top-four hopefuls Arsenal to Bramall Lane on Monday evening (20: 00 BST).
IBM’s Thomas J. Watson Research Center in Yorktown Heights, New York, may be nondescript, but it houses some of the brightest minds working on artificial intelligence today. I spent a day there speaking with several top executives on IBM’s AI ambitions.
The company is serious about the technology and thinking in decades, not years. A major challenge, however, will be the move from narrow to broad AI.
IBM has produced some of the most high-profile AI machines of the past decade, like one that can go head-to-head with the World’s best debaters.
It’s continuing to build upon that legacy, including a new program in development that can automatically provide play-by-play commentary for soccer matches.
Tucked in a luscious forest in Yorktown Heights, New York, a hamlet about an hour outside New York City by train, is IBM’s Thomas J. Watson Research Center.
It’s a rather nondescript croissant-shaped building that may surprise those who were expecting a modern-looking facility where legions of robots roam down bright white hallways and regularly interact with employees.
But it houses some of the brightest minds working on artificial intelligence, who are doing the early-stage work on what will become commercial applications that change how we watch sports, debate one another, or even judge whether an algorithm is biased.
After spending a day at the center and meeting with several executives, I left with four main takeaways of where IBM is at on AI, where it’s heading, and the challenges it faces to get there.
Robots IBM is thinking about AI in decades, not years
From machines that go head-to-head with the greatest debaters or pinpoint the most exciting moments of a sporting event to a slew of offerings that ensure algorithms are fair and explainable, IBM is serious about artificial intelligence.
The company is mapping its AI journey in decades, not years, and pursuing revolutionary technology that could redefine how companies operate. Among the other notable milestones, it launched a joint research laboratory with the Massachusetts Institute of Technology in 2017 and had 175 papers published at eight AI conferences in the past year alone. And with $2.58 billion in revenue in 2018, IBM again ranked as a market leader in AI product.
Aside from the machines themselves, the company is also trying to position itself as a leader in ethical AI to help overcome escalating concerns with the technology. Part of that effort is trying to change the negative connotations that surround the term “artificial intelligence.”
“AI is a loaded term,” Dario Gil, the director of IBM Research, told Business Insider. “If only we could just start adding a little bit more precision around language, that would be helpful.”
Robots The journey from narrow to broad AI will be difficult
While the platforms are transforming operations, Sriram Raghavan, the vice president of IBM Research AI, argues that ultimately, it’s an inefficient system. With so many models, organizations are unlikely to “spend six months and a few hundred million dollars” to implement each one of them, he said.
So instead of a bespoke application that requires a large amount of data, IBM is focused on developing what they refer to as “broad AI,” or models that can manage a wide variety of tasks simultaneously with much less information. That effort, however, will take decades, according to Raghavan.
“We are making progress on it significantly,” he told Business Insider. But “it’s going to be a journey. We’re talking about inventing brand-new techniques.”
Robots Trust in AI remains a key problem
Companies are rushing to adopt artificial intelligence, but trust in the platforms is still a major problem.
IBM is trying to demystify the questions around the technology in a number of ways. But one problem remains in defining what a fair model is. To solve that issue, IBM introduced “AI Fairness 360,” a library of algorithms that can be used to check whether a data set is biased.
“You actually grow this culture of understanding AI biases. And as we all evolve, then eventually, maybe one day, it’s not going to be a problem,” Saska Mojsilovic, who heads the Foundations of Trusted AI group at IBM, told Business Insider.
Explaining the AI is also a challenge. Say a financial institution uses an algorithm to determine whether someone qualifies for a loan. If the application is denied, that company needs to be able to outline to the customer the reasoning behind the decision.
IBM recently introduced a tool kit known as “AI Explainability 360” that consists of algorithms, demos, and other resources, and provides insight into how models come to a final conclusion, including one that outlines which information was used to come to the decision. It also shows which features that, if they were present, would have reversed the choice. So if a loan application is denied, the algorithm could provide a route for a customer to improve their chances the next time.
Robots If you want to see IBM’s AI capabilities, watch a major sporting event
One technology in use is an AI-based program that automatically analyzes the sound of the crowd, the reaction of a player or players, and other factors to determine the most exciting moments of events like the Masters Tournament and the US Open.
Even in sports, however, IBM thinks about how to make the model more fair.
One concern, for example, was how to adequately measure audience reaction on holes or courts where the crowd may not be as large as others. The team employed Watson OpenScale, a product that takes real-time feedback and adjusts AI models to make them more trustworthy. In golf, for example, the platform monitors the estimated crowd size and automatically reweights that category when considering the overall output.
“It’s a nice illustration of what it really means to have to monitor your models once they are in deployment,” said John Smith, who heads the development of vision, speech, and language AI tools at IBM Research.
IBM is experimenting with automated sports play-by-play commentary. The company is testing the product on past soccer matches because it “wanted a challenge,” according to Smith.
Once the model is successfully trained, the hope is it will able to ingest the raw footage and transform the raw pixels into language. It’s a huge evolution from AI-based applications that can scan still images to determine the object and come up with a caption.
Women’s fashion chain Bonmarché has appointed administrators, putting the future of the business in doubt.
The chain’s 318 shops will remain open while a buyer is sought for the chain.
Bonmarché chief executive Helen Connolly said she had made the decision with “deep regret and sadness”, and blamed tough High Street trading conditions for the move.
The Yorkshire-based chain, which specialises in clothing for the over-50s, employs 2,887 people.
“We have spent a number of months examining our business model and looking for alternatives. But we have been sadly forced to conclude that under the present terms of business, our model simply does not work,” she added.
Ms Connolly said the firm had considered a refinancing or a rescue deal, known as a company voluntary agreement (CVA) with its landlords and lenders.
This is an insolvency process that allows a business to reach an agreement with its creditors to pay off all or part of its debts and is often used as an opportunity to renegotiate rents.
However, she said the firm had concluded that neither option would “fundamentally change the core challenges facing the business”.
“We are sadly no longer in a position to demonstrate to our shareholders that the business can continue as a going concern,” she added.