Category Archives: Chess Engines

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Tilting Point and Polygon Studios announced a multi-year partnership on Web3 games. Tilting Point will publish its games it has 10 games in the works using the Polygon Network to integrate Web3 features.

Out of the 10 games that grow from the partnership, three are existing titles. These include Astrokings, from Tilting Points recently acquired developer AN Games, The Walking Dead: Casino Slots, and Chess Universe.

Polygons Ryan Wyatt said in a statement, Tilting Point is set to bring a new level of quality to Web3 gaming, accumulated from a decade of building and publishing mobile games. This partnership will help solidify Web3s place in the gaming industry, and were excited to start developing games that champion user ownership and immersive gameplay.

According to Tilting Point CEO Samir Agili, the partnership will make Tilting Point the ideal developer for both native Web3 developers and those looking to bridge their games from Web2. As he told GamesBeat in an interview, Tilting Points strength has been in having fantastic developers over the years, working with some of the best independent developers on the market, bringing fantastic, big IPs Spongebob, Walking Dead, Star Trek to existing engines and making them better.

In addition to Polygon, Tilting Point also partnered with Stardust, a platform that helps developers integrate NFTs into their titles. It announced this partnership earlier this year.

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Tilting Point partners with Polygon on Web3 games - VentureBeat

Saturday 16 April 2022 10:00 am

As the nation begins to plan summer breaks, following a tortuous two pandemic-fuelled years, a collective sigh of relief should be heard from Somerset to Stoke. But theres little relief to be had when a broken system is driving a false market of competition.

For years, the travel industry network titans have been able to control the price of holidays with artificial competition pitting customers between each other making it seem like theres either high demand or genuine bargains to be had.

Some of the online booking agents can be accused of behaving more like monopolies; setting an ever-spiralling cost which leaves less change in the pocket for hoteliers and holiday makers alike. There are no winners in this system.

These monopolies place focus on growing their cut when booking a stay rather than on user experience and achieving the best service and price for their customers.

Artificial competition between booking sites provides customers with a false sense that they are making a saving on their holiday. Instead at the same time, hotels are landed with growing commissions from the big booking platforms which eat away at their bottom-line causing price rises across the board both for consumers and suppliers.

The established big-brand online travel agents are able to push this dominance by spending billions a year bidding against each other on search engines and its all perfectly legal to do.

With soaring costs, they charge hotels commission rates that on average range from 15 per cent to 25 per cent on every booking creating a price disparity in which both customers and suppliers lose out when booking a hotel room. In real terms, thats less sunset holiday cocktails and less paella in the sun. In other words, less of what we love about holidays.

Furthermore, hotels are often locked into rate parity agreements with the big online booking sites, meaning that they cannot advertise a lower rate to any customers.

This creates a problem: rooms lay dormant, when they could have been filled by guests to shore up the hotels business. With 30 to 40 per cent of revenue derived from additional sales once guests have stayed, such as food and drink and parking, hotels cant afford to have non-occupied spaces.

But look yonder and Big Tech may just turn the tide on this lose-lose situation. By digitally connecting travel suppliers to the booking public consumers, therefore cutting out the expensive intermediary, the end could be nigh for the price fixers.

Playing a game of chess with the giants wont be easy, as they will have their next 6 moves planned out in meticulous detail. But at some point customers will get tired of being pawns in their game, and you can bet your bottom dollar, the travel titans will be toppled.

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Online booking agents have been behaving like kings - it's time to topple them - City A.M.

Online Chess Games

In this games collection, you'll find a variety of fun chess games to play. If you're looking to play against other chess players online, the most popular online chess game is Master Chess. Another popular chess game with a multiplayer game mode is Spark Chess.

Chess is a skill game where practice directly improves gameplay. Practice chess for free in the game Chess Challenges. There are many situational challenges to work through that test your ability to make the optimal play and get your opponent in checkmate (while avoiding it yourself!).

There are many variations of chess, with some clever games making their own mark on this classic game. For games based on chess or with elements of chess, check out Chess Mazes and Pawnbarian.

Unlike most regular games where the AI is as dumb as a rock, computers have been destroying the best players at chess since Deep Blue beat the world champion, Garry Kasparov, in 1997. Since then, chess engines have dominated the world's greatest players, leading to the rapid advancement of chess game theory.

Chess is a skill-based board game played between two players. It's a game that's induced both frustration and success in many of the world's top players, from Magnus Carlsen to Hikaru Nakamura. It has long been seen as an intellectual game, but anyone can learn and improve with practice!

We collected 15 of the best free online chess games. These games include browser games for both your computer and mobile devices, as well as apps for your Android and iOS phones and tablets. They include new chess games such as and top chess games such as Master Chess, Chess Arena, and Spark Chess.

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Chess Games - Play Chess Games on CrazyGames

[Note that Jon Speelman also looks at the content of the article in video format, here embedded at the end of the article.]

Last Saturday, March 12th, I was at the RACsclubhouse (Royal Auromobile Club) in Londons Pall Mall for the annual Varsity match between Oxford and Cambridge Universities.

First played in 1873, this is the worlds oldest chess contest and was for years reported on in the pages of the famous Russian chess magazine 64. When I played for Oxford from 1975-7, Cambridge were in the ascendant and we lost all three matches: personally, I lost to Michael Stean and drew twice with Jonathan Mestel. These things swing over time, and at the moment its very close. Cambridge started as the Elo favourites, but after an endgame save in the last game to finish, Oxford ran out the winners by the narrowest possible margin of 4-3, with the overall score now 60-58 to Cambridge with 22 draws.

The 1921 Oxford team | Find more info at BritBase, John Saunders excellent games archive

The match has been at the RAC now for nearly half a century, with a dinner afterwards, and in recent years internet coverage and commentary on site. This years commentator was Mathew Sadler and for some of the afternoon I acted as sous-commentator, chatting with Matthew about the games.

At one stage I mentioned that I normally use Houdini as my analysis engine, but Matthew [pictured], who of course is immensely knowledgable about computer chess and has written extensively on Alpha Zero, told me that the latest version of Stockfish is much stronger. I therefore decided to switch to it as my default analysis engine in ChessBase, but Im now wondering (and of course this can be changed with the click of a mouse) whether I was right.

The question of course is how to use the analysis and assessments produced. Most computer engines (Alpha Zero and its daughter Leela are different) are giant bean counters which produce a maximin, maximizing the minimum score they get against the opponent's supposedly best play. Depending on the accuracy of the analysis and the size of the beans, the scores will vary, and while Houdini with its rating, I dunno, of 2700 or 2800 tends to bumble around with assessments quite close to zero,Stockfish thunders its pronouncements giving assessments like +/- 2.5 in positions which look to my human eye to be fairly but not entirely clear; and going up/down to +/- 6 or more when even my human eye can see that it oughtto be winning.

The Ruy Lopez Breyer Variation

Pavel Eljanov explains in depth what Gyula Breyer already saw in 1911 and what became an opening choice of the likes of Kasparov, Kramnik, Anand or Carlsen. The Breyer Variation, which is characterised by the knight retreat to b8.

The certainty is wondrous but rather unsettling. When I was a kid, I no doubt made the mistake of trying to play the best moves. Nowadays, of course, I know better, and while I will stop and indeed try to work out the best solution in an obviously utterly critical position, most of the time I poddle along choosing decent moves without worrying too much about whether there are better ones. To do this, Ive created a story for myself that I can quickly select goodish moves in reasonable positions (of course its much harder if youre under heavy pressure). But gazing into the face of God, I have to be careful not to be blinded and to undermine this essential fiction.

So Im still thinking about what to do. Perhaps with enough time available I should use both, analysing both with St Houdini and the deity Stockfish. Certainly when Im streaming I try much of the time to use my own carbon-based resources and sometimes dip into a fairly hobbled version of Stockfish which isnt too scary. But occasionally, when I want to know the truth I turn to My Lord Sesse (the Norwegian-based fusion of Stockfish and ridiculously powerful hardware).

One point I should make in general is not to take too much notice of computer assessments, even if they are right. They are extremely relevant to the worlds top players when they are doing opening preparation, but for the rest of us they are just a tool. In particular, Ive noticed that when people check their games after playing online, there are some engines which dish out ??s like confetti. Of course people do play some terrible moves, especially at blitz, but ?? should mean a move that loses a piece or maybe even a rook or at a higher level makes a complete mess of the position. It shouldnt mean that the assessment has dropped drastically without in human terms affecting the result.

One reason I go to the Varsity match is to help choose the Best Game and Brilliancy Prize often with Ray Keene, in this case with Matthew. Both receive works by the artist Barry Martin and, in this case, since the Brilliancy Prize was shared, both players got prints.

Cambridge team: back, left to right: Miroslav Macko, Matthew Wadsworth, Imogen Camp, Harry Grieve. Front, left to right: Jan Petr, Declan Shafi (captain), Ognjen Stefanovic, Koby Kalavannan. | Photo: John Saunders

For the best game, we decided on the board 1 win by Oxford, and Ive annotated it, out of interest, using both engines. Ive given them a fairly short time to make an assessment, so they might have changed their minds had they worked for a longer period of time but this experimentnonetheless gives an indication of the huge difference between them.

Select an entry from the list to switch between games

Understanding Middlegame Strategies Vol.3 - The Hedgehog

Throughout my playing career I have found the Hedgehog one of the most difficult type of positions to master. The basic aim of this video is to improve understanding of these complex positions and to help tournament players score better.

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A tale of two universities and two engines - Chess News

The first event of the 2022 Champions Chess Tour saw Ian Nepomniachtchi winning the preliminaries with a 29/45 score. In the second tournament of the series, Le Quang Liem managed to score 32 points in as many games to win the Charity Cup prelims. Both times, Magnus Carlsen finished in sole second place.

It is true that Les score has to do with the fact that the participants of the Charity Cup had a lower rating average (2693) than the participants of the Airthings Masters (2708), but that does not take away from his remarkable achievement. Le, after all, vastly outscored the likes of Ding Liren, Jan-Krzysztof Duda and Richard Rapport not to mention that he finished ahead of the world champion himself.

The Ruy Lopez Breyer Variation

Pavel Eljanov explains in depth what Gyula Breyer already saw in 1911 and what became an opening choice of the likes of Kasparov, Kramnik, Anand or Carlsen. The Breyer Variation, which is characterised by the knight retreat to b8.

With Le and Carlsen easing their way into the knockout, Tuesdays excitement for the spectators was provided by the fight for the last qualifying spots. Going into the final round, no fewer than five players had between 19 and 21 points, and all of them were one bad result away from being eliminated.

In the end, Vidit, Praggnanandhaa and Rapport were the ones missing the cut, while David Navara and David Anton made it through thanks to wins over Pragg and Ju Wenjun respectively. Particularly impressive was Antons performance on day 4, as he scored 3/3 (or 9/9, with the football scoring system) to climb from eleventh to fourth place and get a spot in the quarterfinals.

Navara, Pragg and Rapport all finished on 21/45, but Navara was the one advancing to the knockout stage thanks to his better tiebreak score: a larger number of wins than Rapport and a better Sonneborn-Berger score than Pragg.

16-year-old Praggnanandhaa entered the final day of the preliminaries a point behind Vidit and Hans Niemann, topping the bottom half of the standings table. After drawing Niemann, the youngster convincingly defeated Van Foreest with the white pieces.

Van Foreest had overestimated his chances in the late middlegame, pushing his f-pawn to leave his king lacking defenders. Pragg immediately went for an attack, which culminated with 31.Rxg5+ Kh4 32.Qd4+ Kxg5 33.Ne4+, forking queen and king. Van Foreest resigned.

Going into round 15, Pragg had 21 points, as did his opponent Anton, while Rapport (20 points), Vidit (19) and Navara (18) all had chances to climb to the top half of the table.

In a complicated struggle against Anton, Pragg got what the engines considered to be a clearly superior position in the middlegame.

Smash the Sicilian with the Smith-Morra Gambit

The Smith-Morra Gambit (1.e4 c5 2.d4!) is a great attacking weapon against the popular Sicilian . On move two White sacrifices a pawn for fast development and good attacking chances, and Black can easily fall into one of the many devious opening traps.

Black has an exchange for a pawn, and he also has the bishop pair, while both players have mobile pawn chains, one in each flank despite the engines evaluation, all three results are possible here, especially given the tournament situation and the fact that this was a 15-minute encounter!

In the ensuing struggle, it was Anton who managed to better handle the tension, getting an 83-move win that catapulted him to fourth place in the final standings table.

Find both Praggnanandas games in the replayer below.

In the penultimate round, runaway leader Le defeated Navara from a materially balanced rook endgame. As Karsten Mller states in his annotations below, rook endings have a large drawish tendency, but a powerful passed pawn can change that picture.

50...Kd5, instead of 50...Rc4 (which would fail to 51.g4), was correctly chosen by Le, who went on to score his ninth win of the tournament!

Read more from the original source:

Charity Cup: Anton wins three in a row to reach knockout - Chess News

It's almost lights out on the new season of Formula 1 racing. This year, the chase for the championship begins on Sunday, March 20, at the Bahrain Grand Prix and continues for 22 races, concluding in November with the Abu Dhabi Grand Prix.

In a thrilling finale, last season's winner wasn't determined until the final race when Max Verstappen of Red Bull beat out Lewis Hamilton of Mercedes for the Drivers' Championship -- in highly controversial fashion. It was Verstappen's first F1 title and ended Hamilton's run of consecutive championships at four. Mercedes, however, beat Red Bull in the Constructors' Championship, which is given to the racing team with the most points.

Will Verstappen and Red Bull continue to overtake the once-dominant Mercedes? Can 37-year-old Hamilton regain his crown as F1's best driver? Will other teams, such as Ferrari and McLaren, climb the leaderboard?

Those looking to follow all the drama at home in the US will need access to ABC, ESPN, ESPN 2 and ESPNews in order to catch every second of the action. The entire race weekend, including practice sessions and qualifying, will be shown in the US on ESPN's family of television networks.

No single provider has exclusive rights to the network, so there are plenty of ways to get ESPN and watch the races without cable. We've broken down everything you need to know in order to stream F1 races this season.

Lewis Hamilton, driving Mercedes (left), and Max Verstappen, driving Red Bull, are set to open up the new F1 season.

What is F1 and how is it different from IndyCar?

Both IndyCar and F1 are open-wheeled, single-seater racing formats. This means that the cars can only fit one person and have uncovered wheels that protrude from the body of the vehicle. Despite their basic similarities, F1 and IndyCar offer very different experiences.

In F1, there are only 10 teams, with two drivers apiece for a total of 20 drivers. Most races must go for 305 km, which is about 190 miles. Each driver needs to use two different tires in the race, so a pit stop is mandatory, though cars are not allowed to refuel. Races average around two hours in length and are held at venues all over the world.

Teams spend hundreds of millions of dollars each year developing their cars. All cars must have certain elements -- for example, gearboxes must have eight gears plus a reverse and last for six consecutive races -- but teams have leeway to tweak and change some parts of their car, including their engines, in the pursuit of speed.

In contrast, the cars featured in IndyCar are more standardized. They all have the same aerodynamic kit and chassis and can only be powered by one of two engines -- either a Honda or a Chevrolet. That said, teams are allowed to develop some of their own parts, like dampers and some of their suspensions.

IndyCar races occur on a wide range of tracks, from fast ovals to road and street courses. The length of the races also varies, with some, like the Indianapolis 500, lasting 500 laps and taking over three hours to complete. Not surprisingly, refueling during pit stops is a big part of the strategy during IndyCar races. Teams can field more than two cars, meaning that the amount of drivers on the grid fluctuates from race to race.

IndyCar is mostly considered an American sport and does not have the same level of money and glamour associated with it compared to the globe-hopping F1 circuit.

Why should I care about F1?

F1 races might best be described as a sort of action-packed chess match that takes place while drivers are throttling around a track at close to 200 mph. Teams need both strategy and skill to compete against some of the best minds in motorsports.

F1 is also full of strong personalities. The Netflix documentary series F1: Drive to Survivefollows many of the teams and drivers over the course of a year and has helped raise the profile of the sport in the US. Released earlier this month, season four of the series chronicles the tight championship race between rivals Verstappen and Hamilton. It also focuses on the internal battles between drivers on the same team, while giving viewers a peek into the tense, pressurized world of elite racing.

Does F1 stream on ESPN Plus?

ESPN does not air any F1 coverage on its ESPN Plus streaming service. If you want to watch the practices or races you will need a television provider of some kind or to pay for F1's $80 per season TV Pro subscription.

Races are held on Sunday and are usually spaced two weeks apart. Here's the entire schedule, all times ET:

Race weekends normally start on Friday with multiple practice runs and continue on Saturday with qualifying. The races themselves take place Sunday. ESPN typically airs practices and qualifying on a mix of ESPN 2 and ESPNews, while the races tend to air on ESPN. F1 events in North America often land on ABC.

As of now, the network has only solidified the exact channel lineup for the first two races of the season, both of which air on ESPN. Here are some of the best ways to catch the entire race weekend without cable.

You can catch the entire race weekend with a subscription to YouTube TV. ABC, ESPN, ESPN 2 and ESPNews are all included in the package, which means you'll have all the channels you need in order to watch every second of the action.

Read our YouTube TV review.

Hulu Plus Live TV is a little more expensive than YouTube TV, but it also offers all the channels you need to watch every second of race weekend. As an added bonus, Hulu Plus Live TV comes with the rest of the Disney Bundle, which includes a subscription to Disney Plus, as well as ESPN Plus. F1 races don't air on ESPN Plus, but the service offers a ton of other content for die-hard sports fans.

Read our Hulu Plus Live TV review.

Sling TV's $35 Orange plan might be a good choice for F1 fans who are primarily looking to just watch the races on Sundays. This plan is one of the cheapest ways to get access to ESPN and ESPN 2. Those looking for ESPNews will have to opt for the $11 Sports Extra ad-on. Sling TV lacks ABC, which could be a problem for fans hoping to catch the F1 races in North America.

Read our Sling TV review.

FuboTV costs $70 per month and includes ABC, ESPN, and ESPN 2. The base package lacks ESPNews, but you can add it for an extra $8 a month with the Fubo Extra Package or pay for the $80-a-month Elite streaming tier that includes Fubo Extra. Check out whichlocal networks FuboTV offers here.

Read our FuboTV review.

DirecTV Stream is the most expensive live TV streaming service. Its cheapest, $70-a-month Plus package includes ESPN, ESPN 2 and ABC, but you'll need to move up to the $90-a-month Choice plan to get ESPNews. You can use itschannel lookup toolto see which local channels are available in your area.

Read our DirecTV Stream review.

For gearheads looking to get every angle on the action, F1 offers its own streaming service. F1 TV Pro costs $80 per season and gives fans access to all races from F1, F2, F3 and Porsche Supercup. You'll be able to livestream every track session from all F1 grand prix and have access to all driver onboard cameras and team radios. You'll also be able to watch full on-demand races, replays and highlights, along with F1's historic race archive.

F1 also offers a TV Access Plan for $27 per year, which only gives you on-demand access to races once they have been completed. Users will still be able to view all F1 onboard cameras, along with full replays of F1, F2, F3 and Porsche Supercup. It also includes the historic race archive.

See the latest cars and automotive trends from supercars to SUVs. Delivered Tuesdays and Thursdays.

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Formula 1: How to Watch the Bahrain Grand Prix and F1 Racing in 2022 - CNET

After move 38, Magnus Carlsen found his king left with just one safe square to seek fleeting refuge. The end was in sight and inescapable. Sixteen-year-old Indian GM R Praggnanandhaa laid out the traps beautifully with Black, which culminated in moving his light-squared bishop to the c2 square, cordoning off the white queen's ties with the second rank. Both players knew it was over. The fidgety 16-year-old sank back in his chair, shook his head and rested a palm against his face in mild disbelief as Carlsen promptly resigned after 39 moves.

Praggnanandhaa had just become the third Indian to beat Carlsen in tournament play - after Viswanathan Anand and P Harikrishna.

The massive moment in the Indian teen's young career arrived in the early hours of Monday at the Airthings Masters, a 16-player online rapid tournament. It's the first leg of the Play Magnus group-run Champions Chess Tour and the round-robin is scored football-style - three points (and $750) for a win, and one point (and $250) for each draw. Each player has 15 minutes for all moves plus a 10 second per move increment.

On Move 32, in what appeared to be an equal endgame, Carslen stumbled into a tactical blunder. He trapped his own knight by pushing it to the c3 square. Chess engines went wild, giving Black the overwhelming odds for a win. Praggnanandhaa leaned forward over his screen, and his surprised pupils filled the webcam feed. He just needed seven more moves to tuck into a win. And win he did.

2 Related

To wind his body clock and mind to stay focused through games that start late at night in India and spill into the early hours, Praggnanandhaa began work 10 days in advance. He tweaked his sleep and training schedule to mimic the tournament timings.

The Indian began on a disastrous note on Day 1, losing three games in a row. Day 2 turned out to be a world apart. Within the space of a few hours, he had a win each against two top-10 players - Levon Aronian and Carlsen. Further, to outwit a player of Carlsen's strength without the first-mover advantage of White, deserves even more credit.

"What I really admire about him is that he takes the blows and does it his way, as the song goes," Anand, who mentors Praggnanandhaa along with other teen Indian GMs, told ESPN, "In Wijk aan Zee he had some really tough blows but still fought and beat (Andrey) Esipenko in the last round. The first day in the current tournament was really bad for him but on the second day he came up with two very good wins. His fighting spirit is really something."

Praggnanandhaa was always something of a precocious talent. In 2016, he became the youngest International Master in history - at 10 years, 10 months and 19 days. Two years later he became the then second-youngest GM (after Sergey Karjakin) at 12 years, 10 months, 13 days. At sixteen today, he belongs to the group of Indian teens who are throwing down the gauntlet on the world chess circuit.

"Before the pandemic, he was in a really good form and reached 2600 Elo rating at the age of 14. The long break in tournaments impacted him quite a bit, particularly in confidence," Praggnanandhaa's coach RB Ramesh said, "His results in the past six months has swung between extremes. In some games he has been playing like a 2750 player, in others he's operating at a 2550 level. The fluctuation can be worrying and needs to be stabilised. This win against Magnus is important. Beating one of the strongest players in chess history is a huge moment for him."

Among Ramesh's pre-tournament pointers for Praggnanandhaa has been to completely stay away from social media. This, he believes, might ease the youngster of the pressure of being watched. "He knows people are following live streams of his games, commenting on his play on social media and going through them can have a direct impact on him. He's been running into time trouble pretty often in tournaments and it's largely psychological. The burden of expectation can get to him at times. When he loses, it sometimes affects him more than it should. He's working on it, but he's just 16 and I'm really glad at how he's handled himself against some of the top guys."

Soon after his win past 2 AM, when asked if he had any celebratory plans, Praggnanandhaa could only think of one possible way to unwind. "I'm just going to go to bed."

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Praggnanandhaa, 16, becomes only third Indian to beat Magnus Carlsen in stunning upset - ESPN

Artificial Intelligence is very much alive in our personal and professional lives recently

Artificial intelligence (AI), like robotics, has long been seen as future technologies. However, much as with robots, we can now affirm that AI is notjust science fiction, but much more than that. AI is very much alive in our personal and professional lives, and it is swiftly catching up to mobile devices in terms of popularity.

There is not a single activity in our daily activities, the use of AI is not impacting us. From Alexa, Siri to self-driving cars, AI is stepping up to assist us just like a human would. The vision of self-driving automobiles in intricate road situations that comes to mind when onethinksof AI is the first thing that springs to mind, and this can be achieved through the use of Machine Learning and Deep Learning. But the main question that arises here is- Is AI as Intelligent as we think it to be?

AI is a broad word with several definitions, especially when it comes to general intelligence. John McCarthy coined the term artificial intelligence (AI) in 1955 to describe a system that resembles human intellect and problem-solving. AI has become a blanket term for software that executes difficult activities that previously required human input, such as online customer service or chess play. Machine learning and deep learning are two subfields of deep learning that are frequently used interchangeably.

Machine learning is a subfield of artificial intelligence that was established by Arthur Samuel in 1959, which focuses on automatically identifying patterns and developing models from existing data using complex algorithms, as well as making predictions and inferences on fresh data, according to a more recent and widely used definition.

AI is frequently referred to as the driving force of todays technologies. As a result, it naturally elicits enthusiasm and great hopes. Neural Network models, used by computers, are modeled according to the functioning of the human brain which is excelling in previously unimaginable areas.

This has led us to hope that AI will one day surpass our intelligence and solve all of our problems. Language tools, such as virtual assistants or automatic translation tools, are examples of the increasingly advanced capabilities of language tools. Asthe underlying models of AIcan learn patterns from a big amount of data, language tools can mimic us.

However, AI is increasingly being used in decision-making processes in fields like human resources, insurance, and banking, to mention a few. Machines are starting to understand us and our preferences better by analysing human behaviour through a massive volume of input data. Recommendation engines are then easily filtering out content and making recommendations for us on social media for films to watch, news to read, or things to wear, helping us with decision making.

Thus, according to the normal population, these are the examples of Artificial Intelligence in this era, when being asked about it.

However, there is a huge difference between sounding like a human and being a human and the former necessarily does not mean that there is always human intellect attached to it. And this is exactly the deception that we are living in.

When we compare the abilities of a (voice-activated) virtual assistant to those of an average child when they talk about a toy car, for example, the tool requires a lot more data and it will struggle to grasp common knowledge, such as common sense. One of the most unique features of human intelligence is common sense, which no AI machine will ever be able to mimic.

According to Bourland, professor of electrical engineering at Idiap, all this contribution of AI necessarily does not make an Artificial Intelligence, Intelligent and has further stated that there exists no such system to date, that can replicate human intelligence even the slightest bit.

With the term AI gaining increased popularity currently, the major intelligent work done by the underlying technologies like Machine Learning and Deep Learning is getting overshadowed. Thus, the Machines used are Made Intelligent by a human-driven input and require a huge amount of good data, and is not an easy process.

The major drawback of the AI Machine in comparison to human intellect is the reasoning ability. The machines are easily able to offer adequate feedback and answers to the questions, however, they are handicapped in the area of providing logical reasoning, and explaining the process of reaching the conclusion.

In the most famous paper of Alan Turing (published in 1950), he answered the question Can machines think? By inventing the imitation game, which is still used today to interpret machine intelligence. The answer and results of the experiment, even after seventy years remains, that not a single artificial intelligence systemhas passed the Turing Test, which is quite baffling in times of today.

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Is Artificial Intelligence as Intelligent as We Think it is? - Analytics Insight

The computers and super engines have brought a vast difference between the modern chess and the chess that was played before the end of the 20th century. Though the game is still fascinating and mysterious as always, the way modern players approach chess today has completely changed.

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Anyone who dominates a sport for more than a decade defines its course and in chess that responsibility automatically belongs to the world chess champion Magnus Carlsen. The former world chess champion Garry Kasparov believes he is the best of traditional and modern chess combined in one mind.

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The Russian Grand Master said, Todays chess is in many ways Magnus chess. Magnus is clearly superior to all the rest of his generation of chess players.

Obviously, with modern technology, you can analyze chess games better than before, but you cant take help from the computer while playing an actual game. The way Magnus approaches his games is incredible to watch. As I remember while working with him, he was always able to disengage from the computer. In fact, he did not become a hostage to what he saw on the screen said Kasparov.

He further added, The machine helps to develop solution, but he always found the most interesting, pragmatic solutions specifically for modern chess.

Maybe this is the reason the Norwegian Grand Master is still at the top for over a decade, even though the game is constantly changing.

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Well, the simple answer would be that he has an extremely gifted mind, but thats just half of it. The reason he has dominated the game in such evolutionary times is that he has the perfect balance of technology and his ability to analyze the best moves. Its not just the classical chess that he has dominated. He is quite skilled at fast online chess as well.

Super engines can only give you information and million different moves, but as a player, its completely up to you how you maneuver your pieces on the board to outsmart your opponent, and apparently, Magnus knows it all.

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Is Magnus Carlsen the best chess player of all time?

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Time to think

Has Big Tech lived up to its purportedly altruistic ideals? Googles unofficial motto of dont be evil suggests that its intention was always benevolent, despite the deceptive and unethical practices it has adopted in a number of areas not least facial recognition software, which reportedly exploited homeless people of colour.

Bill Gates now heads one of the worlds largest private charities, yet the company he founded, Microsoft, is relatively open about its compliance with state censorship in China. Apple contributes millions of dollars in financial aid for disaster relief but has a grim track record when it comes to working conditions, including allegationsthat it has potentially directly or indirectly benefited from forced Uyghur labour. Amazons working practices have also come under serious scrutiny, especially in the wake of the pandemic and the recent destruction of one of its giant US warehouses by a tornado. As for Facebook (now Meta), there is blood on its hands after it failed to prevent its platform being used to incite violence against the Rohingya minority in Myanmar.

But computing was never about the greater good, no matter what those Big Five firms claim. It was, and still is, about the greater exploitation of productivity. From the moment humans sharpened a flint, technology has been a way to make tasks more effective and, nowadays, thats done for profit. Before we had digital computers, we had human ones: people usually women, as it was seen as a low-status role employed to calculate and repeat those calculations by hand. The goal is to maximise production, to capitalise, to hold market power.

THE Campus views: What can universities learn from Amazon?

It doesnt stop there, though. Big Tech reaches much further than might ever have been expected in the industrys early days. The rise of machine learning and the access to the vast quantities of user-centred data that spurs it on means that Silicon Valley corporations have a profound grip on our lives. They hold vast power and if we want to enjoy the conveniences of a digital society then we cant entirely avoid that. Its a trade-off. Our society thrives on interconnections and limitless access to information; at times, it needs it. Imagine this pandemic without that online space. Imagine getting through a day without your smartphone.

At present, the major developments in AI come from those with the money, the talent and the data. The worlds most powerful nations, the US and China, are also the AI superpowers. Start-ups making new leaps are acquired by established corporations. University researchers are poached into business, lured by high wages and (potentially) better working environments. The resources of grant-funded projects are microscopic when comparedwith the big players budgets. Can universities really have much influence on where the AI revolution takes us?

They can but the roles have changed. Universities are now working on a different scale, but we can still innovate, still foster ideas, still advocate for altruistic and beneficial technology. We can explore data and push for open science. We can work with industry to co-create and advise. And we can hold a mirror up to Big Tech firms and force them to look at themselves.

In the past few years, there has been a marked increase in the academic study of AI ethics. Although it was already an important subject in its own right, the escalation of algorithmic decision-making (and the fallout when those decisions go wrong) pushed ethics into the spotlight. The UK House of Lords Select Committee on Artificial Intelligence published its report in late 2018. It was well received by the community and acknowledged that ethical development was key, stating: The UKs strengths in law, research, financial services and civic institutions mean it is well placed to help shape the ethical development of artificial intelligence and to do so on the global stage.

Big Tech is STEM-focused and it often treats other fields as unimportant, dismissing centuries of philosophy, arts, humanities and social science as irrelevant. But it is learning that it needs to engage. An increased emphasis on the responsible development of technology means it has listened to experts outside its walls. Some of this is regulatory pressure, much comes from academia, but there is also a heartening increase in public awareness, engagement and activism. It didnt stop Google from firing its ethics researchers Timnit Gebru and Margaret Mitchell for self-critical research, but it did force it to re-evaluate its practices following the backlash.

But universities shouldnt be too smug. We need to get our own house in order too. When working with industry, look for strings. Plenty of institutions receive money from tech companies and its not unheard of for funding to cloud judgement something the Massachusetts Institute of Technology learned the hard way when it accepted donations from Jeffrey Epstein even after his conviction as a sex offender.

The slow and contemplative academic practices, often mocked by the fast-moving tech world, offer space to reflect on how new technologies are developed, deployed and used. We are an antidote to the goal-focused business world.

That said, we cannot be too slow. We are also perpetrators and victims of our own productivity practices. If we wait anything from a few months to a few years for a journal article to be published, weve missed the boat. We have to rethink our own ways of responding and interacting. When it comes to Big Tech, we can contribute in new ways, but we cant afford to be left behind.

Kate Devlin is reader in artificial intelligence and society at Kings College London.

How does it all end for humanity? Will it be a giant meteorite crashing from the sky, like it was for the dinosaurs? Or a catastrophic thermonuclear explosion, as we all thought it would be during the Cold War? Or a global pandemic many times deadlier than Covid-19?

Australian philosopher Toby Ord argues in his 2020 book The Precipice: Existential Risk and the Future of Humanity that, in fact, the greatest threat is posed by an artificial super-intelligence poorly aligned with human values. Indeed, he bravely (if that is the word) estimates that there is a 10 per cent chance of such an end in the next century.

As someone who has devoted his whole professional life to building artificial intelligence, you might think such concerns would give me pause for thought. But they do not. I go to sleep at night and try to dream instead of all the promise that science in general and AI in particular offer.

It may be decades, or even centuries, before we can build an AI to match human intelligence. But once we can, it would be very conceited to think a machine could not quickly exceed it. After all, machines have many natural advantages over humans. Computers can work at electronic speeds, which far exceed biological ones. They can have much greater memory, ingesting datasets larger than human eyes can contemplate and never forgetting a single figure. Indeed, in narrow domains such as playing chess, reading X-rays, or translating Mandarin into English, computers are already superhuman.

But the fact that more general artificial super-intelligence remains a distant prospect is not the reason that I am unconcerned by its existential implications. Im unconcerned because we already have a machine with far greater intelligence, power and resources at its disposal than any one individual. Its called a company.

No person on their own can design and build a modern microprocessor. But Intel can. No person on their own can design and build a nuclear power station. But General Electric can. Such collective super-intelligence is likely to surpass the capacities of mechanised super-intelligence for a long time to come.

That still leaves the problem of value alignment, of course. Indeed, this seems to be the main problem we face with todays companies. Their parts the employees, the board, the shareholders may be ethical and responsible, but the behaviours that emerge out of their combined efforts may not be. Just 100 companies are responsible for the majority of greenhouse gas emissions, for instance. And I could write a whole book about recent failures of technology companies to be good corporate citizens. In fact, I just have.

Consider, for example, Facebooks newsfeed algorithm. At the software level, its an example of an algorithm misaligned with public good. Facebook is simply trying to optimise user engagements. Of course, user engagement is hard to measure, so Facebook decided instead to maximise clicks. This has caused many problems. Filter bubbles. Fake news. Clickbait. Political extremism. Even genocide.

This flags up a value alignment problem at the corporate level. How could it be that Facebook decided that clicks were the overall goal? In September 2020, Tim Kendall, who was director of monetisation for Facebook from 2006 through 2010, told a Congressional committee that the company sought to mine as much attention as humanly possible...We took a page from Big Tobaccos playbook, working to make our offering addictive at the outsetWe initially used engagement as sort of a proxy for user benefit. But we also started to realise that engagement could also mean [users] were sufficiently sucked in that they couldnt work in their own best long-term interest to get off the platform...We started to see real-life consequences, but they werent given much weight. Engagement always won, it always trumped.

It is easy to forget that corporations are entirely human-made institutions that only emerged during the industrial revolution. They provide the scale and coordination to build new technologies. Limited liability lets their officers take risks with new products and markets without incurring personal debt often funded, in the modern era, by plentiful sources of venture capital, alongside traditional bond and equity markets.

Most public listed companies came into being only very recently, and many will soon be overtaken by technological change; it is predicted that three-quarters of the companies on the Standard & Poors 500 index today will disappear in the next decade. About 20 years ago, only four of the 10 most valuable publicly listed companies in the world were technology companies: the industrial heavyweight General Electric was top, followed by Cisco Systems, Exxon Mobil, Pfizer and then Microsoft. Today, eight out of the top10 are digital technology companies, led by Apple, Microsoft and Alphabet, Googles parent company.

Perhaps it is time to think, then, about how we reinvent the corporation to suit better the ongoing digital revolution. How can we ensure that corporations are better aligned to the public good? And how do we more equitably share the spoils of innovation?

This is the super-intelligence value-alignment problem that actually keeps me awake at night.

And this is where the academy has an important role to play. We need scholars of all kinds to help imagine and design this future. Economists to design the new markets. Lawyers to draft new regulation. Philosophers to address the many ethical challenges. Social scientists to ensure humans are at the centre of social structures. Historians to recall the lessons from past industrial change. And many others from across the sciences and humanities to ensure that super-intelligence, both in machines and corporations, creates a better world.

Toby Walsh is an ARC Laureate Fellow and Scientia professor of artificial intelligence at UNSW Sydney and CSIRO Data61. His most recent book, 2062: The World that AI Made, explores what the world may look like when machines match human intelligence. His next book, out in May, is Machines Behaving Badly: The Morality of AI.

In 1995, Terry Bynum and I wrote a feature article for Times Higher Education that asked, What will happen to human relationships and the community when most human activities are carried on in cyberspace from ones home? Whose laws will apply in cyberspace when hundreds of countries are incorporated into the global network? Will the poor be disenfranchised cut off from job opportunities, education, entertainment, medical care, shopping, voting because they cannot afford a connection to the global information network? More than a quarter of a century on, I am still asking.

By now, there exists a deep-seated global dependency on digital technology. The Canadian governments January 2021 report, Responsible Innovation in Canada and Beyond: Understanding and Improving the Social Impacts of Technology, calls for solutions that are inclusive and just, undo inequalities, share positive outcomes, and permit user agency. I agree. To that end, we need an ever-greater emphasis on what we should now call digital ethics, defined as the integration of digital technology and human values in such a way that the former advances rather than detracts from the latter.

Two recent ethical hotspots reinforce this need. One is the estimated 360+ million over-65s who are currently on the wrong side of the digital divide; as the world has come to rely even more heavily on digital technology during the pandemic, these people have been put at greater risk. Another example is the 700+ UK sub-postmasters who were accused of theft on the basis of a faulty digital accounting system. Unverified digital forensics was the only evidence used to obtain the convictions many of which have now been overturned.

Only virtuous action can promote an ethical digital age. Rules may offer some guidance, but they are a double-edged sword. Within industry and government, a compliance culture has taken firm hold, strangling any opportunity for dialogue and analysis of the complex socio-ethical issues related to digital technology. Organisational silo mentalities must also be replaced by inclusivity and empathy.

Genuinely virtuous action can be promoted in three different ways. Top-down drivers are typically impositions by bodies of authority, which dictate where resources should be placed to achieve some overall goal. Middle-out drivers involve empowering all those within an organisation to propose new ideas, initiate change and support it. Bottom-up drivers emanate typically from grassroots collective action, often citizen-led.

Whistleblowing is a bottom-up driver and has been successfully used to expose and sometimes rectify unethical activity, primarily related to personal data. In 2013, Edward Snowden leaked highly classified information from the US National Security Agency, revealing its numerous global surveillance programmes, conducted with the cooperation of telecommunication companies and European governments. In 2018, Christopher Wylie revealed that Cambridge Analytica, a political consultancy that worked for the Trump campaign, had illegally obtained Facebook information about 87 million people and used it to build psychological profiles of voters and then spread narratives on social media to ignite a culture war, suppress black voter turnout and exacerbate racist views. In 2021, Frances Haugen disclosed thousands of Facebooks internal documents to the Securities and Exchange Commission and The Wall Street Journal. This has led to investigations into Facebooks updating of platform-driving algorithms, impacts on young people, exemptions for high-profile users and response to misinformation and disinformation.

Some ethical hotspots may be obvious while others may not, but all must be addressed. This can only be achieved through effective digital ethics education and awareness programmes that promote proactive individual social responsibility, both within work and beyond it, while taking into account both global common values and local cultural differences. Discussion, dialogue, storytelling, case study analysis, mentoring and counselling are all useful techniques.

The way forward, then, is a middle-out, interdisciplinary, lifelong-learning partnership of primary education, secondary education, further education, higher education and beyond. Universities have a key role to play. While some have introduced digital ethics into their technology degrees, others have not, and most existing courses are elective. This must change. Relevant digital ethics elements should be mandatory across undergraduate and postgraduate programmes within many disciplines, including technology and engineering, business and management, science, finance and law.

Nurturing practical wisdom and developing individuals confidence and skills to act responsibly and ethically will increase graduates awareness and commitment as they move into the world of work. However, to make a lasting difference, universities must engage politically, commercially, industrially, professionally and internationally to influence the strategies and attitudes of those beyond their own walls. They must develop and promote a new vision of the digital future that is theoretically grounded but also pragmatic if industry and government are to embrace it.

We must accept and adjust to the fact that we are all technologists to a lesser or greater degree. How we educate our future generations must reflect this change to ensure that the digital age is good for each individual, as well as for the world at large.

Simon Rogerson is professor emeritus at De Montfort University. He founded the Centre for Computing and Social Responsibility, the international ETHICOMP conference series and the Journal of Information, Communication and Ethics in Society. He was Europes first professor of computer ethics. His latest book is The Evolving Landscape of Ethical Digital Technology.

The biggest peril stemming from Big Tech is nothing less than the loss of human autonomy for the sake of increasing efficiency.

Even when decisions affecting a person are made by other human beings such as our family, government or employer we understand the power relationships between those decision-makers and ourselves, and we can choose to obey or to protest. However, if the computer says no in a systemthat we cannot escape, protest becomes meaningless, as there is no social element to it.

Furthermore, Big Tech robs us of our core competencies, which are important aspects of our intelligence and, ultimately, our culture. Take map-reading and orientation. While it may be both efficient and convenient to rely on Google Maps, habitual use means that we lose our ability to decide how to drive from A to B. More importantly, we lose the ability to navigate and understand our geographical environment, becoming ever more dependent on technology to do this for us.

Many people may not care about this particular trade-off between convenience and ability. Others may barely even notice it. But the tech-driven loss of decision-making and other abilities is pervasive. A more concerning example regarding autonomy is the profiling enabled by tracking technology when we browse the World Wide Web and engage on social media. The aggregation of data about our preferences and interests is all-encompassing; it does not merely include our shopping choices, but also our aesthetics, our religious or political beliefs, and sensitive data about health or sexual proclivities. Profiling enables the micro-targeting of what we consume and this includes news results, resulting in the widely lamented establishment of so-called filter bubbles or echo chambers.

The algorithms are serving us the content we apparently crave, or at least agree with, but they pigeonhole us into groupings that we cannot escape. Profiling deprives us of the autonomy to decide which content to access and, more broadly, the skill of media literacy. The consequences are serious, as the polarisation of opinion and the micro-targeting of advertising directly affect democracy, as was illustrated by the Facebook-Cambridge Analytica scandal.

Moreover, while the extraction of knowledge from big data has many economic, social and medical benefits, there are numerous instances where more knowledge is positively harmful. For example, imagine a free online game that allows the profiling of individuals regarding their likelihood of succumbing to early onset dementia. Learning of their risk profile may affect peoples mental health. Sharing the information with companies may lead to individuals being denied employment, credit or insurance. It would undermine the spreading of risk on which the whole health insurance industry is currently predicated.

Finally, it is not only what Big Tech does to us, but its sheer power that is disconcerting. At its core, Big Tech is based on the networks connecting us. The more people are connected to a network, the more useful it becomes, leading inevitably towards monopolies. This is true for e-commerce, online auctions, search engines and social media.

In addition, Big Tech firms size and power allows them to invest heavily in research and development, meaning they are always ahead of the innovation game. This makes it difficult for governments or publicly funded research institutions, such as universities, to keep up. In turn, it means that the research and innovation agenda is geared towards making Big Tech companies richer and even more powerful.

This loop has created a mindset that sees unbridled innovation through big data, data mining and artificial intelligence as imperative, regardless of ethics and the impact on humanity: the next, inevitable evolutionary step in human development. Universities should question this inevitability through their core missions in teaching and research. They must guard their independence from both politics and commercial interests.

In particular, universities should encourage truly interdisciplinary research, integrating all subjects as equal partners, including in terms of the funding and leadership of projects. It is wrong, for instance, that most funding from UK Research and Innovation in the area of artificial intelligence and autonomous systems has gone to fund computer science and engineering projects, offering little, if any, opportunity for ethicists, lawyers, humanities and social science researchers to critically reflect on what is good for human progress as a whole.

Universities should lead the dialogue about Big Tech and enable cross-fertilisation between disciplines and mindsets. After all, how you define the challenges created by Big Tech depends on your perception of them. Accordingly, teaching in computer science and engineering should also contain elements of ethics, law (such as data protection law), social sciences and humanities.

Of course, however public resources are divided up, they will always be dwarfed by those available to the Big Tech companies. For that reason, some people perceive the power relationship between university research/teaching and Big Tech innovation as akin to that between a person with a peashooter and Godzilla. But sometimes the question of who comes out on top is not only determined by power conferred by technology and money. It is also important to consider who can influence the mindset of human beings and this is precisely where universities have a big stake in the game.

Julia Hrnle is professor of internet law at the Centre for Commercial Law Studies, Queen Mary University of London.

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Can the academy rein in Big Tech? - Times Higher Education