Kozminski Techblog

Over the past two decades chess computers have absolutely exceeded human capabilities. However in late 2017 everything changed. The Deepmind team at Google created Alphazero. They gave it four hours and the basic rules of chess. The algorithm played millions of games against itself and then it was pitted against Stockfish – the strongest computer at the time. In a hundred games it won 28 drew 72 and lost none of them. However, not everybody was impressed. The issue was that Alphazero was using the entire google server system while Stockfish was playing on the equivalent of a laptop. That is why in late 2018 they played a rematch. in this post i’m going to give you one example and show you how powerful, creative and exciting Alphazero is to chess. The Google team released the sample size of 10 games from the initial match and this is one of them that i’m going to show you. 

This game is one of the few that featured an opening possible after move 1.e4. Alpha zero did not like 1.e4 because it couldn’t find consistent advantages against the sicilian defence and 1.e5 positions. Alphazero simply could not create the imbalances it was able to create in 1.d4 positions. This game however After 1.d4 Stockfish played the move 1. e6 which allowed the transposition to the french defence after the move 2.e4. The position after what is called a classical french after 6 moves looked like this. 

The most common and natural move in this position would be of course to take the pawn back with the knight. However Alphazero plays 7.Nb5. The point is to allow 7.Bb4 8.Bd2 Bc5 and create a very peculiar pawn structure. In many positions in the french defence black commits many pawns to light squares early. The consequence is that the bishop from c8 is very bad throughout the game being stuck behind the pawns. There are many moments when black needs to trade it off or break through the center.

Over the next couple of moves white suppresses black’s position and allows the move 15.Nxb2 after which it plays 16.Kxb2 which waives the rights to castle. If this move doesn’t look weird to you after 16.Bd7 it plays 17.Ke3! All of this looks completely ridiculous but black cannot do anything! Both of their bishops look awful and the only chance that black has of ever breaking out is playing f6 and if black ever takes on e5 white can recapture with Nxe5 activating their knight. To add insult to injury the white king is very safe on e3.

After maneuvering, improving placement of it’s pieces and trading a pair of rooks white plays a stunning sacrifice 30.Bxg6. After 30.Bxg5 31.Qxg5 fxg6 on the first glance it seems like white is just down a piece, but when we look deeper we can see that the bishop on b7 is practically worthless and alphazero continues its relentless attack with 32.f5, which is another pawn sacrifice.

The pawn cannot be taken for it would lead to a complete collapse of the black position. Instead the game continues with 32.Rg8 33.Qh6 Qf7 34.f6 Kd8 35.Kd2 Kd7 36.Rc1 Kd8. Here white switches targets and after attacking black on the kingside for the whole game it switches to the queenside in just a couple of moves and the infiltration of black’s position is inevitable. On move 52 stockfish resigned.

In 2018 Google Deepmind and the Stockfish team agreed to a rematch on equal terms to eliminate any doubts that Alphazero won due to better equipment. The second match had been played on equal terms. They played 1000 games against each other and this time Alphazero won 155 – 6 with 839 draws. This is a small example of how alpha zero completely changed chess computers forever. 210 games from the second match have been published on chessgames.com. There is also a very interesting book by grandmaster Matthew Sadler “Game Changer”, in which he looks at 20 of them which he found most interesting. If this topic is interesting to you I really recommend reading. Let me know in the comments which other Alphazero games do you like the most and if it still would have been the strongest chess engine on earth if Google Deepmind kept developing the project.

The game notation:

1.d4 e6 2.e4 d5 3.Nc3 Nf6 4.e5 Nfd7 5.f4 c5 6.Nf3 cxd4 7.Nb5 Bb4+ 8.Bd2 Bc5 9.b4 Be7 10.Nbxd4 Nc6 11.c3 a5 12.b5 Nxd4 13.cxd4 Nb6 14.a4 Nc4 15.Bd3 Nxd2 16.Kxd2 Bd7 17.Ke3 b6 18.g4 h5 19.Qg1 hxg4 20.Qxg4 Bf8 21.h4 Qe7 22.Rhc1 g6 23.Rc2 Kd8 24.Rac1 Qe8 25.Rc7 Rc8 26.Rxc8+ Bxc8 27.Rc6 Bb7 28.Rc2 Kd7 29.Ng5 Be7 30.Bxg6 Bxg5 31.Qxg5 fxg6 32.f5 Rg8 33.Qh6 Qf7 34.f6 Kd8 35.Kd2 Kd7 36.Rc1 Kd8 37.Qe3 Qf8 38.Qc3 Qb4 39.Qxb4 axb4 40.Rg1 b3 41.Kc3 Bc8 42.Kxb3 Bd7 43.Kb4 Be8 44.Ra1 Kc7 45.a5 Bd7 46.axb6+ Kxb6 47.Ra6+ Kb7 48.Kc5 Rd8 49.Ra2 Rc8+ 50.Kd6 Be8 51.Ke7 g5 52.hxg5 1-0

The game: https://www.chessgames.com/perl/chessgame?gid=1899422

In 1997, a momentous event occurred that forever changed the relationship between humans and machines: the supercomputer IBM Deep Blue defeated the reigning world chess champion, Garry Kasparov. Deep Blue’s victory was a defining moment, showcasing the potential of machines to tackle complex intellectual challenges.

The Origin of Deep Blue

The journey of Deep Blue began with a research project at Carnegie Mellon University in the late 1980s. Initially called Deep Thought, it was developed by a team led by Feng-hsiung Hsu. After joining IBM, Hsu continued his work, and Deep Thought evolved into Deep Blue. IBM’s goal was to create a machine capable of defeating the best human chess players in the world.

Deep Blue’s development was driven by a combination of hardware innovation and software sophistication. The team faced numerous challenges, including designing specialized processors for parallel computation and creating software capable of evaluating millions of chess positions per second with strategic accuracy. Balancing computational speed with decision-making quality was a critical hurdle that required constant iteration and refinement. Unlike general-purpose computers, Deep Blue was designed specifically for chess. It featured custom-built processors optimized for parallel computation, allowing it to evaluate millions of potential moves in mere seconds.

How Deep Blue Worked

Deep Blue’s strength lay in its ability to analyze a staggering number of positions per second. At its peak, it could evaluate 200 million positions per second, a feat unimaginable for any human player. The supercomputer achieved this through a brute-force search algorithm, combined with advanced evaluation functions that helped it assess the relative strength of different positions on the board.

Key techniques used by Deep Blue included:

1. Brute-force search: Deep Blue systematically examined a vast number of possible moves and countermoves up to a certain depth.
2. Evaluation functions: These functions allowed Deep Blue to score positions based on various chess heuristics, such as material advantage, king safety, and control of key squares.
3. Opening and endgame databases: Deep Blue had access to extensive pre-programmed databases that covered thousands of well-known opening sequences and endgame scenarios, giving it an edge in these critical phases of the game.

The 1997 Kasparov vs. Deep Blue Match

The showdown between Kasparov and Deep Blue took place in May 1997. It was a six-game match that drew worldwide attention. Kasparov, known for his aggressive and creative style, had previously defeated an earlier version of Deep Blue in 1996. However, this time, the upgraded machine proved too powerful.

The turning point came in Game 6, before which the match was tied 2,5-2,5. Kasparov has decided to go into the Steinitz variation in the Caro-Kann defence playing with the black pieces. In the pretty known line Kasparov played the move 7. h6 which allowes 8. Kxe6. This lines was known to be dubious already at the time, but Kasparov didn’t believe the engine would sacrifice a piece without clear compensation. This might seem like a stupid risk by the world champion, but back in the day computers valued material over any positional advantage. He expands on the topic in a book “Deep Thinking” which I recommend to anyone interested in the topic. The world was shocked, when the Russian resigned the game on move 19. losing the match. Deep Blue won with a final score of 3.5–2.5. Kasparov’s defeat marked the first time a reigning world champion lost a match to a computer under standard chess tournament conditions.

Kasparov later accused IBM of unfair play, suggesting that human intervention might have influenced some of Deep Blue’s moves. IBM denied these allegations, and while the controversy remains a topic of debate, it does not diminish the significance of the achievement.

The Aftermath and Legacy

Deep Blue’s victory had a profound impact on both the chess world and AI research. For chess, it marked the beginning of an era where computers became indispensable tools for analysis and training. Today, even amateur players can access powerful chess engines far more advanced than Deep Blue.

In AI, the match underscored the potential of machines to solve highly complex problems through brute-force computation and expert knowledge. However, it also highlighted the limitations of this approach. Subsequent AI developments, such as Google’s AlphaZero, shifted towards machine learning and neural networks, which focus on teaching machines to learn and adapt rather than relying solely on pre-programmed knowledge.

Chess computers in the modern era

Since Kasparov’s loss computers have improved so much that there is no debate if they are better then people for more than 20 years. The conversation has changed to computers ruining top level chess showing refutations to any new creative opening ideas and making grandmasters memorise 40 moves for each side instead of playing on their own. Let me know in the comments what your opinion is and what aspect of our lives computers will conquer next.

Written with help of Ninja AI.

Sources:

-Garry Kasparov “Ostatni Bastion Umysłu”

-https://www.youtube.com/watch?v=EsMk1Nbcs-s

https://en.wikipedia.org/wiki/Deep_Blue_versus_Garry_Kasparov#Game_6_2

Is your laptop taking forever to open apps? Does your computer feel like it’s stuck in slow motion? A sluggish device can be frustrating, but the good news is you don’t need to spend a dime to fix it. With a few simple tweaks and regular maintenance, you can get your gadgets running like new again. 

Here’s a guide to speeding up your devices without breaking the bank.

Clear Unnecessary Files and Apps

Clutter is one of the main reasons devices slow down. Over time, we accumulate apps we don’t use, files we don’t need, and a browser cache that’s bursting at the seams. Start by deleting apps you haven’t used in months and clearing out old downloads and photos.

Check the storage settings to see which apps are taking up the most space. Use tools like Disk Cleanup on Windows or Storage Management on Mac to clear unnecessary files.

Optimize Startup Programs

If your computer takes forever to start, too many apps might be launching when you turn it on. 

On Windows: Open the Task Manager, go to the “Startup” tab, and disable apps you don’t need immediately. 

On Mac: Head to System Preferences > Users & Groups > Login Items and uncheck unnecessary programs.

Disabling startup apps doesn’t delete them—it just prevents them from running automatically, freeing up resources.

Keep Your System Updated

Software updates aren’t just about adding new features—they often include performance improvements and bug fixes. Ignoring updates can leave your device slower and less efficient.

Make it a habit to install updates for your operating system and apps. On most devices, you can enable automatic updates so you don’t have to worry about it.

Restart Regularly

Sometimes, the simplest fix is the most effective. Restarting your device clears temporary files, resets background processes, and can resolve performance hiccups.

If you leave your device on all the time, try restarting it at least once a week. You might be surprised at how much faster it feels afterward.

Check for Malware or Viruses

Malware and viruses don’t just compromise security—they can also slow your device down significantly. Use free antivirus tools like Windows Defender or Malwarebytes to scan your computer regularly. Many phones also have built-in security features that detect suspicious activity.

If you find malware, remove it immediately and keep your device protected by avoiding suspicious downloads and websites. 

Conclusion

Keeping your devices running fast doesn’t have to cost a fortune. By clearing clutter, managing background processes, and maintaining good habits like restarting and updating, you can enjoy smoother performance without spending a cent.

Try out these tips today and see the difference for yourself! Have any additional tips or experiences? Share them in the comments below!

This post has been written with some help of Perplexity.ai

Every one of us has heard tech advice from people who have no clue about what they are saying. While they want to help their wisdom is simply outdated or they just don’t understand the subject. This post is here to debunk some common tech myths and set the record straight.

“More megapixels means better photos”

While megapixels play a role in image quality, they’re not the whole story. Megapixels determine the resolution of an image, which essentially means how large you can print it without it becoming pixelated (blurry). 

Think of it like this: Imagine two paintings. One is made with a million tiny dots, and the other is made with a hundred thousand larger dots. The one with a million dots can be printed much larger without losing detail. But if both paintings are the same size, and the one with fewer dots was painted by a master artist, it’s probably going to be the better painting! Similarly, factors like the size of the camera’s sensor, the quality of the lens, and the image processing software are much more important for creating good quality photos.

“Closing apps saves battery lives”

Modern smartphones are smart! They manage your phone’s memory (RAM) efficiently. When you close an app, it’s not completely shut down; it’s often put into a suspended state. Constantly closing and reopening apps actually forces your phone to work harder, using more battery in the process. It’s only necessary to force-close an app if it’s frozen, glitching, or causing other problems. So, relax your swiping finger – your battery will thank you.

“Charging the phone overnight will ruin your battery”

I have actually been a victim of this one for a while, but now I know that modern smartphones are equipped with smart charging circuitry that stops charging the battery once it reaches 100%. So, leaving your phone plugged in overnight won’t cause it to overcharge. However, exposing your phone to extreme temperatures (very hot or very cold) can negatively affect battery health over time, so try to avoid that.

“Incognito mode makes you invisible”

While incognito mode has its uses, it doesn’t make you invisible online. What incognito mode does do is prevent your browser from saving your browsing history, cookies, and site data. This means that if someone else uses your computer, they won’t see what you’ve been up to. However, your internet service provider (ISP), your employer (if you’re using their network), and the websites you visit can still track your online activity. So, while it’s great for keeping your browsing history private from others who use your device, it’s not a cloak of invisibility at all.

Hopefully I managed to make some of you realize that you believe in digital fairy tales. Don’t worry, we’ve all been there. What other tall tales of technology have you encountered? Leave a comment if you know some other myths that people believe all the time!