Let’s delve into how AI is revolutionising online slot gaming in the UK and what this means for both players and developers.

AI integration in slot machine development

The development of slot machines has come a long way from their mechanical beginnings to the sophisticated digital versions we see today. AI is at the forefront of this evolution, significantly enhancing the creation and functionality of these games.

Enhanced game design

AI enables developers to create more dynamic and visually appealing games. By analysing vast amounts of player data, AI can generate themes, graphics, and narratives that are tailored to the preferences of different player demographics. This means that games can be more immersive and engaging, drawing players into captivating storylines and visually stunning environments that are continually evolving based on player interactions.

Adaptive gameplay

One of the most exciting applications of AI in slot machine development is the ability to adjust gameplay in real-time. AI algorithms monitor player behaviour and adapt the difficulty and features of the game accordingly. For example, if a player is struggling, the game might become slightly easier to keep them engaged, or if a player is doing exceptionally well, the game might present more challenges to maintain excitement. This adaptive gameplay ensures that players remain interested and challenged, providing a more satisfying gaming experience.

Personalised player experience

Personalisation is a key aspect of modern online gaming, and AI is instrumental in delivering a customised experience for each player.

Machine learning for player insights

AI uses machine learning to analyse player behaviour and preferences, allowing for highly personalised game suggestions and promotional offers. By understanding what types of games a player enjoys and how they like to play, AI can recommend new games or bonuses that are most likely to appeal to them. This level of personalisation enhances the player’s experience and increases their engagement with the platform.

Customised in-game experience

Beyond recommendations, AI also customises the gameplay itself. For instance, AI can adjust game mechanics, such as bonus frequencies and difficulty levels, based on individual player data. This means that each gaming session is unique and tailored to the player’s specific preferences, making the gaming experience more enjoyable and engaging.

Enhancing security and fairness

Security and fairness are critical components of online gaming, and AI plays a significant role in ensuring both.

Fraud detection and prevention

AI is highly effective in identifying and preventing fraudulent activities. By continuously monitoring player behavior and transaction patterns, AI can detect anomalies that may indicate fraudulent actions. When such activities are detected, AI can intervene in real-time to prevent losses and protect players and operators alike. This capability is crucial for maintaining the integrity and trustworthiness of online gaming platforms.

Ensuring fair play

Ensuring fair play is paramount in online gaming, and AI enhances this by maintaining the integrity of random number generators (RNG). AI algorithms ensure that the outcomes of slot games are truly random and free from manipulation. This transparency is essential for player trust, as it guarantees that every player has an equal chance of winning based on luck, without any external interference.

AI’s role in responsible gambling

AI is also a powerful tool in promoting responsible gambling practices, helping to mitigate the risks associated with gambling addiction.

Predictive analytics for problem gambling

AI can analyse playing patterns to identify behaviours that may indicate problem gambling. By using predictive analytics, AI can spot early signs of addiction, such as excessive spending or extended gaming sessions. This allows gaming platforms to intervene proactively, offering support and resources to players who may be at risk.

Intervention strategies

Once potential problem gambling behavior is identified, AI can implement intervention strategies. This might include sending notifications to players about their gaming habits, providing self-assessment tools, or limiting the amount of time and money a player can spend on the platform. These strategies are designed to help players maintain a healthy relationship with gambling and prevent the escalation of problematic behaviours.

Future prospects

Looking ahead, the potential of AI in the online slot gaming industry is immense. As AI technology continues to advance, we can expect even more sophisticated and personalised gaming experiences. AI-driven innovation will likely lead to entirely new types of games that we cannot yet imagine, offering unparalleled levels of engagement and excitement.

AI is revolutionising the online slot gaming industry in the UK, offering enhanced game design, personalised player experiences, improved security, and responsible gambling measures. As the technology continues to evolve, the future of online slot gaming looks incredibly promising, with AI playing a pivotal role in shaping this exciting landscape. For players and developers alike, the integration of AI presents endless possibilities for innovation and improvement in the world of online gaming.

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Using AI in gambling experiences opens up new dimensions of interactivity and engagement. AI algorithms can optimise live dealer games, making them more responsive and adaptable to player preferences. 

Enhanced personalisation and user experience

Artificial Intelligence has significantly altered the landscape of online gambling, offering a more personalised gaming experience. The technology analyses player behaviour, preferences, and playing patterns, tailoring game recommendations accordingly. 

The adaptive approach allows AI to refine its suggestions continuously, ensuring each player’s experience is unique and aligned with their interests.

The algorithms employed in this process are sophisticated and capable of understanding nuanced player preferences. As players engage with various games, AI observes and learns, making adjustments to recommendations based on evolving playing styles or interests. 

As a result, players get a more streamlined and enjoyable gaming experience, as they are presented with games that closely match their preferences.

Intelligence in marketing and profit management

AI has revolutionised marketing strategies within the gambling industry. It enables operators to analyse the most popular games and identify underperforming machines. AI helps craft effective marketing campaigns and maximise profits by understanding player preferences. For example, targeted welcome offers and free spins attract new players and retain existing ones.

Furthermore, AI-driven casino analytics assist operators in identifying low-profit games, enabling them to make informed decisions about technological adjustments to improve revenues.

Rewards-based system intelligence

Online gambling algorithms also play a crucial role in managing loyalty programs. AI enables operators to tailor VIP rewards based on player activity, enhancing customer retention. By analysing player behaviour, casinos can adjust reward levels and make VIP tiers more attainable or desirable, increasing player satisfaction and loyalty.

Security and fraud detection

The use of AI in the online gambling sector marks a pivotal shift in how security is managed and maintained. AI, especially through machine learning algorithms, has emerged as a formidable tool in enhancing the security of these platforms, addressing a spectrum of challenges that were previously difficult to manage.

Machine learning algorithms, a core component of AI, excel in detecting anomalies in betting patterns, which is crucial in identifying and preventing fraudulent activities. These algorithms analyse vast amounts of data in real-time, learning from player behaviours to identify patterns that deviate from the norm.

Game development and innovation

In game development, AI is enhancing existing games and also aiding in creating new ones. Developers use AI to generate dynamic content, adjust game difficulty in real-time based on player performance, and test new game mechanics. It results in more engaging and versatile games, offering a level of personalisation and dynamism previously unattainable​​.

The technological revolution is not just confined to digital gaming platforms but extends to options for live play, enhancing real-time gambling experiences in ways previously unimagined.

Conclusion

The impact of AI on the gambling industry is both extensive and multifaceted. From enhancing user experiences through personalisation to bolstering security, AI’s role in this sector is undeniably transformative. However, it is crucial to navigate the ethical and practical challenges AI poses to ensure its integration benefits all stakeholders in the gambling industry. 

(Photo by Erik Mclean on Unsplash)

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At the core of DEPT®’s approach is the strategic utilisation of large language models. Briski articulated the delicate balance between the ‘pioneering’ and ’boutique’ ethos encapsulated in their tagline, “pioneering work on a global scale with a boutique culture.”

While ‘pioneering’ and ’boutique’ evokes innovation and personalised attention, ‘global scale’ signifies the broad outreach. DEPT® harnesses large language models to disseminate highly targeted, personalised messages to expansive audiences. These models, Briski pointed out, enable DEPT® to comprehend individuals at a massive scale and foster meaningful and individualised interactions.

“The way that we have been using a lot of these large language models is really to deliver really small and targeted messages to a large audience,” says Briski.

However, the integration of AI into various domains – such as retail, sports, education, and healthcare – poses both opportunities and challenges. DEPT® navigates this complexity by leveraging generative AI and large language models trained on diverse datasets, including vast repositories like Wikipedia and the Library of Congress.

Briski emphasised the importance of marrying pre-trained data with DEPT®’s domain expertise to ensure precise contextual responses. This approach guarantees that clients receive accurate and relevant information tailored to their specific sectors.

“The pre-training of these models allows them to really expound upon a bunch of different domains,” explains Briski. “We can be pretty sure that the answer is correct and that we want to either send it back to the client or the consumer or some other system that is sitting in front of the consumer.”

One of DEPT®’s standout achievements lies in its foray into the web3 space and the metaverse. Briski shared the company’s collaboration with Roblox, a platform synonymous with interactive user experiences. DEPT®’s collaboration with Roblox revolves around empowering users to create and enjoy user-generated content at an unprecedented scale. 

DEPT®’s internal project, Prepare to Pioneer, epitomises its commitment to innovation by nurturing embryonic ideas within its ‘Greenhouse’. DEPT® hones concepts to withstand the rigours of the external world, ensuring only the most robust ideas reach their clients.

“We have this internal project called The Greenhouse where we take these seeds of ideas and try to grow them into something that’s tough enough to handle the external world,” says Briski. “The ones that do survive are much more ready to use with our clients.”

While the allure of AI-driven solutions is undeniable, Briski underscored the need for caution. He warns that AI is not inherently transparent and trustworthy and emphasises the imperative of constructing robust foundations for quality assurance.

DEPT® employs automated testing to ensure responses align with expectations. Briski also stressed the importance of setting stringent parameters to guide AI conversations, ensuring alignment with the company’s ethos and desired consumer interactions.

“It’s important to really keep focused on the exact conversation you want to have with your consumer or your customer and put really strict guardrails around how you would like the model to answer those questions,” explains Briski.

In December, DEPT® is sponsoring AI & Big Data Expo Global and will be in attendance to share its unique insights. Briski is a speaker at the event and will be providing a deep dive into business intelligence (BI), illuminating strategies to enhance responsiveness through large language models.

“I’ll be diving into how we can transform BI to be much more responsive to the business, especially with the help of large language models,” says Briski.

As DEPT® continues to redefine digital paradigms, we look forward to observing how the company’s innovations deliver a new era in AI-powered experiences.

DEPT® is a key sponsor of this year’s AI & Big Data Expo Global on 30 Nov – 1 Dec 2023. Swing by DEPT®’s booth to hear more about AI and LLMs from the company’s experts and watch Briski’s day one presentation.

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Gaming QA testers regularly come under fire as bug-riddled games reach the hands of disappointed gamers with seemingly increasing prevalence.

The backlash QA testers receive from frustrated gamers is often misplaced. Managers are often aware that games are full of bugs but decide to release unfinished games anyway in the hope of starting to recoup development costs.

However, proper QA testing is a time-consuming and resource-intensive process. On the PAX stage, Booty explained how a game needs to be re-tested from start to finish whenever a feature is added.

“Some of the processes that we have [currently] haven’t really kept up with how quickly we can make content. One of those is testing,” Booty said.

“There’s a lot going on with AI and ML right now, and people using AI to generate all these images. What I always say when I bump into the AI folks, is: ‘Help me figure out how to use an AI bot to go test a game.’”

If bugs can be caught earlier in the development process, they have a greater chance of being fixed prior to management feeling the financial pressure to send the game to market regardless.

The full ‘Storytime with Matt Booty’ talk can be viewed here. At around 01:02:00, you can hear Booty explain his vision for AI in game testing.

“I would love to be able to start up ten thousand instances of a game in the cloud – so there are ten thousand copies of the game running – deploy an AI bot to spend all night testing that game, and in the morning we get a report. That would be transformational,” explains Booty.

Booty’s core idea of improving QA testing with AI is solid. However, the way it was presented – of replacing human testers – may not go down too well. Mistreatment of QA testers in the gaming industry has led to a growing call for their members to unionise.

(Photo by Jose Gil on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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The startup has attracted interest for its ability to design and deploy interactive characters with more realistic interactions across the metaverse and other virtual words like video games.

In current video games, NPCs have pre-scripted responses. AI-powered virtual characters like those Inworld are developing can offer dynamic responses to general questions about the local area or wider world.

While graphics have generally become more immersive over the years, interactions have largely remained the same. The ability for NPCs to hold conversations more naturally will be a giant leap forward for gaming and help to deliver on the metaverse’s bold promises.

Inworld’s potentially key role in the future of the metaverse and gaming market – which is already worth hundreds of billions of dollars – has opened investors’ wallets.

Since it left stealth last year, Inworld has raised $70 million. In March, it raised $10 million in a strategic funding round.

Inworld was also notably included in the latest Disney Accelerator cohort which also included blockchain network Polygon, NFT platform Flickplay, AR hardware and interface developer Red 6, metaverse e-commerce platform Obsess, and immersive experience provider Lockerverse.

“I’ve long believed that interactions, memories, and connections formed in immersive worlds can become as real as those formed in real life. It’s why I’m excited about being named a Disney Accelerator company,” wrote Inworld AI CEO Ilya Gelfenbeyn in a LinkedIn post about the accelerator.

“Our platform for creating memorable, AI-powered characters will unlock new opportunities for creators in entertainment, gaming, the metaverse, and other digital realms who are ready to create memories like mine.”

Inworld Studio launched in beta a few months ago. The no-code system works with most common game and metaverse engines, including Unreal and unity.

“It’s crazy to think that Inworld was founded just 13 months ago. Since then, we raised two seed rounds, were selected for the Disney Accelerator, launched the beta version of our product, and now, closed our Series A!” wrote Gelfenbeyn in a blog post.

“It’s been impressive to see our community bring characters to life with AI. I know the best is yet to come.”

(Image Credit: Inworld)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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Some masochists enjoy the pain of being repeatedly beaten in games like Dark Souls – it’s understandable, overcoming those challenges is a great feeling – but most of us have a breaking point where the power button gets hit and the game just ends up collecting dust on a shelf.

A patent spotted by SegmentNext details an AI which learns from the human player and can continue when they’re not playing:

“The method includes monitoring a plurality of game plays of the user playing a plurality of gaming applications,” the patent explains.

“The method includes generating a user gameplay profile of the user by adjusting the default gameplay style based on the plurality of game plays, wherein the user gameplay profile includes a user gameplay style customized to the user. The method includes controlling an instance of a first gaming application based on the user gameplay style of the user gameplay profile.”

It’s easy to see how such an AI could be used in grind-heavy games to reach a required level, or another player’s AI that has completed a particular challenge could even be used to overcome it rather than lead to a situation where they give up completely.

For those who feel that level of intervention is cheating, the AI could instead offer tips to the human player as they’re gaming. The AI basically wants to be a helpful player two rather than the person on your couch that mocks you and then does worse when they take the controller.

While great strides have been made in making games accessible for people with disabilities, there are some parts of games which remain problematic even with the best intentions of developers. These individuals will also benefit from an AI which can take the reins for a bit and allow them to continue enjoying the rest of the game and the increasingly immersive storytelling many provide.

(Photo by Fabian Albert on Unsplash)

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

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While gaming remains Nvidia’s primary source of growth, the company’s artificial intelligence business is growing rapidly. In the second fiscal-quarter, Nvidia reported increased demand for both its graphics and AI chips.

For some idea of Nvidia’s growth in AI, Huang says there are now over 4,000 AI startups working with his company. That number is up from 2,000 in April 2017 and goes to show the growing interest around the technology.

Nvidia continues to innovate in AI and is quickly establishing itself as a major player; particularly in driverless cars.

The company’s self-driving platform DRIVE is powered by Nvidia Xavier chips and consists of three parts:

1. DRIVE AV — This part of the DRIVE platform was also available in the previous generation and uses neural networks to perform the calculations required for self-driving cars.
2. DRIVE IX — The first of the two new inclusions is a software development kit which enables AI assistants that can harness data from sensors inside and outside the vehicle.
3. DRIVE AR — While there have been many advancements around self-driving technologies and AI assistants for cars, augmented reality is still relatively unexplored. With DRIVE AR, Nvidia intends to enable new graphical experiences which can deliver things such as information about points of interest along the route.

Nvidia says its Xavier chips have been in development for over four years and represents the work of over 2,000 engineers. Xavier features more than nine billion transistors and Nvidia claims it’s the most complex system-on-a-chip (SoC) ever created.

In a conference call last August, Huang teased Tesla’s reported difficulties in building its own AI chips: “It’s super hard to build Xavier and all the software stack on top of it. If it doesn’t turn out for whatever reason for them [Tesla] you can give me a call and I’d be more than happy to help.”

Autonomous car manufacturers need to train petabytes of data per day, reiterate their models, and deploy them again in order to get those vehicles to market. Nvidia has a server, equivalent to 800 traditional servers, called the DGX-2 which delivers two petaflops of performance.

During AI Expo London earlier this year, Nvidia senior director of enterprise David Hogan said: “The compute demands of AI are huge and beyond what anybody has seen within a standard enterprise environment before. You cannot train a neural network on a standard CPU cluster.”

While Nvidia is well-positioned in AI, and is already reaping the benefits, it foresees gaming continuing to be its primary source of revenue for some time.

Nvidia reported earnings per share of $1.24 on revenues of $2.58 billion in the second fiscal quarter ended July 31. Gaming was about 50.3% of total revenues, and GPUs were 81% of revenues.

Huang believes Nvidia’s GPU sales will increase thanks to the growing popularity of ‘ray tracing’ in games, deliver stunning realism by enabling things such as full-detail reflections which mirror the action happening in and around the player’s field of view:

Few games offered support for ray tracing last year and supporting RTX chips were expensive, so sales were subdued. That’s changed this year, with more supporting games and cheaper RTX chips available; a combination which produced $1.3 billion in gaming revenue for Nvidia this quarter.

Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo.

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Most sports have been established for some time and ‘new’ ones are generally just similar but with some tweaked rules.

Design agency AKQA set out to create a truly new sport with help from an AI – meet, Speedgate.

Speedgate features six-player teams (take that, five-a-side lovers…) which compete on a field with three open-ended gates.

To score, players must first kick a ball through a centre gate which they’re unable to step through. After which, they can score a point by putting a ball through either of the end gates. If a teammate catches the ball and ricochets it back through, an extra point is scored.

To keep things fast-paced, the ball cannot be still for more than three seconds.

Rather than a rewrite of the rules of an existing sport, Speedgate sounds more like a collision of several. There are elements of soccer (I’m a Brit, so don’t tell my mates I called it that but NFL is king…), basketball/netball in terms of not standing still for long, and I’d imagine even some dodgeball.

That’s probably of little surprise when you hear how the AI came to create its new sport.

Data from 400 existing sports was fed into a neural network before it spat out some basic outlines for a sport and its accompanying rules. Some of these rules, while pretty awesome, were unrealistic. Many of us would like to see things like exploding Frisbees – but health and safety people are sticklers.

Playtests were then used to whittle down the sports to one champion. AKQA is now in discussions with the Oregon Sports Authority to get a Speedgate league going this summer.

AI even created the logo and motto, though we think the latter could do with some work (“face the ball to be the ball to be above the ball”).

It’s a cool example of what AI is able to create, but let’s make a pact to keep clips of The Hunger Games locked away. After all, AIs are already beating us at our own creations

Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo..

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AI News first reported of OpenAI’s gaming prowess in August 2017 when it took on three of the best Dota 2 players in the world and won.

The AI learned how to play the game from scratch and was able to beat regular players within the space of an hour. Professional gamers put up more of a fight, with the AI requiring two weeks of training to beat some of humankind’s best.

At the time, OpenAI said they believe their AI is beatable as it’s not better in terms of actions-per-minute but made smarter decisions. Some players were able to confuse the bot and distract it from the main objectives; showing it’s not flawless.

In the latest man versus machine spectacle, the humans lost the first two rounds but won in the third.

The opponents faced off Valve’s The International 2018 esports competition in San Francisco. Rules were kept the same as the last bout which meant things like ‘couriers’ (NPCs used for delivering items to heroes) were not invulnerable.

On average, a match features 80,000 individual frames and each character is able to perform around 170,000 possible actions. The AI’s ability to comprehend and take relevant actions is nothing short of incredible.

According to OpenAI Cofounder and Chairman Greg Brockman, the firm’s AI now has the equivalent of 45,000 years of Dota 2 gameplay experience. Taking that into account makes it even more impressive the human players managed to beat the AI even once.

OpenAI is currently able to play just 18 of the 115 heroes featured in Dota 2, so – if you’re thinking of issuing a challenge – perhaps get to grips with those it’s not had the equivalent of around 562 human lifetimes training in.

An archived broadcast of the match can be viewed on Twitch here.

Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo.

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Back in 2015, DeepMind attempted to play various Atari games. The AI was competent in most of the games and became as good at Video Pinball as a human player.

DeepMind notoriously struggled with Montezuma’s Revenge, a notoriously complex game from the 1980s. The AI was unable to learn a path and retrieve even the first ‘key’ in the game.

Video games, in general, have become a battleground for AIs to show-off. DeepMind’s failure with Montezuma’s Revenge set the game as one benchmark for the industry to prove advancements.

A new algorithm designed by Fabio Zambetta and his team from RMIT University learns from past mistakes and identified next steps 10 times faster. The AI was successful in autonomously playing Montezuma’s Revenge.

In a statement, Zambetta explained:

“Truly intelligent AI needs to be able to learn to complete tasks autonomously in ambiguous environments.

We’ve shown that the right kind of algorithms can improve results using a smarter approach rather than purely brute forcing a problem end-to-end on very powerful computers.”

Zambetta presented his findings at the 33rd AAAI Conference on Artificial Intelligence in Hawaii today and explained how it works.

DeepMind and similar AIs struggle with adventure games like Montezuma’s Revenge due to a lack of reward until it obtains the first item, a key in this case. This makes it difficult for the AI to work out if what it’s doing is correct/optimal.

Games like Video Pinball provide the AI with quick rewards due to things such as point increases. This approach enables the AI to learn what path is going to achieve the highest score.

By implementing reinforcement learning, the researchers added ‘pellet rewards’ for the system to promote it exploring more paths.

“With time, this technology will be valuable to achieve goals in the real world, whether in self-driving cars or as useful robotic assistants with natural language recognition,” said Zambetta.

Other AI researchers are continuing to advance their approaches. DeepMind itself published two papers last summer describing how an AI could learn to conquer Montezuma’s Revenge from YouTube videos.

We look forward to watching upcoming AI bouts for the Montezuma’s Revenge title.

Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo.

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