Bryant Francis, Senior EditorMay 14, 20253 Min ReadImage via Square EnixAt a GlanceSquare Enix is announcing notable changes to its business strategy following a weak earnings report.These plans notably do not mention the company's trumpeted investments in blockchain and NFTs.Square Enix is making major changes to its business operations to revamp its output after a year-on-year sales slump. In annual financial results posted today, the Final Fantasy and Dragon Quest developer reported an 8 percent decrease in net sales for the fiscal year ending March 31, 2025, diving from ¥356 billion (about $2.5 billion) billion to ¥324 billion (about $2.2 billion).Operating income decreased accordingly, dropping from ¥40 billion to ¥32 billion.These changes—and a steady stream of sagging quarterly financial results over the last year—prompted the company to announce a 3-year business plan promising a "reboot for long-term growth." Its strategy centers around reorganizing its development studios to operate under one management group, expanding revenue opportunities by "strengthening customer contact points," and other corporate initiatives.This plan began taking shape in 2024 with the shuffling of its internal studios under one "franchise management division." This means all Square Enix developers working on online games, "HD games," and "SD games" are in one business unit. Its AI and engine development divisions, as well as its audio, QA, and other "development-related specialized organizations" now sit outside these studios. The company says this shuffling led to "discontinued development" of some games (including a Kingdom Hearts mobile spin-off), and increased investment in titles that "require refinement."Related:This reorg has already led to decreased spending on advertising and promotion for its portfolio of free-to-play mobile games like Dragon Quest Tact. Its plan to "strengthen customer contact points" includes a plan to expand into the Chinese market and roll out new retail initiatives like "pop-up stores" and other merchandising promotion.The success of these plans will be judged by Square Enix's ability to hit three financial goals: a 15 percent consolidated operating margin in the fiscal year ending on March 31, 2027, an allocation of ¥100 billion over the next three years, and a target return on equity of at least 10 percent.The nitty gritty of Square Enix's studio structure is interesting—but it's what's not mentioned in this business revamp that makes the leadership strategy of the last few years all the more glaring.NFTs are nowhere to be seen in Square Enix's plan for the futureSearch any of Square Enix's financial documents released today and you'll notice two words are notably missing: "NFT" and "blockchain."Under normal circumstances, that wouldn't be unusual—NFTs have sputtered in the broader video game industry and blockchain game technology hasn't clicked with mainstream audiences. But Square Enix spent the last three years boasting that NFTs and blockchain tech would be a big business opportunity for the company. This was an especially big gamble coming out of the COVID-19 lockdown era, where player spending rocketed to unprecedented highs, creating a ripe opportunity for companies that could capitalize on the newfound cash.Related:It seems that was a misplaced bet. Few other companies followed in Square Enix's footsteps, and those that did like Sega have publicly reversed course with their enthusiasm. (Ubisoft is still sitting at that particular blackjack table, yelling "hit me" as other players slip away).The hot technology that followed the blockchain craze, generative AI, is still a part of Square Enix's future. Its R&D studios will invest in the technology to help create "new kinds of experiences." But so far, the most we know of these experiences is an (intriguing!) fictional language system the company showed off at the 2024 Game Developers Conference.Game Developer and Game Developers Conference are sibling organizations under Informa.Read more about:Square EnixTop StoriesFinancialsAbout the AuthorBryant FrancisSenior Editor, GameDeveloper.comBryant Francis is a writer, journalist, and narrative designer based in Boston, MA. He currently writes for Game Developer, a leading B2B publication for the video game industry. His credits include Proxy Studios' upcoming 4X strategy game Zephon and Amplitude Studio's 2017 game Endless Space 2.Follow Bryant Francis, Senior Editor, on Bluesky or LinkedIn.See more from Bryant FrancisDaily news, dev blogs, and stories from Game Developer straight to your inboxStay UpdatedYou May Also Like

Mission: Impossible – The Final Reckoning carries the weight of a meaningful farewell but lacks the courage to commit. The eighth film in the series begins with a sincere American president (Angela Bassett) entreating IMF agent Ethan Hunt (Tom Cruise) to take one last mission to save the world. This time, he must defeat a scheming AI called the Entity, which is hell-bent on wiping humans off the face of the earth through computer hacking and nuclear war. As fans have come to expect of this espionage franchise, Mission: Impossible – The Final Reckoning will deliver globe-trekking, tense twists, jaw-dropping action sequences that make grown-ups feel like kids again, the unrelenting star power of Tom Cruise, and a sentimental belief in the righteousness of one noble man playing by his own rules. But amid these treasures, The Final Reckoning is a film at war with itself. Rather than a fitting send-off to a film series rich in stunts and thrills, it feels like an exquisite corpse of warring artistic goals that is incredible to behold, but never really comes together. Mission: Impossible – The Final Reckoning delivers a plot that refuses to make sense. Ethan is still on the mission from Mission: Impossible — Dead Reckoning Part One.not to capture this AI wonder and hand it over to any government. He wants to destroy it, even though stern American counselors to the president insist that killing the Entity would mean destroying cyberspace. How? Despite much, much exposition dropping in brow-furrowing war room scenes, that's never remotely clear. You May Also Like Actually, the script by Christopher McQuarrie (who also directs) and Erik Jendresen makes a lot of declarations about the Entity's intentions, powers, and drawbacks without giving much sense of how any of it is possible. This has the effect of making the movie feel less like a sci-fi espionage thriller and more like flat-out fantasy adventure. The Entity becomes effectively an evil spirit that must be captured to end its reign of terror and its influence on the power-hungry or weak-minded. Final Reckoning even offers a doomsday cult devoted to the Entity to unfurl a thin thread. At 2 hours and 49 minutes, Mission: Impossible – The Final Reckoning takes off running with the plot line from Dead Reckoning, but runs it into the ground by losing sense of what made audiences so excited about the last installment. This fuzzy focus on AI as some vague but almost inescapable demon makes many of the decisions by Ethan and his crew hard to follow if not impossible. Worse yet, McQuarrie and Jendresen's overstuffed plot forces too many of Ethan's allies into a dull box, where they become tools of the plot over engaging characters. Tom Cruise is in top form, but Hayley Atwell is criminally misused in Mission: Impossible – The Final Reckoning. Cruise is a producer and star of this movie, and that's clear even without the title card announcing "A Tom Cruise Production." In Final Reckoning, he is an American action star in full, able to drop a powerful glower to underscore a dramatic moment better than any orchestra swell. He can perform a complicated and astonishing stunt with seeming ease. And truly, no one in cinema history can run as intensely as Cruise; his every speedy step seems to propel the iconic Mission: Impossible theme. At 62, his latest mission pulls him into the depths of the ocean and into a sky-high dogfight. Whether pummeling cronies with his bare hands or leaping from one in-flight plane to another, Cruise (and his stunt team) make Ethan a one-of-a-kind hero, capable of anything, yet able to express keenly his own morality through a powerful glance. This works even amid Final Reckoning's meandering plotting. Unfortunately, all the Ethan-centered heroics leave little room for his expansive crew to shine. Reprising their roles as IMF agents Luther Stickell and Benji Dunn, Ving Rhames and Simon Pegg have little screen time, but solid impact. They've mastered the art of making the most of these brotherly supporting roles. But more recent additions — like Hayley Atwell as pickpocket turned agent Grace and Pom Klementieff as assassin turned ally Paris — have achingly little to do. Mashable Top Stories Stay connected with the hottest stories of the day and the latest entertainment news. Sign up for Mashable's Top Stories newsletter By clicking Sign Me Up, you confirm you are 16+ and agree to our Terms of Use and Privacy Policy. Thanks for signing up! Klementieff gets a fun opening fight scene and a tender sequence in the third act. But frankly, that finale feels in conflict with her chilly character, as everywhere in between her dialogue is the same one-note joke of being apathetic, in French. Atwell, who was established as Cruise's next love interest in Dead Reckoning, becomes an unrecognizable nag in Final Reckoning. Her spirited banter and self-assurance has been swapped for tedious dialogue filled with worry or bizarrely out-of-character proclamations, like that Ethan should take over Entity and effectively rule the world! A collection of critically heralded actors, from Academy-Award winner Bassett to Emmy-winner Nick Offerman to Morales, Hannah Waddingham, Shea Whigham, and Janet McTeer, are similarly underused in scenes that involve a lot of furrowed brow-talking, but too little logic. Their intensity might have better sold the absurdity if McQuarrie didn't linger so long in these preposterous war room discussions. Tramell Tillman steals Mission: Impossible – The Final Reckoning. The underwhelming dialogue, which veers from exposition dumping to near-religious proclamations, proves a stumbling block for much of the Final Reckoning ensemble. Even Cruise struggles with comically dramatic lines like, "We can deceive the Lord of Lies!" But Severance star Tramell Tillman strides where others stumble. It's not that he gets better dialogue. Many of his lines are unremarkable, like, "Oh, OK" in response to some intense Ethan declaration. But Tillman builds a world with his curious delivery. Playing a smooth submarine captain, Tillman delivers every line as if he is welcoming Ethan into an exclusive resort. There's an almost seductive attitude to Tillman's captain, who moves suavely in the tight confines of the submarine and addresses his crew with a magnanimous warmth. As if he had not a concern in the world, he oozes charisma, which is reflected by his invitingly smirking crewmate Kodiak, played by Love Lies Bleeding's Katy O'Brian. Together they weave an underwater world of camaraderie and personality that had me wishing Ethan would abandon his mission and just hang out there for a spell. This series has offered scads of compelling characters. But I was sad to see the plot plunge away from this submarine crew so soon. I'd follow Tillman's captain anywhere, just because of the beguiling way he says "OK." Related Stories Mission: Impossible – The Final Reckoning is bloated but very fun. The final hour of Final Reckoning is jam-packed with suspense as action sequences between Ethan and his crew are cut across each other. Editor Eddie Hamilton masterfully creates tension while underlying how everything in the impossible plan to defeat the Entity must come together in "the blink of an eye." When the action scenes are hitting as they should, it's hard to imagine anything better to experience in a theater than a Mission: Impossible movie. Even Cruise's old-school sincerity is contagious, as Ethan throws his life on the line one more time for life, liberty, and an idealized American way. Very likely, you'll walk out of the cinema with a rush and joy, marveling over the stunts and heroics. But if you linger on the details of Final Reckoning, you begin to notice plot holes and dangling threads. You may get hung up on the tonal shifts that feel less like a flowing dance — as they did in Dead Reckoning — and more like a frenzied battle between ideas. In some ways, Mission: Impossible – The Final Reckoning feels like the final chapter. Ethan's colleagues praise him so intensely that several scenes feel like a premature eulogy for the still (ass-)kicking agent. The title and the snarling threats of the antagonist Gabriel — who promises a "final reckoning" — suggest this is Ethan's last mission, should he choose to accept it. Cruise's drive to top himself with not one but two absolutely bonkers action set pieces feels like an encore before he retires the character for good. Plus, a reprisal of a character long forgotten in the franchise is not only a welcome surprise, but also suggests this story is coming to a comforting close. (Cheers to Rolf Saxon and Lucy Tulugarjuk, who are splendid scene partners.) However, McQuarrie also refuses to shut doors that seem to be closing. Without giving away third-act spoilers, I can say Final Reckoning pulls its punches, seemingly to allow for a IMF story to continue. Yet what might make for a happy ending isn't satisfyingly resolved either. Rather than providing a sense of resolution, McQuarrie ends the film with a sequence meant to speak to enduring connection, but it feels jarringly isolating because of how disjointedly it is presented. Essentially, Mission: Impossible – The Final Reckoning feels like the filmmakers were both trying to make this the final movie in a successful franchise — and also leaving the door open for more. In waffling over that, they deliver a final chapter that is in turns thrilling and frustrating. Rather than going out with a bang, Mission: Impossible may go out with the fizzled whimper of a message self-destructing in a tape deck. Mission: Impossible – The Final Reckoning opens exclusively in theaters on May 23. Topics Film

As machine learning systems become integral to various applications, from recommendation engines to autonomous systems, there’s a growing need to address their environmental sustainability. These systems require extensive computational resources, often running on custom-designed hardware accelerators. Their energy demands are substantial during training and inference phases, contributing to operational carbon emissions. Also, the hardware that powers these models carries its environmental burden, called embodied carbon, from manufacturing, materials, and life-cycle operations. Addressing these dual carbon sources is essential for reducing the ecological impact of machine learning technologies, especially as global adoption continues to accelerate across industries and use cases. Despite increasing awareness, current strategies for mitigating the carbon impact of machine learning systems remain fragmented. Most methods focus on operational efficiency, reducing energy consumption during training and inference, or improving hardware utilization. However, few approaches consider both sides of the equation: the carbon emitted during hardware operation and that embedded in the hardware’s design and manufacturing process. This split perspective overlooks how decisions made at the model design stage influence hardware efficiency and vice versa. Multi-modal models, which integrate visual and textual data, exacerbate this issue due to their inherently complex and heterogeneous computing requirements. Several techniques currently employed to enhance AI model efficiency, including pruning and distillation, aim to maintain accuracy while decreasing inference time or energy use. Hardware-aware neural architecture search (NAS) methods further explore architectural variants to fine-tune performance, typically favoring latency or energy minimization. Despite their sophistication, these methods often fail to account for embodied carbon, the emissions tied to the physical hardware’s construction and lifetime. Frameworks such as ACT, IMEC.netzero, and LLMCarbon have recently started modeling embodied carbon independently, but they lack the integration necessary for holistic optimization. Similarly, adaptations of CLIP for edge use cases, including TinyCLIP and ViT-based models, prioritize deployment feasibility and speed, overlooking total carbon output. These approaches provide partial solutions that are effective within their scope but insufficient for meaningful environmental mitigation. Researchers from FAIR at Meta and Georgia Institute of Technology developed CATransformers, a framework that introduces carbon as a primary design consideration. This innovation allows researchers to co-optimize model architectures and hardware accelerators by jointly evaluating their performance against carbon metrics. The solution targets devices for edge inference, where both embodied and operational emissions must be controlled due to hardware constraints. Unlike traditional methods, CATransformers enables early design space exploration using a multi-objective Bayesian optimization engine that evaluates trade-offs among latency, energy consumption, accuracy, and total carbon footprint. This dual consideration enables model configurations that reduce emissions without sacrificing the quality or responsiveness of the models, offering a meaningful step toward sustainable AI systems. The core functionality of CATransformers lies in its three-module architecture:  A multi-objective optimizer An ML model evaluator A hardware estimator The model evaluator generates model variants by pruning a large base CLIP model, altering dimensions such as the number of layers, feedforward network size, attention heads, and embedding width. These pruned versions are then passed to the hardware estimator, which uses profiling tools to estimate each configuration’s latency, energy usage, and total carbon emissions. The optimizer then selects the best-performing setups by balancing all metrics. This structure allows rapid evaluation of the interdependencies between model design and hardware deployment, offering precise insight into how architectural choices affect total emissions and performance outcomes. The practical output of CATransformers is the CarbonCLIP family of models, which delivers substantial gains over existing small-scale CLIP baselines. CarbonCLIP-S achieves the same accuracy as TinyCLIP-39M but reduces total carbon emissions by 17% and maintains latency under 15 milliseconds. CarbonCLIP-XS, a more compact version, offers 8% better accuracy than TinyCLIP-8M while reducing emissions by 3% and ensuring latency remains below 10 milliseconds. Notably, when comparing configurations optimized solely for latency, the hardware requirements often doubled, leading to significantly higher embodied carbon. In contrast, configurations optimized for carbon and latency achieved a 19-20% reduction in total emissions with minimal latency trade-offs. These findings underscore the importance of integrated carbon-aware design. Several Key Takeaways from the Research on CATransformers include: CATransformers introduces carbon-aware co-optimization for machine learning systems by evaluating operational and embodied carbon emissions. The framework applies multi-objective Bayesian optimization, integrating accuracy, latency, energy, and carbon footprint into the search process. A family of CLIP-based models, CarbonCLIP-S and CarbonCLIP-XS, was developed using this method. CarbonCLIP-S achieves a 17% reduction in emissions compared to TinyCLIP-39M, with similar accuracy and <15 ms latency. CarbonCLIP-XS offers 8% improved accuracy over TinyCLIP-8M while reducing carbon by 3% and achieving <10 ms latency. Designs optimized only for latency led to an increase of up to 2.4× in embodied carbon, showing the risk of ignoring sustainability. Combined optimization strategies provided 19-20% carbon reductions with minimal latency increases, demonstrating a practical trade-off path. The framework includes pruning strategies, hardware estimation, and architectural simulation based on real-world hardware templates. This research lays the groundwork for sustainable ML system design by embedding environmental metrics into the optimization pipeline. In conclusion, this research sheds light on a practical path toward building environmentally responsible AI systems. By aligning model design with hardware capabilities from the outset and factoring in carbon impact, the researchers demonstrate that it’s possible to make smarter choices that don’t just chase speed or energy savings but genuinely reduce emissions. The results highlight that conventional methods can unintentionally lead to higher carbon costs when optimized for narrow goals like latency. With CATransformers, developers have a tool to rethink how performance and sustainability can go hand in hand, especially as AI continues to scale across industries. Check out the Paper and GitHub Page. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 90k+ ML SubReddit. The post Meta AI Introduces CATransformers: A Carbon-Aware Machine Learning Framework to Co-Optimize AI Models and Hardware for Sustainable Edge Deployment appeared first on MarkTechPost.

Deal  When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Buy Windows 11 Pro for 2 devices with a copy of Office 2021 Pro for only $55 Neowin Deals · May 14, 2025 13:00 EDT Today's highlighted deal comes via our Apps + Software section of the Neowin Deals store, where you can save 86% on Windows 11 Pro (for 2 devices) + Microsoft Office Pro 2021. Upgrade your computing experience with Windows 11 Pro. This cutting-edge operating system boasts a sleek new design and advanced tools to help you work faster and smarter. From creative projects to gaming and beyond, Windows 11 delivers the power and flexibility you need to achieve your goals. With a focus on productivity, the new features are easy to learn and use, enhancing your workflow and efficiency. Whether you're a student, professional, gamer, or creative, Windows 11 Home has everything you need to take your productivity to the next level. 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At 3DPI, our mission is to deliver high-quality journalism, technical insight, and industry intelligence to professionals across the additive manufacturing (AM) ecosystem. Whether you’re designing aerospace parts, building dental workflows, investing in next-generation materials, or shaping national AM strategy, you’re part of the reason we do this. But we want to go further. And that means hearing from you. 📋 Take the 3DPI Reader Survey We’re launching a short, focused reader survey to help us understand: What you value most in our content What’s missing How we can better serve your professional goals This is your chance to tell us: What kinds of stories or tools would help you do your job better Whether you want more technical explainers, market trend analysis, procurement tools, or vendor insights How 3DPI can improve your daily workflow—whether you’re in R&D, strategy, production, investment, or academia It takes less than 5 minutes. Your input directly informs editorial priorities and platform features. Why It Matters There’s a lot of noise in the AM space: press release churn, hype, and recycled headlines. At 3DPI, we aim to cut through that and bring you reporting, insight, and tools that actually move the needle. But to do that well, we need clarity on what you actually use, trust, and want more of. This survey helps us align what we publish with what you actually need; whether that’s: In-depth coverage of standards and regulations Real-world case studies that go beyond the brochure Technical deep dives Trend briefings or expert interviews Your voice shapes that roadmap. Thanks in advance for sharing your time and insight. We’re committed to keeping 3DPI the trusted source for professionals building the future of manufacturing. Michael Petch Michael Petch is the editor-in-chief at 3DPI and the author of several books on 3D printing. He is a regular keynote speaker at technology conferences where he has delivered presentations such as 3D printing with graphene and ceramics and the use of technology to enhance food security. Michael is most interested in the science behind emerging technology and the accompanying economic and social implications.

John Edwards, Technology Journalist & AuthorMay 14, 20255 Min ReadNicoElNino via Alamy Stock PhotoWhen it comes to AI, yesterday's comprehensive skillset may already be obsolete. Considering AI's ultra-rapid evolution, it's now important to help team members understand and utilize the latest skills without disrupting their already heavy workloads. A mix of hands-on experience and guided learning is the best way to build AI skills, advises Justice Erolin, CTO at software outsourcing company BairesDev. "Traditional education isn't keeping up with the rapid evolution of AI, so microlearning and peer learning programs can be more effective than a university course on AI," he says in an email interview. You no longer need AI experts; you need people who know their way around AI, says Mike Loukides, a vice president at technology and business training firm O'Reilly Media. "With appropriate training, the types of people you need can be developed from the staff you already have," he explains in an online interview. "Look for data engineers -- people who know how to build data pipelines, who know how to analyze data." Keeping Pace The AI landscape changes monthly, observes David Brauchler, technical director and head of AI and ML at cybersecurity consultancy NCC Group. To stay up to date on the latest advances, engineering teams should establish a culture of knowledge sharing and collaboration, he advises in an email interview. "AI improvement is a continual process, not one that occurs piecewise." Related:It's a continual process, Loukides says. "Even if you manage to hire the perfect team of outsiders, their skills will start to go out of date immediately," he observes. "Continuous learning was never more important than it is now." Dive into hands-on projects using pre-built examples with data and evaluation techniques that are readily accessible, recommends Vamsi Duvvuri, technology, media, and telecommunications leader at business advisory firm at EY Americas. "Collaborating with diverse teams across the organization during this stage is critical, especially folks from teams that typically do not work with each other," he explains in an online discussion. A mix of perspectives can reveal blind spots and spark ideas. Consider bringing in challenger hires or even exploring acquihires, Duvvuri suggests. "Bringing in new talent who aren’t entrenched in the status quo can disrupt traditional thinking and introduce fresh, unexpected approaches." Essential Skills New team members often challenge existing processes and help spark innovation, Duvvuri says. "In some cases, if you spot an innovative startup or a talented team, acquiring them -- or even doing an acquihire -- can rapidly inject cutting-edge expertise into your organization," he notes. "This isn't just about filling a gap, it's about shaking up the norm and accelerating learning." Related:Learning how to collaborate with AI is becoming a skill in itself, Erolin observes. "Beyond technical expertise, soft-skill development will help hone the ability to collaborate with AI." Critical thinking, problem-solving, and business knowledge are key to understanding when it makes sense to use AI. A handful of universal skills stand out, Erolin says. These include: Prompt engineering for working with generative AI models. AI model evaluation and fine-tuning to ensure that models align with business goals. AI governance and ethics, especially around bias, privacy, and explainability. MLOps skills to integrate AI into production reliably and at scale. Frameworks such as TensorFlow, PyTorch, or LangChain. Avoiding Mistakes A trap many IT leaders fall into is treating AI training as a one-off event, such as holding a single course or workshop. "If you skip the continuous cycle of learning, reflection, and even disruptive talent acquisition, you risk becoming stagnant and falling behind," Duvvuri warns. "In contrast, a culture that embraces ongoing education, diverse team dynamics, and bold moves, like challenger hires, fosters innovation and resilience." Related:Application architects and developers should consider the intricacies AI introduces to application threat models and skill-up in low-sensitivity environments, Brauchler suggests. "For example, AI presents new concerns related to data risk, including its inability to reliably distinguish between trusted and untrusted content," he says. "Consequently, application designers need to consider new risks that they might not be used to addressing in traditional software stacks." A Final Thought The companies that thrive in the AI era won't be the ones with the fanciest models, but the ones with the most adaptable teams, Erolin says. "The real differentiator is your people's ability to learn, unlearn, and relearn fast." At BairesDev, we've built our success around that belief, Erolin states. "We scale AI talent globally, but we also help our partners build internal cultures that keep pace with innovation. In this space, the only real risk is standing still."About the AuthorJohn EdwardsTechnology Journalist & AuthorJohn Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.See more from John EdwardsWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

John Edwards, Technology Journalist & AuthorMay 14, 20255 Min ReadNicoElNino via Alamy Stock PhotoWhen it comes to AI, yesterday's comprehensive skillset may already be obsolete. Considering AI's ultra-rapid evolution, it's now important to help team members understand and utilize the latest skills without disrupting their already heavy workloads. A mix of hands-on experience and guided learning is the best way to build AI skills, advises Justice Erolin, CTO at software outsourcing company BairesDev. "Traditional education isn't keeping up with the rapid evolution of AI, so microlearning and peer learning programs can be more effective than a university course on AI," he says in an email interview. You no longer need AI experts; you need people who know their way around AI, says Mike Loukides, a vice president at technology and business training firm O'Reilly Media. "With appropriate training, the types of people you need can be developed from the staff you already have," he explains in an online interview. "Look for data engineers -- people who know how to build data pipelines, who know how to analyze data." Keeping Pace The AI landscape changes monthly, observes David Brauchler, technical director and head of AI and ML at cybersecurity consultancy NCC Group. To stay up to date on the latest advances, engineering teams should establish a culture of knowledge sharing and collaboration, he advises in an email interview. "AI improvement is a continual process, not one that occurs piecewise." Related:It's a continual process, Loukides says. "Even if you manage to hire the perfect team of outsiders, their skills will start to go out of date immediately," he observes. "Continuous learning was never more important than it is now." Dive into hands-on projects using pre-built examples with data and evaluation techniques that are readily accessible, recommends Vamsi Duvvuri, technology, media, and telecommunications leader at business advisory firm at EY Americas. "Collaborating with diverse teams across the organization during this stage is critical, especially folks from teams that typically do not work with each other," he explains in an online discussion. A mix of perspectives can reveal blind spots and spark ideas. Consider bringing in challenger hires or even exploring acquihires, Duvvuri suggests. "Bringing in new talent who aren’t entrenched in the status quo can disrupt traditional thinking and introduce fresh, unexpected approaches." Essential Skills New team members often challenge existing processes and help spark innovation, Duvvuri says. "In some cases, if you spot an innovative startup or a talented team, acquiring them -- or even doing an acquihire -- can rapidly inject cutting-edge expertise into your organization," he notes. "This isn't just about filling a gap, it's about shaking up the norm and accelerating learning." Related:Learning how to collaborate with AI is becoming a skill in itself, Erolin observes. "Beyond technical expertise, soft-skill development will help hone the ability to collaborate with AI." Critical thinking, problem-solving, and business knowledge are key to understanding when it makes sense to use AI. A handful of universal skills stand out, Erolin says. These include: Prompt engineering for working with generative AI models. AI model evaluation and fine-tuning to ensure that models align with business goals. AI governance and ethics, especially around bias, privacy, and explainability. MLOps skills to integrate AI into production reliably and at scale. Frameworks such as TensorFlow, PyTorch, or LangChain. Avoiding Mistakes A trap many IT leaders fall into is treating AI training as a one-off event, such as holding a single course or workshop. "If you skip the continuous cycle of learning, reflection, and even disruptive talent acquisition, you risk becoming stagnant and falling behind," Duvvuri warns. "In contrast, a culture that embraces ongoing education, diverse team dynamics, and bold moves, like challenger hires, fosters innovation and resilience." Related:Application architects and developers should consider the intricacies AI introduces to application threat models and skill-up in low-sensitivity environments, Brauchler suggests. "For example, AI presents new concerns related to data risk, including its inability to reliably distinguish between trusted and untrusted content," he says. "Consequently, application designers need to consider new risks that they might not be used to addressing in traditional software stacks." A Final Thought The companies that thrive in the AI era won't be the ones with the fanciest models, but the ones with the most adaptable teams, Erolin says. "The real differentiator is your people's ability to learn, unlearn, and relearn fast." At BairesDev, we've built our success around that belief, Erolin states. "We scale AI talent globally, but we also help our partners build internal cultures that keep pace with innovation. In this space, the only real risk is standing still."About the AuthorJohn EdwardsTechnology Journalist & AuthorJohn Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.See more from John EdwardsWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

According to data.ai, puzzle games have now racked up over 3 billion mobile game downloads and are the 5th largest genre in the mobile gaming space. Not to mention, they grow at a rate of 15% every year.This is for good reason - puzzle games appeal to a wide range of gamers because they’re relatively simple. Puzzle gamers get to test their problem-solving skills with short challenges they can easily play over and over again (think: solitaire, sudoku, hex puzzles, and more).Puzzle games are so straightforward that they tend to have a single currency. If a player wants to purchase anything in the game, they can’t rely on harder currency like rubies or gems - they just need soft currency like coins, and a lot of it. And that’s why ad placements offering extra currency are so valuable. In fact, according to Google, 73% of mobile puzzle players believe that ads have no effect, or even a positive effect, on their gameplay experience.To make sure you’re setting up your puzzle game’s placement strategy for success, Anna Popereko, Game Design Consultant at ironSource, walks through the most useful rewarded video placements and what makes them so effective. Let’s get started.1. Reward multipliersThe most popular rewarded video placement in puzzle games is a reward multiplier. It works like this: once players receive a reward (e.g. after completing a level), the next screen offers the chance to multiply the reward they just got - simply by watching a rewarded video. The amount may depend on the game, but you can offer anything from 2x to 20x the reward.This placement works for a few reasons. First, it allows players to easily capitalize on and exponentially increase the currency they just won. Second, these placements also create a sense of urgency - they have only one chance to engage, so if the user chooses to skip this page, they miss out on a major opportunity to boost their currency.Playsimple, for example, used this approach in their game Word Trip. Once users receive a reward, they simultaneously get the option to multiply it - all they need to do is watch a rewarded video.2. Extra currencyExtra currency is another strategic placement, and it has a similar purpose to reward multipliers: increasing currency. But instead of popping up, these placements sit on the home page or the shop, waiting to be engaged with. Unlike reward multipliers, you don’t need to be actively playing the game to access extra currency placement - in fact, many players just stumble upon them.These placements don’t offer unlimited currency - they’re paced and capped so players can usually only engage with them once or twice a day. Extra currency placements also use timing to their advantage - they’re usually accompanied by a countdown clock, letting the player know how much time is left until they can watch a new video and access another reward.For example, Lihuhu worked this placement into their hit Match Triple 3D: while players explore currency bundles in the shop, they can watch a rewarded video to get 10 coins free of charge. Players in the shop are already motivated to get more currency, so this kind of placement works well.3. RevivalPuzzle games tend to have pretty long levels, often several minutes - so revival is another critical placement. Usually, if a player fails in the middle of the level, they’d have to give up all the time they’ve invested in the level and start over. But with revival placements, they just watch a rewarded video and continue from the moment they left off.Players are naturally motivated to engage with revival placements - especially when the other option is losing their hard work and time spent progressing in the level. Generally, the longer the level, the more players are open to engaging with this placement.Lihuhu successfully uses this placement in Match Triple 3D - when players run out of lives, there are only two ways to continue playing: spend their currency, or watching a rewarded video. This placement is very effective because it catches players in a critical spot, where the rewarded video is literally life-saving.4. BoosterPuzzle games attract players who are motivated by mental challenges, and being able to solve any problem that comes their way. That’s why booster placements are popular. When a player gets stuck at any point in the level, they can just watch a rewarded video, get some assistance in solving the current challenge, then confidently move on to their next challenge.The booster shouldn’t solve the entire puzzle for players - doing that would take away from the sense of achievement players get from solving challenges themselves. Rather, the booster should offer just the right push to keep the player engaged in the game, and hopefully able to solve the puzzle themselves.In Pixel by Number, Wido Games’ color by numbers game, when players get tired of tapping on a group of numbers, they can just click on the paint can icon, watch a rewarded video, and get that area colored in for them. It’s a win-win - with the booster, the player gets the extra help and motivation they need to complete the puzzle.5. Extra life and mystery rewardsTwo other common and worthwhile placements to use are extra life and chests. In games with a life-based system, once gamers run out of lives, they have to wait to get a refill - so this can be an ideal spot for a rewarded video placement. By engaging with the extra life placement, players gain another lifeline and the boost of energy they need, simply by watching a rewarded video. These placements are an ideal way to motivate players to keep going, especially if they're burning through multiple lives in one sitting - not to mention, they increase session length.Mystery rewards, on the other hand, offer a nice and exciting alternative to extra currency placements. Once the player opens the mystery placement (e.g. a chest), they’ll get to spin a wheel with a mystery prize. Like extra currency placements, these are time-limited with a countdown clock, and pacing depends on the game.In Word Trip by Playsimple, for example, onceplayers engage with the mystery reward, they can watch a rewarded video to spin for their prize - but they only get a certain amount per day.Puzzle games continue to be a dominant genre in the mobile gaming sphere - and using placements like these only improves the puzzle game experience and keeps the genre booming. By understanding your players’ goals and motivations, and using ad placements to enrich and extend their playtime, you can boost their experience and, as a result, your revenue.