The Indie Survival Guide is your ongoing archive of real talk and hard-won insights from the devs and industry experts making games happen—often against the odds. Whatever tools you’re using, this growing library of Q&As, livestreams, and VODs is here to help. There’s no magic formula, but we believe shared experience—across design, business, and survival—can give you the best shot.We recently sat down with Emily Pitcher—a Forbes 30 Under 30 and Game Awards Future Class honoree, better known online as sonderingemily to her 350,000 followers across YouTube, Instagram, and beyond. Emily is the creator of lily’s world XD, a psychological horror game built on cringy teen nostalgia, fourth-wall breaks, and real photos from her own adolescence. Her work spans game dev and content creation, and she’s the first to admit: it hasn’t all been easy. But the journey has a lot to learn from.Here’s what she had to say.1. Failing as part of the processBefore the success of lily’s world XD, there was Gold Lining—a project that taught Emily the brutal, necessary lessons of creative failure. She poured her heart into the game, even secured early funding from Xbox, but ultimately it didn’t find traction. There was no publisher. No finish line. Just hard decisions and emotional fallout. But it was also the beginning of clarity.“Gold Lining was a project I started basically right out of college,” she says. “Instead of researching what might be popular with Steam players, I just thought, what would be a concept that seems cool to make?... We actually got some funding from that game from Xbox… but unfortunately, we were never able to secure a publisher with that game, and the game was ultimately cancelled.”Emily doesn’t romanticize this period. The dream faltered. Her confidence did too. And the weight of rejection nearly broke her.“The game could not be finished without money,” she said. “The scope was just way too big… and we kind of came at a crossroads of what should we do… I stopped having fun making the game… I was really sad every day with the rejections… I stopped believing in the game itself.”Still, she made the hardest—and wisest—move: she quit. And by walking away, she opened the door to her next act.“It was honestly really hard, very emotional—there was crying involved, of course—but now looking back, I am so happy I had the courage to step away,” she says. “I do not regret that failure at all because only because I went through that and learned the hard way, that lily’s world XD has been able to get grounding.”2. Turning Mistakes Into MomentumEmily didn’t just recover—she reflected. Every painful lesson from Gold Lining became a data point. And rather than rebuild in the same direction, she rebuilt smarter.“actually had this video that changed my life,” she says. “He did this interview with a popular game dev channel and he had this whole section about genre. And he said platformers—the worst genre—that hurt a little bit.”The first shift? She stopped building games no one could explain. She learned that clarity matters. Especially when talking to publishers or creating content, having a razor-sharp pitch can be the difference between intrigue and indifference.“You can summarize the hook of your game in one sentence,” she says. “That one sentence can guide you when you're talking to publishers, guide you when you're making content about your game.”She also interrogated her design logic more rigorously. Was every mechanic supporting the theme, or just convention?“I was just following the conventions of the genre and not asking myself, are we just doing this because it’s a platformer?” she said. “Or are we doing this because it helps the central theme of the game?”Most importantly, she dismantled the echo chamber. No more developing in isolation. Instead, she decided to involve the audience early—and often.“Another big thing I would do is to try to validate your game earlier,” she says. “With Gold Lining, it was just an echo chamber of me and my friends… with lily’s world XD, I made the videos from the very beginning.”3. Playing to your strengthsOne of Emily’s biggest unlocks wasn’t about tech or trends. It was about accepting who she is—and who she isn’t. She’s not a trained programmer. She’s not a pro artist. But she is a storyteller. A designer. A builder of weird, personal worlds. And when she embraced that, things clicked.“You gotta be a little objective about what you're good and bad at,” she said. “I suck at programming. I am a good writer. And I would say I'm passable with art… if someone told me, ‘I suck at programming, I'm mediocre at art, and I can only write,’ I’d be like, ‘You should not make an indie game’… but even though all of those things are true, when I get the feedback form for my game, for playtesters, people actually say that art direction is one of their favorite things.”Instead of pretending to be someone she wasn’t, Emily designed around her limits. And in doing so, she carved out a creative space that felt truly hers.“I worked around my weaknesses,” she says. “I suck at programming, so I decided to make a game that I thought would be easier to program… I used to work at Meta, so I’m familiar with tools like Figma… I use pictures of myself because I’m not that good at art… and it is a narrative detective game, so storytelling and writing is at the forefront.”Her lesson: don’t wait to be good at everything. Use what you’ve got.“Limitation is what makes you seem competent if you have a lower skill set,” she says. “If you're doing pixel art and you use a limited color palette, immediately your art is gonna seem more cohesive just because of that—even though you still suck.”4. Publicly validating conceptsIn contrast to the quiet, closed-door development of Gold Lining, Emily took a radically open approach with lily’s world XD. She didn’t just develop in public—she launched her audience journey before her Unity project even existed.“With Gold Lining, it was a secret right up until the end… I worked for about two years in private on the game,” she said. “And with lily’s world XD, I thought: in the first week of development, let’s make a video. And that video got 2 million views… I realized that I could use social media as a way to evaluate whether my ideas had strengths.”The result? Instant feedback. Viral traction. And a powerful way to gauge demand before sinking years into development.“I had started making videos here and there… eventually I grew a small audience,” she says. “I posted one of my TikTok videos to Instagram just to share with my family and friends. That video got over 2 million views, and now I do it as a career.”This approach wasn’t accidental—it was strategic. She tested multiple angles and found the hook that stuck.“When I had an idea, I came up with a few sentences of hooks,” she explained. “...and what led to the huge boom and rise of my game… was this thing I did to save time, that ended up being a cool developer story.”Emily’s story proves you don’t need a huge following to start. You just need to start.“I know that not everyone has a massive social media following,” she said. “But I don’t think you need a massive social media following to validate this idea through social media… Unpacking went viral at its first tweet… they weren’t famous people before that.”5. Using Social MediaSocial media was never Emily’s endgame—it was a bridge. A means of discovery, validation, and momentum. But not a silver bullet. She’s blunt about its limits.“Short-form video is not the best way to convert to wishlists,” she says. “That conversion has to happen when they see the name, they save the video, then they go on their computer and search it up… that is just too many steps.”What works? A multi-platform approach, repeated visibility, and content with a clear hook.“Post your video on all social media platforms,” she said. “This video that is literally 6 million views got 700 views on my TikTok. If I just posted on TikTok, I would think this is a bad video—but no, this video gave me like 10,000 wishlists.”Most impressive of all, she built momentum before she even touched code.“I started making videos when all I had were two screenshots,” she said. “When I made my video, I didn’t even open Unity. I didn’t know how to code yet. I just assumed I was going to learn on the way.”But Emily is crystal clear: none of this matters if the game itself doesn’t land.“Social media will not take you to the finish line,” she says. “Ultimately, you need to make a good game… you should leverage social media to give you opportunities in your game, rather than relying on it as the sole marketing method.”There’s no single path through indie game development, but Emily Pitcher’s story makes one thing clear: failure is not the opposite of progress; it is progress. From burnout to bounceback, her ability to interrogate her process, stay honest about her strengths, and meet the audience where they are has turned lily’s world XD into one of the most anticipated indie horror games on Steam.As Emily put it best:“We are stronger together and we should not look at each other as competition.” #lessons #learn #failed #game

An AI integration modifies a business process and how employees work, but it also requires an integration with IT infrastructure and systems. This is where some of IT’s most technically savvy staff will be working, and they will want to discuss technology integration approaches and ideas. Most CIOs aren’t software engineers, but they are responsible for having a working knowledge of all things IT so they can hold meaningful dialogues with their most technical employees to assist in defining technology direction. What do CIOs need to know about the technical side of AI integration? 1. AI technical integration is about embedding AI in systems and workflows The assumption here is that by the time your staff is getting into technical design and tooling decisions, that the business case and application for AI have already been decided. Now the task is deciding how to effect a technical embedding and integration of the AI into the IT infrastructure and applications that will support the business process. 2. Modeling is first and foremost AI systems are built around models that utilize data stores, algorithms for query, and machine learning that expands the AI’s body of knowledge as the AI recognizes common logic patterns in data and assimilates knowledge from them. There are many different AI models to choose from. In most cases, companies use predefined AI models from vendors and then expand on them. In other cases, companies elect to build their own models “from scratch.”  Related:Building from scratch usually means that the organization has an on-board data science group with expertise in AI model building. Common AI model frameworks, provide the software resources and tools. These AI model-building technologies are not familiar to most IT staffs. The technologies use data graphs to build dataflows and structures that define how the data will move through the graph. Operational flows for the logic that operates on data must be defined. The model-building software also provides for algorithm development, model training, business rule definitions, and the machine learning that the model executes on its own as it “learns” from the data it ingests. IT might not know this stuff, but it can’t afford to ignore it. IT and CIOs need at least a working knowledge of how these opensource model building technologies work, because inevitably, these models must interface with IT infrastructure and data.  3. IT Infrastructure comes next Related:How to integrate an AI system with existing IT infrastructure is where CIOs can expect significant dialogue with their technical staffs. The AI has to be integrated seamlessly with the top to bottom tech stack if it is going to work. This means discussing how and where data from the AI will be stored, with SQL and noSQL databases being the early favorites. Middleware that enables the AI to interoperate with other IT systems must be interfaced with. Most AI models are open source, which can simplify integration --  but integration still requires using middleware APIslike REST, which integrates the AI system with Internet-based resources; or GraphQLwhich facilitates the integration of data from multiple sources. It’s IT that decides how to deploy the optimal data stores, infrastructure storage and connectors needed to support the AI, and there are likely to be different optionsfor deployment. This is where the CIO needs to dialogue with technical staff. 4. Data quality The AI group will rely on IT to provide quality data for the AI. This is accomplished in two ways: 1) by ensuring that all data incoming into the AI data repository is “clean”, and it is accurate and it is able to interact with other data in the AI data repository; and the data is secure. Whether it is working with outside vendors, vetting vendors for clean, secure data and periodically auditing them; or defining the data transformations and security technology and operations that must be put in place internally, it is all IT’s responsibility. The CIO will need to dialogue on technical levels with vendors, and with the IT database, storage, security, systems, applications and networking groups. Related:5. AI security The datain and to AI must be secure at all times. To arrive at this point, security must be enacted on multiple levels, and it will entail technical discussions and decision making to get there.  First and foremost is data security. Much of this has already been discussed under data quality, and it will involve most IT departmental teams. Second is user access authorities and activity monitoring. Who gets access to what, and how will you monitor user activities? The users can define their own authorization lists and IT can implement these -- but complication occurs when it comes to monitoring user activities. If for example, the user activities occur only with onsite data repositories, sites can use a technology like IAM, which gives IT granular visibility of every user activity. However, if cloud-based access is involved, IAM won’t be able to monitor this activity at any level of detail. It might become necessary to use CIEMsoftware instead to gain granular observation of user activity in the cloud. Then there are “umbrella” technologies like IGAthat can serve as an over-arching framework for both IAM and CIEM.  The IT security groupmust decide which strategy to adopt for comprehensive protection of AI. Finally, there are malware threats that are unique to AI. Yes, you can use standard malware detection to ward off attacks from bad actors on AI data, just as you would on standard data and applications -- but the plot thickens from there. For example, there are malware injections into AI systems that can inject inaccurate data or change the labels and features of data. These skew the results derived from that data and result in erroneous recommendations and decisions. The practice is known as “data poisoning.”  IT is expected to come up with a data validation technique for incoming data that can detect possible poisoning attempts and stop them. This could involve data sanitization technologies, or data source verifications, and it is possible that inserting these technologies could slow down data transport. The technical staff needs to weigh these options, and CIOs should insert themselves into the discussions. The Bottom Line The bottom line is clear: CIOs must be able to dialogue and participate in decisions at multiple AI levels: the strategic, the operational and the technical. Even if companies have dedicated data science groups, both data scientists and users will ultimately wend their way to IT, which still must make the whole thing happen. CIOs can help both their staffs and their companies if they develop a working knowledge of how AI works, in addition to understanding the strategic and operational aspects of AI -- because companies, employees and business partners all need to hear the CIO’s voice.  #what #cios #need #know #about

Don’t call Kylie Kelce a WAG. The acronym for the “wives and girlfriends” of professional athletes rankles the podcaster, who first rose to fame as the wife of retired Philadelphia Eagles player Jason Kelce. As Kelce explains, the phrase suggests that “your spouse’s profession swallows you up as well.”But many in the media are heralding this moment as a “new era” for WAGs, and Kelce is just one of several famous women who are at the fore of this renaissance: Everyone from TikToker Alix Earle, who is dating Miami Dolphins player Braxton Berrios, to Olympic gold medalist Simone Biles — unquestionably the more famous athlete — who is married to the Chicago Bears’ Jonathan Owens. Then there’s Taylor Swift, one of the most successful musicians on the planet, who, thanks to her relationship with Kylie’s brother-in-law Travis Kelce, has become the ultimate symbol of the new WAG.Meanwhile, a host of lesser-known women are experiencing their first taste of fame through their relationships with tennis players, Formula 1 race-car drivers, and even pole-vaulters. A sizable number have leveraged their romantic lives to receive brand deals, podcasting opportunities, and magazine profiles.By and large, our understanding of WAGs is rapidly evolving to acknowledge their own social and economic power. They’ve transformed from tabloid punching bags to an appealing status symbol. Still, the continued use of the term does raise some complicated questions: Why are we so interested in defining these women, some of whom are independently successful, by their relationships to men? And what does it mean that they might be raking in more attention and financial opportunities than some female athletes? The rise of the new WAG The public’s fascination with WAGs isn’t new. The acronym originated across the pond in the early 2000s to describe the wives and girlfriends of English footballers. British tabloids and football fans alike lambasted women — celebrities in their own right — like former Girls Aloud member Cheryl Cole and former Spice Girl Victoria Beckham for their partying, extravagant spending, and flashy, maximalist looks. When the England national football team lost the 2006 FIFA World Cup, their partners were blamed in the press for the defeat. In the United States, being a WAG could be an equally dangerous public position. From Jessica Simpson to the Kardashians, they’ve been painted as distractions, attention-seekers, and bearers of bad luck. Over the past two decades, though, a WAG has become less of an involuntary title and more of an identity that some women are willing to cultivate, given that it can come with its own rewards.David and Victoria Beckham at the MOBO Awards on October 6, 1999. Dave Hogan/Getty ImagesThis modern version of WAG-dom can be credited to early 2010s reality shows like WAGS, Basketball Wives, and La La’s Full Court Life. These platforms allowed these women — some anonymous before they entered into relationships with athletes — to craft their own public narratives and become notable personalities on their own. For years now, Ayesha Curry, wife of Golden State Warriors point guard Stephen Curry, has modeled what it means to be a “WAG influencer,” embracing her public relationship with her spouse while building a separate career as a successful cookbook author and host. Since then, WAG-influencers have become a welcome staple of certain sports cultures. Formula 1 has exploded in recent years, with a small part of that popularity owed to the sport’s stylish other halves. Since 2017, female viewership has grown from 8 percent to 40 percent. This has been largely credited to the popular Netflix series Formula 1: Drive to Survive, which put a spotlight on the personal lives of drivers and, naturally, their partners. Lily Herman, who writes the F1 newsletter Engine Failure, says that the current popularity of WAG-influencers in Formula 1 can be credited to the former partners of a few young popular drivers from 2019 to 2022, like Carlos Sainz’s girlfriend Isa Hernáez and Charles Leclerc’s girlfriend Charlotte Sine, who were both featured on Drive to Survive. In 2022, Sine was the first WAG in the sport to explicitly use her access to the F1 circuit as a part of an ad campaign for the skincare brand Sunday Riley.“They were around during an era where the sport saw a lot of growth in its younger fan base, especially among teen girls and younger women, and there was a new wave of interest in these young drivers’ personal lives,” says Herman. These women have inspired fan pages, Tumblr accounts, and subreddits dedicated to their relationships, fashion, and rumored drama. Lately, the organization has fully embraced WAGs as recognizable supporting characters in the F1 universe, featuring them on social media and including them on chyrons during racing broadcasts. Tennis has tried to replicate the WAG-to-influencer pipeline too, although the sport and its fans are still warming up to the presence of outside partners. Morgan Riddle, who’s dating highest-ranked American male player Taylor Fritz, has been making get-ready-with-me videos for tournaments and vlogging about her life on the tennis tour since 2022. Ayan Broomfield, a former college tennis player who’s dating Frances Tiafoe, and influencer Paige Lorenze, who’s dating Tommy Paul, have mimicked the same career path, broadcasting their lives as WAGs on social media. Herman says that WAGs play a role in “adding dimension” to their male partners, contributing to the marketability of both. “Fritz is pretty bland as a public figure without his girlfriend,” says Herman. “She’s done way more in her work as an influencer and content creator to make him seem multidimensional than he has through solo interviews and profiles.”It certainly benefits younger, newer WAGs who are already powerful women. Biles and Swift have joined their ranks and seem to take pride in the role. Beckham, now a successful fashion designer, has also played a role in igniting a nostalgia for WAGs, thanks to the popular 2023 Netflix docuseries Beckham. The business of being a WAG is still very traditional In our current political climate, the WAG boom raises interesting questions. Research shows that some Gen Z-ers are identifying as more conservative than their parents. “Trad wife” content abounds online. Where do WAGs fit in? WAG influencers share some obvious similarities to tradwife influencers, women who’ve created lucrative identities and even businesses by perpetuating conservative ideas of marriage and motherhood. In a Substack essay, sports writer Frankie De La Cretaz argues that WAGs are essentially the tradwives of men’s sports: “No matter how many businesses a WAG starts or how many charities she runs, she still embodies a heteronormative idea of family and a woman’s place in society.” It’s hard to get around the fact that most WAGs are initially famous for their association with a male partner, although they may ultimately transcend that attachment.WAGs are gaining visibility while the most talented female athletes are still fighting for wage parity and struggling to land brand deals.But even attempts to define WAGs outside of their relationships come off a bit shallow. Stories about how these women are impacting sports largely focus on their brand deals and follower counts. When we celebrate the influence of WAGs, we’re mostly talking about their ability to turn other women into consumers and spectators, not athletes. Meanwhile, WAGs are gaining visibility while the most talented female athletes are still fighting for wage parity and struggling to land brand deals. Back in March, Australian tennis pro Daria Saville made a TikTok about the lack of sponsorships she and other female pros receive compared to tennis WAGs. “Female tennis players are not getting those brand deals,” she said. “It’s actually tennis WAGs that fit into the ‘aesthetic’ rather than, us, sweaty tennis players.” De la Cretaz tells Vox that the WAG boom echoes the mainstream platforming of tradwives. “It’s an extension of “girlboss” feminism, the idea that promoting women regardless of what that looks like is somehow good for women,” De la Cretaz says. “It’s also this idea that whatever you’re choosing is valid, even though those choices don’t exist in a vacuum.” The most visible WAGs are still predominantly in straight relationships, and a large part of being one still involves affirming a male athlete’s heterosexuality. As journalist Kira Cochrane wrote in a 2010 piece for the Guardian about football WAGs, “consciously or not, the women know their role is to boost their partner’s masculinity.” She added that their often highly feminized presentation “underlinesstatus as possessions, part of the package for footballers.” WAGs, with their new clout and influence, haven’t exactly gotten a total makeover. Rather, their hustle has grown more appealing. After all, they represent all the things women are encouraged to be in a time when mainstream culture is trending more conservative. They’re tradwives. They’re girlbosses. They’re stylish and beautiful. Most of all, they’re sitting on the sidelines. See More: #whatampamp8217s #behind #wag #renaissance

An AI integration modifies a business process and how employees work, but it also requires an integration with IT infrastructure and systems. This is where some of IT’s most technically savvy staff will be working, and they will want to discuss technology integration approaches and ideas. Most CIOs aren’t software engineers, but they are responsible for having a working knowledge of all things IT so they can hold meaningful dialogues with their most technical employees to assist in defining technology direction. What do CIOs need to know about the technical side of AI integration? 1. AI technical integration is about embedding AI in systems and workflows The assumption here is that by the time your staff is getting into technical design and tooling decisions, that the business case and application for AI have already been decided. Now the task is deciding how to effect a technical embedding and integration of the AI into the IT infrastructure and applications that will support the business process. 2. Modeling is first and foremost AI systems are built around models that utilize data stores, algorithms for query, and machine learning that expands the AI’s body of knowledge as the AI recognizes common logic patterns in data and assimilates knowledge from them. There are many different AI models to choose from. In most cases, companies use predefined AI models from vendors and then expand on them. In other cases, companies elect to build their own models “from scratch.”  Related:Building from scratch usually means that the organization has an on-board data science group with expertise in AI model building. Common AI model frameworks, provide the software resources and tools. These AI model-building technologies are not familiar to most IT staffs. The technologies use data graphs to build dataflows and structures that define how the data will move through the graph. Operational flows for the logic that operates on data must be defined. The model-building software also provides for algorithm development, model training, business rule definitions, and the machine learning that the model executes on its own as it “learns” from the data it ingests. IT might not know this stuff, but it can’t afford to ignore it. IT and CIOs need at least a working knowledge of how these opensource model building technologies work, because inevitably, these models must interface with IT infrastructure and data.  3. IT Infrastructure comes next Related:How to integrate an AI system with existing IT infrastructure is where CIOs can expect significant dialogue with their technical staffs. The AI has to be integrated seamlessly with the top to bottom tech stack if it is going to work. This means discussing how and where data from the AI will be stored, with SQL and noSQL databases being the early favorites. Middleware that enables the AI to interoperate with other IT systems must be interfaced with. Most AI models are open source, which can simplify integration --  but integration still requires using middleware APIslike REST, which integrates the AI system with Internet-based resources; or GraphQLwhich facilitates the integration of data from multiple sources. It’s IT that decides how to deploy the optimal data stores, infrastructure storage and connectors needed to support the AI, and there are likely to be different optionsfor deployment. This is where the CIO needs to dialogue with technical staff. 4. Data quality The AI group will rely on IT to provide quality data for the AI. This is accomplished in two ways: 1) by ensuring that all data incoming into the AI data repository is “clean”, and it is accurate and it is able to interact with other data in the AI data repository; and the data is secure. Whether it is working with outside vendors, vetting vendors for clean, secure data and periodically auditing them; or defining the data transformations and security technology and operations that must be put in place internally, it is all IT’s responsibility. The CIO will need to dialogue on technical levels with vendors, and with the IT database, storage, security, systems, applications and networking groups. Related:5. AI security The datain and to AI must be secure at all times. To arrive at this point, security must be enacted on multiple levels, and it will entail technical discussions and decision making to get there.  First and foremost is data security. Much of this has already been discussed under data quality, and it will involve most IT departmental teams. Second is user access authorities and activity monitoring. Who gets access to what, and how will you monitor user activities? The users can define their own authorization lists and IT can implement these -- but complication occurs when it comes to monitoring user activities. If for example, the user activities occur only with onsite data repositories, sites can use a technology like IAM, which gives IT granular visibility of every user activity. However, if cloud-based access is involved, IAM won’t be able to monitor this activity at any level of detail. It might become necessary to use CIEMsoftware instead to gain granular observation of user activity in the cloud. Then there are “umbrella” technologies like IGAthat can serve as an over-arching framework for both IAM and CIEM.  The IT security groupmust decide which strategy to adopt for comprehensive protection of AI. Finally, there are malware threats that are unique to AI. Yes, you can use standard malware detection to ward off attacks from bad actors on AI data, just as you would on standard data and applications -- but the plot thickens from there. For example, there are malware injections into AI systems that can inject inaccurate data or change the labels and features of data. These skew the results derived from that data and result in erroneous recommendations and decisions. The practice is known as “data poisoning.”  IT is expected to come up with a data validation technique for incoming data that can detect possible poisoning attempts and stop them. This could involve data sanitization technologies, or data source verifications, and it is possible that inserting these technologies could slow down data transport. The technical staff needs to weigh these options, and CIOs should insert themselves into the discussions. The Bottom Line The bottom line is clear: CIOs must be able to dialogue and participate in decisions at multiple AI levels: the strategic, the operational and the technical. Even if companies have dedicated data science groups, both data scientists and users will ultimately wend their way to IT, which still must make the whole thing happen. CIOs can help both their staffs and their companies if they develop a working knowledge of how AI works, in addition to understanding the strategic and operational aspects of AI -- because companies, employees and business partners all need to hear the CIO’s voice.  #what #cios #need #know #about

Ongoing Regent’s Park Estate Story Trail Regent’s Park Estate, London NW1Regent’s Park Estate Story Trail is a public art trail. Artworks include Unwritten by Polish artist Rafal Zajko, which excavates the history of a clandestine LGBTQ+ bar located beneath St Mary Magdalene church and You Are Here by Ocean Stefan, a queer, trans and non-binary artist based in Margate. olddiorama.com Unwritten by Rafal Zajko. Photography: Nick Turpin 22 May AJ goes OUT sixteen3’s showroom, London EC1Advertisement Sponsored by UK furniture designer sixteen3 and held at its showrooms in Clerkenwell as part of Clerkenwell Design Week, the AJ is holding a party to celebrate the release of this issue. Expect music, drinks, posters, copies of the AJ and lots of networking with co-collaborators and contributors. sixteen3.co.uk 24 May Queer Archi* Social London LGBT+ Community Centre, London SE1Organised by Queerscapes, Queer Archi* Social is a meet-up for queer and trans people working in the architecture, landscape, horticulture and built environment sectors. Not a formal networking event, it’s a chance to meet others who get it, swap stories and find new collaborators. londonlgbtqcentre.org queerscapes.com Still from E.1027 Eileen Gray and the House by the Sea. Credit: Rise And Shine World Sales 31 May Linden Archives Museum of LiverpoolStuart Linden Rhodes established Instagram account @Linden_Archives during Covid, digitising hundreds of 35mm photographs he shot for All Points North and Gay Times in the 1990s. This talk covers his books on the pub and club scene from Birmingham to Newcastle, as well as Pride events across the whole of England. liverpoolmuseums.org.ukAdvertisement 7 June Queer Realms – Zine Workshop Ada Haus, London SW8Part of The London Festival of Architecture, this zine workshop, organised by and for LGBTQ+ people, invites attendees to explore how their identities shape and are shaped by the London landscape, using zine-making as a creative tool. londonfestivalofarchitecture.org You Are Here by Ocean Stefan. Part of Regent's Park Estate Art Trail. Photography: Nick Turpin 9 June-14 September The Painted Picnic – A Summer Pavilion Citypoint, London EC2Designed by artist John Booth, Citypoint’s plaza will be transformed into a vibrant scene from an outdoor party. Inspired by the LFA’s 2025 theme Voices, the installation reimagines a still-life composition at an architectural scale that visitors can interact with. Digital illustrations by Booth celebrating Pride month will also be on display on the screen at Citypoint throughout June. Brookfield Properties as the commissioners. londonfestivalofarchitecture.org 14-18 June Queer Frontiers 1 Customs Wharf, EdinburghHeld over five days of the 2025 Architecture Fringe in Scotland, Queer Frontiers is a project that explores the ‘corporate capture’ of the queer as we progress towards a future where queer has become the norm. The event includes an exhibition and talks, organised by designer and researcher Kirsty Watt, designer Samuel Stair and Architecture Fringe co-director Andy Summers. architecturefringe.com Still from E.1027 Eileen Gray and the House by the Sea. Credit: Rise And Shine World Sales 18 June E.1027 Eileen Gray and the House by the Sea Museum of BathAs part of Queer Bath 2025’s festival and in partnership with FilmBath, this screening sheds light on Irish designer and architect Eileen Gray’s story and the significance of the Modernist villa E.1027 in queer architectural history. The screening will be followed by a discussion on gender, space, and visibility in design. queerbath.co.uk June, date TBC Architecture LGBT+ Life Drawing HOK, London W1Architecture LGBT+’s next free-to-attend monthly life drawing class is being held at HOK’s offices near Warren Street. A queer model will do a variety of poses throughout the evening for attendees to draw. Drawing supplies, music and drinks are all included. The event is aimed at those who work or study within the architectural field. architecturelgbt.com Life drawing at Heatherwick Studio. Photography: Daniel Innes and Joe Stancer 21 June Soho Queer History – Walking Tour Trafalgar Square, London WC2A two-hour walking tour exploring the history of London LGBTQ+ life. It takes you through the West End, sharing stories of drag queens of the 1700s, gay soirées of the 1920s, and the development of this queer neighbourhood. londonfestivalofarchitecture.org 4 July Queer Nightcrawl Through the City NLA, The London Centre, London EC2Dani Dinger and Dan de la Motte of Queer Tours of London shine a light on London's hidden queer stories. The tour strolls down Sodomites Walk, heads to the docks to discover the secret lives of the Mollies of 18th Century Wapping and minces down Old Compton Street to navigate the danger and dalliance of 1930s Soho. thelondoncentre.org 5 July Architecture LGBT+ London Pride Celebration 2025 London, location TBCArchitecture LGBT+ hosts a breakfast and drinks ahead of the London Pride parade to gather architects and built environment professionals together before joining the parade with the official architecture float. architecturelgbt.com London Pride Float competition winning scheme Proudspeaker by oo office. Credit: oo office 5 July London Pride Float Hyde Park Corner, LondonIn March this year, the LFA, Architecture LGBT+ and Freehold announced an open call for the annual £8,000 pride float competition, which is backed by Brookfield Properties and will celebrate the contributions of LGBTQIA+ architects to the built environment. The winner is oo office. architecturelgbt.com November, date TBC Queer Places: The Exhibition 2.0 Liverpool, location TBCLaunching its second round, exhibition Queer Places, a growing archive of Liverpool’s LGBTQ+ spaces past, present and future, opens its doors again in November. The exhibition will be filled with art, architectural models, maps, photographs and artefacts celebrating queer heritage. New this year are interactive 3D models of historic queer spaces. queerplaces.co.uk Queer Places exhibition. Credit: Queer Places Organisations, initiatives and platforms Architecture Foundation Young Trustees’ Spatial Queeries Spotlight Sunday A weekly spotlight on LGBT+ practitioners, design initiatives and queer spaces. @youngtrusteesArchitecture LGBT+ Not-for-profit organisation run by volunteers. It aims to provide an inclusive and prejudice-free environment for LGBT+ architects and those working and studying within the profession through learning, mentoring and networking events – including life drawing and yoga. architecturelgbt.com @architecturelgbtArchitecture LGBT+ Academic Champions NetworkAn alliance of academic champions – one per architecture school in the UK – working to improve representation and understanding of queer identity and action in architectural education. architecturelgbt.com/academic-champions-networkBuilding Equality UK-wide member association with resources for built environment consultants, engineers, developers, contractors and institutions – plus events. buildingequalityuk.comFirst Brick Community-led, democratically run housing organisation aiming to build housing and community spaces for LGBTQ+ people who want and need it. firstbrickhousing.co.ukFreehold Networking hub for LGBTQ professionals and allies in the UK’s real estate industry. freeholdlgbt.comFriends of The Joiners Arms: The JOIN Project Collaboration with community partners to explore how LGBTQIA+ venues and organisations can help create inclusive spaces and better opportunities for work, training and volunteering. friendsjoinersarms.comHomotopia Arts and social justice organisation based in Liverpool supporting local, national, and international queer and trans creatives, artists and makers. homotopia.netInterEngineering A professional network aiming to connect, inform and empower lesbian, gay, bisexual and transgender engineers and their straight allies. interengineeringlgbt.comLondon LGBT Community Centre Based in pop-up premises in Southwark, this centre is a safe, sober space that welcomes and supports anyone identifying as LGBTQ+. The space was fitted out by the design and architecture community, who rallied around to support the space. londonlgbtqcentre.orgOpen Plan Scotland A volunteer-led advocacy and support network for all who identify as LGBTQIA+ and study or work across architecture in Scotland. openplan.scot @openplanscotlandOutwardly Creative A new event in Brighton bringing together queer members of the arts and creative industries, including architects. outwardlycreative.co.uk @outwardlycreativePlanning Out Network for LGBT professionals in the town planning and planning sector. @planningoutPride of Place: England’s LGBTQ Heritage Resource and interactive map uncovering and celebrating the LGBTQ heritage of buildings, places and landscapes across England. historicengland.org.ukThe London Queer Housing Coalition Specialist steering group made up of by-and-for LGBTQ+ housing and homelessness organisations working in the capital. stonewallhousing.org/lqhcThe Outside Project London’s LGBTIQ+ community shelter, centre, domestic abuse refuge and trans night shelter. lgbtiqoutside.orgThe Proud Place, Manchester Manchester’s LGBT+ Community Centre hosting The Proud Trust in a purpose-built building. theproudtrust.orgTonic Community-led, not-for-profit organisation focused on creating vibrant and inclusive urban LGBTQ+ affirming retirement communities to address issues of loneliness and isolation of older LGBTQ+ people. tonichousing.org.ukRIBA Collections: LGBTQ+ spaces Research guide to a few of the historical spaces that have formed sites where LGBTQ+ communities have explored, celebrated or concealed sexual and gender identities. architecture.comQueerscapes A platform and community for queer and trans spatial practitioners, including architects, designers, landscape architects, urbanists, builders, gardeners, artists and anyone working with space. queerscapes.com @_queerscapesQueercircle Charity founded to fill the gaps and advocate for systemic change where other arts, health and education institutions fail or actively perpetuate harm, based in the Design District in a David Kohn-designed building. queercircle.orgQueer Design Club Online platform where LGBTQ+ designers can celebrate queer contributions to the design industry and visual culture, share their work and connect with each other. queerdesign.clubQuEAN: Queer Educators in Architecture Network Network of queer spatial design educators – with a focus on queer theory, pedagogies, identities and intersections with spatial design – founded by Gem Barton. @quean_the_networkQueer Places A growing, free digital archive celebrating the vibrant LGBTQ+ spaces of Liverpool’s past, present and future. queerplaces.co.uk @queerplacesQueer Scenarios A research, practice and dissemination community that explores and supports queer identities and queer approaches within critical spatial practices, working collaboratively between teaching staff and students. Based at Central Saint Martins. @queer_scenariosThis list is by no means comprehensive and there are plenty of other resources available. If you are doing something in this field, the AJ would love to hear from you. #goes #out #upcoming #events #calendar

In February 2024, CNN reported, “A finance worker at a multinational firm was tricked into paying out million to fraudsters using deepfake technology to pose as the company’s chief financial officer in a video conference call.” In Europe, a second firm experienced a multimillion-dollar fraud when a deepfake emulated a board member in a video allegedly approving a fraudulent transfer of funds. “Banks and financial institutions are particularly at risk,” said The Hack Academy. “A study by Deloitte found that over 50% of senior executives expect deepfake scams to target their organizations soon. These attacks can undermine trust and lead to significant financial loss.”  Hack Academy went on to say that AI-inspired security attacks weren’t confined to deepfakes. These attacks were also beginning to occur with increased regularity in the form of corporate espionage and misinformation campaigns. AI brings new, more dangerous tactics to traditional security attack methods like phishing, social engineering and the insertion of malware into systems. For CIOs, enterprise AI system developers, data scientists and IT network professionals, AI changes the rules and the tactics for security, given AI’s limitless potential for both good and bad. This is forcing a reset in how IT thinks about security against malicious actors and intruders. Related:How Bad Actors are Exploiting AI What exactly is IT up against? The AI tools that are available on the dark web and in public cyber marketplaces give security perpetrators a wide choice of AI weaponry. Also, IoT and edge networks now present much broader enterprise attack surfaces. Security threats can come in videos, phone calls, social media sites, corporate systems and networks, vendor clouds, IoT devices, network end points, and virtually any entry point into a corporate IT environment that electronic communications can penetrate. Here are some of the current AI-embellished security attacks that companies are seeing: Convincing deepfake videos of corporate executives and stakeholders that are intended to dupe companies in pursuing certain actions or transferring certain assets or funds. This deep faking also extends to voice simulations of key personnel that are left as voicemails in corporate phone systems.  Phishing and spearfishing attacks that send convincing emailsto employees, who mistakenly open them because they think the sender is their boss, the CEO or someone else they perceive as trusted. AI supercharges these attacks because it can automate and send out a large volume of emails that hit many employee email accounts. That AI continues to “learn” with the help of machine learning so it can discover new trusted sender candidates for future attacks.   Related:Adaptive messaging that uses generative AI to craft messages to users that correct grammar and that “learn” from corporate communication styles so they can more closely emulate corporate communications that make them seem legitimate. Mutating code that uses AI to change malware signatures on the fly so antivirus detection mechanisms can be evaded. Data poisoning that occurs when a corporate or cloud provider’s AI data repository is injected by malware that altersso the data produces erroneous and misleading results.  Fighting Back With Tech To combat these supercharged AI-based security threats, IT has number of tools, techniques and strategies it can consider. Fighting deepfakes. Deepfakes can come in the form of videos, voicemails and photos. Since deepfakes are unstructured data objects that can’t be parsed in their native forms like real data, there are new tools on the market that can convert these objects into graphical representations that can be analyzed to evaluate whether there is something in an object that should or shouldn’t be there. The goal is to confirm authenticity.  Related:Fighting phishing and spear phishing. A combination of policy and practice works best to combat phishing and spear phishing attacks. Both types of attacks are predicated on users being tricked into opening an email attachment that they believe is from a trusted sender, so the first line of defense is educatingusers on how to handle their email. For instance, a user should notify IT if they receive an email that seems unusual or unexpected, and they should never open it. IT should also review its current security tools. Is it still using older security monitoring software that doesn’t include more modern technologies like observability, which can check for security intrusions or malware at more atomic levels?  Is IT still using IAMsoftware to track user identities and activities at a top level in the cloud and on top and atomic levels on premises, or has it also added cloud identity entitlements management, which gives it an atomic level view of  user accesses and activities in the cloud? Better yet, has IT moved to identity governance administration, which can serve as an over-arching umbrella for IAM and CIEM plugins, plus provide detailed audit reports and automated compliance across all platforms? Fighting embedded malware code. Malware can lie dormant in systems for months, giving a bad actor the option to activate it whenever the timing is right. It’s all the more reason for IT to augment its security staff with new skillsets, such as that of the “threat hunter,” whose job is to examine networks, data and systems on a daily basis, hunting down malware that might be lurking within, and destroying it before it activates. Fighting with zero-trust networks. Internet of Thingsdevices come into companies with little or no security because IoT suppliers don’t pay much attention to it and there is a general expectation that corporate IT will configure devices to the appropriate security settings. The problem is, IT often forgets to do this. There are also times when users purchase their own IoT gear, and IT doesn’t know about it. Zero-trust networks help manage this, because they detect and report on everything that is added, subtracted or modified on the network. This gives IT visibility into new, potential security breach points. A second step is to formalize IT procedures for IoT devices so that no IoT device is deployed without the device’s security first being set to corporate standards.  Fighting AI data poisoning. AI models, systems and data should be continuously monitored for accuracy. As soon as they show lowered levels of accuracy or produce unusual conclusions, the data repository, inflows and outflows should be examined for quality and non-bias of data. If contamination is found, the system should be taken down, the data sanitized, and the sources of the contamination traced, tracked and disabled. Fighting AI with AI. Most every security tool on the market today contains AI functionality to detect anomalies, abnormal data patterns and user activities. Additionally, forensics AI can dissect a security breach that does occur, isolating how it happened, where it originated from and what caused it. Since most sites don’t have on-staff forensics experts, IT will have to train staff in forensics skills. Fighting with regular audits and vulnerability testing. Minimally, IT vulnerability testing should be performed on a quarterly basis, and full security audits on an annual basis. If sites use cloud providers, they should request each provider’s latest security audit for review. An outside auditor can also help sites prepare for future AI-driven security threats, because auditors stay on top of the industry, visit many different companies, and see many different situations. An advanced knowledge of threats that loom in the future helps sites prepare for new battles. Summary AI technology is moving faster than legal rulings and regulations. This leaves most IT departments “on their own” to develop security defenses against bad actors who use AI against them.  The good news is that IT already has insights into how bad actors intend to use AI, and there are tools on the market that can help defensive efforts. What’s been missing is a proactive and aggressive battle plan from IT. That has to start now.  #let #security #war #games #begin

Reading Time: 4 minutes Lifecycle marketers are facing a profound shift in how they engage customers. Artificial intelligencehas emerged as both a promise and a pressure point, positioned as the key to delivering hyper-personalized, timely, and impactful experiences. Yet behind the AI hype lies a more nuanced reality: executing AI-driven lifecycle marketing at scale is often messier than advertised. Marketers are caught between high expectations and systemic challenges, from fragmented data to stalled adoption and internal roadblocks. Understanding what’s holding AI backis essential for modern lifecycle teams.   The Great Data Disconnect One of the most persistent obstacles to realizing AI’s potential in customer engagement and lifecycle marketing is the inability to access and seamlessly activate customer data. Many marketers report being bottlenecked by their reliance on centralized data teams, which slows down the ability to test, iterate, and personalize campaigns at scale. While platforms frequently advertise integrations with major data warehouses such as Snowflake, Databricks, and Amazon Redshift, the reality often falls short. These connections may exist in name but not in function. Instead of enabling real-time audience segmentation or event-triggered personalization, many marketers are forced to rely on manual data exports, SQL queries, or engineering support just to get campaigns off the ground. This idea reinforces what many already know from experience: a tech stack is only as powerful as its weakest connection. The end goal isn’t just connection, but cohesion.  You need platforms that support bi-directional data sync, real-time event streaming, and transparent visibility across the customer journey without additional tools or workarounds. Until these capabilities are widespread, you’ll continue to feel like your AI ambitions are constrained by outdated infrastructure.   When AI Falls Short: Fatigue, Friction, and Fading ROI Even with the right data, many marketers are growing skeptical of AI’s ability to deliver tangible results.  AI fatigue is real.  Teams have poured time and resources into personalization engines, predictive analytics models, and generative content tools…only to find underwhelming returns. This disconnect isn’t imagined. Many AI projects ultimately fail to deliver on their promised ROI, often due to unclear use cases, lack of stakeholder alignment, or insufficient change management. For lifecycle marketers, this often plays out as prolonged proof-of-concept cyclesthat absorb months of energy with little to show. It’s not uncommon for teams to invest in tools that generate predictive churn scores or optimal send times, only to realize those insights aren’t actionable within their rigid engagement platforms. The issue is compounded by the flood of marketing tools claiming AI capabilities. In many cases, the “AI” is little more than rule-based automation in disguise, creating confusion around what real AI looks like and how it should be evaluated.   The Hidden Cost of Vendor Lock-In Another growing concern is vendor lock-in. As marketing tech stacks expand, so does the risk of becoming overly dependent on a single vendor’s ecosystem. This can be especially problematic when marketers outgrow their existing platforms but fear the complexity and disruption of switching. Model Context Protocolsoffer a path forward. These emerging frameworks are designed to create portable, standardized models for audience segmentation and campaign orchestration. With MCPs, marketers can define core elements—like audiences, campaign flows, and experimentation strategies—in a vendor-agnostic way. This means if they switch platforms, they don’t have to rebuild everything from scratch. The appeal is clear: reduced rework, faster time to value, and more flexibility in choosing best-of-breed tools. MCPs are still gaining traction, but their potential to reduce friction and future-proof marketing strategies is significant. Meanwhile, marketers continue to seek out credible migration stories that show what platform transitions look like in practice. Clear documentation, proven onboarding frameworks, and peer testimonials are increasingly essential for vendors looking to attract modern, data-savvy teams.     Practical Tips for Testing and Evaluating AI Tools Despite the challenges, marketers can adopt a more strategic approach to AI: one that reduces risk and increases clarity. Instead of jumping into full-scale deployments, teams can take smaller, more deliberate steps.  Using the following tactics, you can better differentiate between hype and real capability, allowing you to adopt AI tools that align with your goals and constraints. 1. Use sandbox environments Ask for a sandbox to simulate real use cases without impacting production data. This allows teams to pressure-test capabilities before committing. 2. Prioritize transparent case studies Look for success stories that offer a behind-the-scenes look at implementation, challenges, and actual results, not just polished outcomes. 3. Test integration depth, not just compatibility Don’t stop at “Yes, we integrate.” Ask: Can you trigger journeys based on real-time data? Can attributes update dynamically? Does data flow both ways? 4. Evaluate vendor support and education The best tools come with great training, responsive support, and documentation that accelerates onboarding and learning. 5. Learn from your peers Communities like the Lifecycle Luminaries Slack channel offer real, unfiltered feedback from practitioners. These sources are often the most trustworthy and valuable for unbiased opinions.     Embracing AI Realistically and Strategically AI has the power to transform lifecycle marketing, but only when it’s applied with clarity, intention, and the right foundation. Success doesn’t come from chasing the flashiest tools. It comes from solving real problems: fragmented data, limited visibility, and disconnected systems that prevent marketers from executing the strategies they already know will work. That’s why the most effective marketers right now aren’t asking, “How do I use more AI?” They’re asking, “Where can AI remove friction and help me act faster, smarter, and with more confidence?” At MoEngage, we’ve seen meaningful results when AI is embedded directly into the marketing workflow, not layered on top as an afterthought. Our AI engine, Sherpa, supports use cases like predictive segmentation, intelligent send-time optimization, and creative performance insights. These features are designed to help marketers spend less time reacting and more time proactively engaging their customers. This isn’t about replacing human decision-making. It’s about making smarter decisions, faster, with AI as the assistant, not the driver. As lifecycle marketing continues to evolve, the marketers who succeed won’t be the ones with the most tools. They’ll be the ones who combine strategic thinking, team alignment, and well-integrated AI to deliver personalized, timely, and scalable customer experiences. Marketers must remain curious but skeptical, innovative but grounded. Those who strike the right balance will be best positioned to harness AI’s full potential, but as a lasting engine of engagement and growth. The post Navigating the AI Revolution in Lifecycle Marketing: Challenges & Opportunities appeared first on MoEngage. #navigating #revolution #lifecycle #marketing #challenges

In February 2024, CNN reported, “A finance worker at a multinational firm was tricked into paying out million to fraudsters using deepfake technology to pose as the company’s chief financial officer in a video conference call.” In Europe, a second firm experienced a multimillion-dollar fraud when a deepfake emulated a board member in a video allegedly approving a fraudulent transfer of funds. “Banks and financial institutions are particularly at risk,” said The Hack Academy. “A study by Deloitte found that over 50% of senior executives expect deepfake scams to target their organizations soon. These attacks can undermine trust and lead to significant financial loss.”  Hack Academy went on to say that AI-inspired security attacks weren’t confined to deepfakes. These attacks were also beginning to occur with increased regularity in the form of corporate espionage and misinformation campaigns. AI brings new, more dangerous tactics to traditional security attack methods like phishing, social engineering and the insertion of malware into systems. For CIOs, enterprise AI system developers, data scientists and IT network professionals, AI changes the rules and the tactics for security, given AI’s limitless potential for both good and bad. This is forcing a reset in how IT thinks about security against malicious actors and intruders. Related:How Bad Actors are Exploiting AI What exactly is IT up against? The AI tools that are available on the dark web and in public cyber marketplaces give security perpetrators a wide choice of AI weaponry. Also, IoT and edge networks now present much broader enterprise attack surfaces. Security threats can come in videos, phone calls, social media sites, corporate systems and networks, vendor clouds, IoT devices, network end points, and virtually any entry point into a corporate IT environment that electronic communications can penetrate. Here are some of the current AI-embellished security attacks that companies are seeing: Convincing deepfake videos of corporate executives and stakeholders that are intended to dupe companies in pursuing certain actions or transferring certain assets or funds. This deep faking also extends to voice simulations of key personnel that are left as voicemails in corporate phone systems.  Phishing and spearfishing attacks that send convincing emailsto employees, who mistakenly open them because they think the sender is their boss, the CEO or someone else they perceive as trusted. AI supercharges these attacks because it can automate and send out a large volume of emails that hit many employee email accounts. That AI continues to “learn” with the help of machine learning so it can discover new trusted sender candidates for future attacks.   Related:Adaptive messaging that uses generative AI to craft messages to users that correct grammar and that “learn” from corporate communication styles so they can more closely emulate corporate communications that make them seem legitimate. Mutating code that uses AI to change malware signatures on the fly so antivirus detection mechanisms can be evaded. Data poisoning that occurs when a corporate or cloud provider’s AI data repository is injected by malware that altersso the data produces erroneous and misleading results.  Fighting Back With Tech To combat these supercharged AI-based security threats, IT has number of tools, techniques and strategies it can consider. Fighting deepfakes. Deepfakes can come in the form of videos, voicemails and photos. Since deepfakes are unstructured data objects that can’t be parsed in their native forms like real data, there are new tools on the market that can convert these objects into graphical representations that can be analyzed to evaluate whether there is something in an object that should or shouldn’t be there. The goal is to confirm authenticity.  Related:Fighting phishing and spear phishing. A combination of policy and practice works best to combat phishing and spear phishing attacks. Both types of attacks are predicated on users being tricked into opening an email attachment that they believe is from a trusted sender, so the first line of defense is educatingusers on how to handle their email. For instance, a user should notify IT if they receive an email that seems unusual or unexpected, and they should never open it. IT should also review its current security tools. Is it still using older security monitoring software that doesn’t include more modern technologies like observability, which can check for security intrusions or malware at more atomic levels?  Is IT still using IAMsoftware to track user identities and activities at a top level in the cloud and on top and atomic levels on premises, or has it also added cloud identity entitlements management, which gives it an atomic level view of  user accesses and activities in the cloud? Better yet, has IT moved to identity governance administration, which can serve as an over-arching umbrella for IAM and CIEM plugins, plus provide detailed audit reports and automated compliance across all platforms? Fighting embedded malware code. Malware can lie dormant in systems for months, giving a bad actor the option to activate it whenever the timing is right. It’s all the more reason for IT to augment its security staff with new skillsets, such as that of the “threat hunter,” whose job is to examine networks, data and systems on a daily basis, hunting down malware that might be lurking within, and destroying it before it activates. Fighting with zero-trust networks. Internet of Thingsdevices come into companies with little or no security because IoT suppliers don’t pay much attention to it and there is a general expectation that corporate IT will configure devices to the appropriate security settings. The problem is, IT often forgets to do this. There are also times when users purchase their own IoT gear, and IT doesn’t know about it. Zero-trust networks help manage this, because they detect and report on everything that is added, subtracted or modified on the network. This gives IT visibility into new, potential security breach points. A second step is to formalize IT procedures for IoT devices so that no IoT device is deployed without the device’s security first being set to corporate standards.  Fighting AI data poisoning. AI models, systems and data should be continuously monitored for accuracy. As soon as they show lowered levels of accuracy or produce unusual conclusions, the data repository, inflows and outflows should be examined for quality and non-bias of data. If contamination is found, the system should be taken down, the data sanitized, and the sources of the contamination traced, tracked and disabled. Fighting AI with AI. Most every security tool on the market today contains AI functionality to detect anomalies, abnormal data patterns and user activities. Additionally, forensics AI can dissect a security breach that does occur, isolating how it happened, where it originated from and what caused it. Since most sites don’t have on-staff forensics experts, IT will have to train staff in forensics skills. Fighting with regular audits and vulnerability testing. Minimally, IT vulnerability testing should be performed on a quarterly basis, and full security audits on an annual basis. If sites use cloud providers, they should request each provider’s latest security audit for review. An outside auditor can also help sites prepare for future AI-driven security threats, because auditors stay on top of the industry, visit many different companies, and see many different situations. An advanced knowledge of threats that loom in the future helps sites prepare for new battles. Summary AI technology is moving faster than legal rulings and regulations. This leaves most IT departments “on their own” to develop security defenses against bad actors who use AI against them.  The good news is that IT already has insights into how bad actors intend to use AI, and there are tools on the market that can help defensive efforts. What’s been missing is a proactive and aggressive battle plan from IT. That has to start now.  #let #security #war #games #begin

May 22, 2025Ravie LakshmananEnterprise Security / Malware A recently patched pair of security flaws affecting Ivanti Endpoint Manager Mobilesoftware has been exploited by a China-nexus threat actor to target a wide range of sectors across Europe, North America, and the Asia-Pacific region. The vulnerabilities, tracked as CVE-2025-4427and CVE-2025-4428, could be chained to execute arbitrary code on a vulnerable device without requiring any authentication. They were addressed by Ivanti last week. Now, according to a report from EclecticIQ, the vulnerability chain has been abused by UNC5221, a Chinese cyber espionage group known for its targeting of edge network appliances since at least 2023. Most recently, the hacking crew was also attributed to exploitation efforts targeting SAP NetWeaver instances susceptible to CVE-2025-31324. The Dutch cybersecurity company said the earliest exploitation activity dates back to May 15, 2025, with the attacks targeting healthcare, telecommunications, aviation, municipal government, finance, and defense sectors. "UNC5221 demonstrates a deep understanding of EPMM's internal architecture, repurposing legitimate system components for covert data exfiltration," security researcher Arda Büyükkaya said. "Given EPMM's role in managing and pushing configurations to enterprise mobile devices, a successful exploitation could allow threat actors to remotely access, manipulate, or compromise thousands of managed devices across an organization." The attack sequence involves targeting the "/mifs/rs/api/v2/" endpoint to obtain an interactive reverse shell and remotely execute arbitrary commands on Ivanti EPMM deployments. This is followed by the deployment of KrustyLoader, a known Rust-based loader attributed to UNC5221 that enables the delivery of additional payloads like Sliver. The threat actors have also been observed targeting the mifs database by making use of hard-coded MySQL database credentials stored in /mi/files/system/.mifpp to obtain unauthorized access to the database and exfiltrating sensitive data that could grant them visibility into managed mobile devices, LDAP users, and Office 365 refresh and access tokens. Furthermore, the incidents are characterized by the use of obfuscated shell commands for host reconnaissance before dropping KrustyLoader from an AWS S3 bucket and Fast Reverse Proxyto facilitate network reconnaissance and lateral movement. It's worth mentioning here that FRP is an open-source tool widely shared among Chinese hacking groups. EclecticIQ said it also identified a command-and-controlserver associated with Auto-Color, a Linux backdoor that was documented by Palo Alto Networks Unit 42 as used in attacks aimed at universities and government organizations in North America and Asia between November and December 2024. "The IP address 146.70.8767:45020, previously associated with Auto-Color command-and-control infrastructure, was seen issuing outbound connectivity tests via curl immediately after exploitation of Ivanti EPMM servers," Büyükkaya pointed out. "This behaviour is consistent with Auto-Color's staging and beaconing patterns. Taken together, these indicators very likely link to China-nexus activity." The disclosure comes as threat intelligence firm GreyNoise noted that it had witnessed a significant spike in scanning activity targeting Ivanti Connect Secure and Pulse Secure products prior to the disclosure of CVE-2025-4427 and CVE-2025-4428. "While the scanning we observed was not directly tied to EPMM, the timeline underscores a critical reality: scanning activity often precedes the public emergence of zero-day vulnerabilities," the company said. "It's a leading indicator — a signal that attackers are probing critical systems, potentially in preparation for future exploitation." Found this article interesting? Follow us on Twitter  and LinkedIn to read more exclusive content we post. SHARE     #chinese #hackers #exploit #ivanti #epmm

Tech Wheeled, rugged robot dog built for extreme industrial missions New robot to revolutionize industrial inspection and disaster response Published May 22, 2025 6:00am EDT close Wheeled, rugged robot dog built for extreme industrial missions The machine is designed to inspect industrial sites, respond to disasters, carry out logistics operations and support scientific research. Deep Robotics, a company from China, has unveiled a durable four-legged robot built to operate in extreme environments that humans struggle to traverse. It's called the Lynx M20, and it builds upon the agility of its predecessor, the Lynx robot dog.This versatile machine is designed to handle anything from inspecting industrial sites and responding to disasters to carrying out logistics operations and supporting scientific research. Here’s what you need to know.JOIN THE FREE "CYBERGUY REPORT": GET MY EXPERT TECH TIPS, CRITICAL SECURITY ALERTS AND EXCLUSIVE DEALS, PLUS INSTANT ACCESS TO MY FREE "ULTIMATE SCAM SURVIVAL GUIDE" WHEN YOU SIGN UP! Lynx M20Advanced terrain capabilities set the Lynx M20 apartThe Lynx M20 combines wheels and legs to traverse challenging terrain. It can move at an average speed of 4.5 mph, but in optimal conditions, it can go up to 11 mph. It can also walk and climb obstacles using its independent wheel-locking mechanism. Its impressive traversal makes it able to cross rugged mountain paths, muddy wetlands and urban ruins.The Lynx M20 is also great at navigation and monitoring, with its 96-line lidar system, which gives it 360-degree awareness. It also has a front-facing wide-angle camera capable of livestreaming and bidirectional lighting for venturing into dark environments.AI-powered intelligence for real-world challengesWhat really sets the Lynx M20 apart is its use of advanced artificial intelligence. The robot is equipped with AI motion-control algorithms that allow it to autonomously perceive and adapt to its environment, adjusting its posture and gait to handle everything from rocky trails to debris-strewn ruins.Thanks to reinforcement learning, the Lynx M20 can actually improve its performance over time, learning from experience so that it gets even better at tackling new or unexpected obstacles. This means it's not just following a set of pre-programmed instructions but is actively making decisions and getting smarter with every mission.The robot's dual 96-line lidar sensors and wide-angle cameras feed data into its onboard processors, enabling real-time mapping, omnidirectional obstacle avoidance and autonomous navigation, even in low visibility or completely dark environments.WORLD'S FIRST AI-POWERED INDUSTRIAL SUPER-HUMANOID ROBOT Lynx M20IP66 rated: Built to be toughThe Lynx M20 features IP66 water and dust resistance and operates in temperatures from minus 4 degrees Fahrenheit to 131 degrees Fahrenheit. This toughness makes it suitable for harsh weather conditions. Weighing 72.8 pounds, it can carry up to a 33-pound payload, climb 31.5-inch obstacles and navigate 45-degree inclines. The robot runs for 2.5 to 3 hours per charge with a hot-swap battery system to keep it going longer. Lynx M20The pro variant has advanced featuresThe Lynx M20 also has a Pro version, which includes autonomous charging, SLAM-based positioning and advanced navigation tools. It has more connectivity options, like USB and Gigabit Ethernet, to enhance its functionality.PricingThe price of the Lynx M20 is unknown as Deep Robotics has yet to reveal the details. However, its standard Lynx robodog is estimated to cost around meaning this could cost more.CHINA'S TRON 1 ROBOT HURDLES OVER OBSTACLES LIKE THEY'RE NOTHING Lynx M20What does this mean for you?If you work in industries like construction, energy, logistics or emergency response, the Lynx M20 could be a game changer. Its ability to handle rough terrain, carry heavy loads and operate in extreme weather means you can send it into places that are risky or even impossible for people to reach.Whether it is inspecting power lines after a storm, delivering supplies across a muddy worksite or helping out in disaster zones, this robot is designed to keep your team safer and your operations running smoothly. Its hot-swap battery system also means less downtime, so you can rely on it for long shifts without constant recharging interruptions.Kurt's key takeawaysThe Lynx M20 isn't just any robot. It's a tough, smart machine built to handle some of the hardest jobs out there. By combining wheels and legs, it moves in ways that most robots can't, making it perfect for tricky terrain and tough conditions.We don't know the exact price yet, but judging by what it offers, it's clearly designed for serious work. If you're dealing with challenging environments and need a reliable helper, this robot might just be the partner you've been waiting for.CLICK HERE TO GET THE FOX NEWS APPWhat are your thoughts on how industrial inspection robots like this might transform workplace safety and efficiency? Let us know by writing us at Cyberguy.com/Contact.For more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/Newsletter.Ask Kurt a question or let us know what stories you'd like us to cover.Follow Kurt on his social channels:Answers to the most-asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com. All rights reserved. Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com. #wheeled #rugged #robot #dog #built