Milagros Caturla fue una fotógrafa cuyas imágenes han permanecido ocultas hasta después de su muerte. Quizá por ello y su gran trascendencia, ya hay gente que la considera la 'Vivian Maier barcelonesa'.

[Juillet 2025, Londres] — Avec l’arrivée de l’été, de plus en plus d’investisseurs en cryptomonnaies […] Cet article Surfez sur la vague des crypto-monnaies : gagnez 3 500 $ par jour avec les mineurs DOT ! a été publié sur REA

Regarder du porno en VR séduit actuellement de plus en plus de monde, même les […] Cet article Regarder du porn VR : comment faire ? - juillet 2025 a été publié sur REALITE-VIRTUELLE.COM.

Remember how, when Palworld was blowing up, fans were excited that a Pokémon competitor might force The Pokémon Company to get its act together and stop releasing busted games like Scarlet and Violet? Whether that pans out remains to be seen, but giv

The recent wave of cyber attacks targeting UK retailers has been a moment of reckoning for the entire retail industry. As someone who went through supporting one of the largest retail breaches in history, this news hits close to home. The National Cyber Security Centre’s (NCSC) call to strengthen IT support protocols reinforces a hard truth: cybersecurity is no longer just a technical/operational issue. It’s a business issue that directly affects revenue, customer trust, and brand reputation. Retailers today are navigating an increasingly complex threat landscape, while also managing a vast user base that needs to stay informed and secure. The recent attacks don’t represent a failure, but an opportunity - an inflection point to invest in stronger visibility, continuous monitoring and a culture of shared responsibility that meets the realities of modern retail. We know that the cyber groups responsible for the recent retail hacks used sophisticated social engineering techniques, such as impersonating employees to deceive IT help desks into resetting passwords and providing information, thereby gaining unauthorised access to internal systems. Employees are increasingly a target, and retailers employ some of the largest, most diverse workforces, making them an even bigger risk with countless touchpoints for breaches. In these organisations, a cybersecurity-first culture is vital to combatting threats. Cybersecurity-first culture includes employees that are aware of these types of attacks and understand how to report them if they are contacted. In order to establish a cybersecurity-first culture, employees must be empowered to recognise and respond to threats, not just avoid them. This can be done through simulation training and threat assessments - showcasing real life examples of threats and brainstorming possible solutions to control and prevent further and future damage. This allows security teams to focus on strategy instead of constant firefighting, while leadership support - through budget, tools, and tone - reinforces its importance at every level. In addition to support workers, vendors also pose a significant attack path for bad actors. According to data from Elastic Path, 42% of retailers admit that legacy technology could be leaving them exposed to cyber risks. And with the accelerating pace of innovation, modern cyber threats are not only more complex, but often enter through unexpected avenues, like third-party vendors. Research from Vanta shows 46% of organisations say that a vendor of theirs has experienced a data breach since they started working together. The M&S breach is a case in point, with it being reported that attackers exploited a vulnerability in a contractor’s systems, not the retailer’s own. This underscores that visibility must extend beyond your perimeter to encompass the entire digital supply chain, in real time. Threats don’t wait for your quarterly review or annual audit. If you're only checking your controls or vendor status once a year, you're already behind. This means real-time visibility is now foundational to cyber defence. We need to know when something changes the moment it happens. This can be done through continuous monitoring, both for the technical controls and the relationships that introduce risk into your environment. We also need to rethink the way we resource and prioritise that visibility. Manual processes don’t scale with the complexity of modern infrastructure. Automation and tooling can help surface the right signals from the noise - whether it’s misconfigurations, access drift, or suspicious vendor behavior. The best case scenario is that security measures are embedded into all digital architecture, utilising a few security ‘must haves’ such as secure coding, continuous monitoring, and regular testing and improvement. Retailers who want to get proactive and about breaches following the events of the last few weeks can follow this action plan to get started: First, awareness - have your security leadership send a message out to managers of help desks and support teams to make sure they are aware of the recent attacks on retailers, and are in a position to inform teams of what to look out for. Then, investigate - pinpoint the attack path used on other retailers to make sure you have a full understanding of the risk to your organisation. After that, assess - conduct a threat assessment to identify what could go wrong, or how this attack path could be used in your organisation. The final step is to identify - figure out the highest risk gaps in your organisation, and the remediation steps to address each one. Strong cybersecurity doesn’t come from quick fixes - it takes time, leadership buy-in, and a shift in mindset across the organisation. My advice to security teams is simple: speak in outcomes. Frame cyber risk as business risk, because that’s what it is. The retailers that have fallen victim to recent attacks are facing huge financial losses, which makes this not just an IT issue - it’s a boardroom issue. Customers are paying attention. They want to trust the brands they buy from, and that trust is built on transparency and preparation. The recent retail attacks aren’t a reason to panic - they’re a reason to reset, evaluate current state risks, and fully understand the potential impacts of what is happening elsewhere. This is the moment to invest in your infrastructure, empower your teams, and embed security into your operations. The organisations that do this now won’t just be safer - they’ll be more competitive, more resilient, and better positioned for whatever comes next. Jadee Hanson is the Chief Information Security Officer at Vanta Read more about cyber security in retail Content Goes Here Harrods becomes latest UK retailer to fall victim to cyber attack Retail cyber crime spree a ‘wake-up call’, says NCSC CEO Retail cyber attacks hit food distributor Peter Green Chilled

Pictured Above: Designer Amber Lewis balances New England charm with old-world sophistication with a half Calacatta Vagli marble backsplash in the kitchen of this Martha's Vineyard home. To backsplash or not to backsplash? That is the question. Or is it? Because if anyone’s ever told you “you shouldn’t do anything halfway,” they clearly haven’t heard of the half backsplash. This twist on a design mainstay makes a compelling case for stopping short. So maybe the real question is: to backsplash or to half backsplash?Lately, we’ve seen more and more designers going for the latter. “A trend these days is to use 1/2 or 2/3 stone backsplashes with a six- to nine-inch ledge,” says designer Jennifer Gilmer. “This is typically used behind a range and adds interest as well as softening the overall look.” It’s not just aesthetic—it’s strategic functionality. “The ledge is useful for salt and pepper shakers, olive oil, and other items,” she adds. Ahead, we break down everything to know about half backsplashes and why this kitchen trend is gaining traction in the design world.Related StoriesWhat Is a Half Backsplash?Lisa PetroleMagnolia’s director of styling, Ashley Maddox, enlisted the help of designer Hilary Walker to create her midcentury-modern dream home in Waco, Texas. Complete with walnut kitchen cabinetry topped with a Topzstone countertop continued into a partial backsplash.“A half backsplash or 1/3 backsplash is when the material stops at a point on the wall determined by the design,” explains designer Isabella Patrick. This makes it distinct from a “built-out or existing element, such as upper cabinets, a ceiling, soffit, or some other inherent element of the space.” In other words, it’s intentional, not just the result of running out of tile.Courtesy of JN Interior SpacesTaking the ceiling height into consideration, JN Interior Spaces decided a half backsplash would be suitable for this sleek, modern kitchen.While traditional backsplashes typically reach the bottom of upper cabinetry or span the entire wall, partial backsplashes usually stop somewhere around four to 25 inches up, depending on the look you’re going for.And while it may sound like a design compromise, it’s actually quite the opposite.Related StoryWhy Designers Are Loving the Half-Height LookOpting for a half backsplash is a clever way to balance proportion, budget, and visual interest. “If the design does not have upper cabinets, we would opt for a half backsplash to create visual interest,” Patrick says. “A full wall of the same tile or stone could overwhelm the space and seem like an afterthought.”Shannon Dupre/DD RepsIsabella Patrick experimented with this concept in her own kitchen, mixing materials for a more layered half backsplash look.Instead, Patrick often mixes materials—like running Cambria quartzite up from the counter to a ledge, then switching to Fireclay tile above. “This is a great example of how a singular material would have overwhelmed the space but also may have felt like an afterthought,” she explains. “Mixing materials and adding in details and personal touches is what good design is.”Another bonus? It lets the rest of the kitchen sing. “In another design, we eliminated the upper cabinets in favor of a more open and airy look so that the windows were not blocked—and so you were not walking right into a side view of cabinetry,” Patrick says. “No upper cabinets also makes the kitchen feel more of a transitional space and decorative, especially since it opens right into a dining room.”krafty_photos
copyright 2021This kitchen from JN Interior Spaces proves that a partial backsplash can still make a big impact. They chose to use an iridescent, almost-patina tile in this Wyoming kitchen.For Jill Najinigier of JN Interior Spaces, the choice is just as much about form as it is function. “It's all about how the backsplash interacts with the architecture,” she explains. “Wall height, windows, the shape of the hood, upper cabinets, or open shelves—where do they start and terminate?”In one standout project, Najinigier used a luminous tile just tall enough to tuck under a tapered plaster hood, topped with a narrow stone ledge carved from the same slab as the counter. The result? “Clean lines that make a stunning statement.”Mixing materials and adding in details and personal touches is what good design is.It’s Decorative and FunctionalHeather TalbertDesigner Kate Pearce installed a statement-making marble backsplash. Bringing it only halfway up allows its beauty to be appreciated while giving the other aesthetic elements in the space room to breathe.Don’t underestimate what that ledge can do. Designer Kate Pearce swears by hers: “I love my little five-inch-deep marble shelf that allows me to style some vintage kitchenware in the space,” she says. “And I think the shelf (and the pieces styled on it) is exactly what gives the kitchen an approachable feel—versus having a full backsplash of marble, which would have given the space a more serious vibe.”Stylish ProductionsPrioritizing visually continuity, Italian designer Federica Asack of Masseria Chic used the same leathered sandstone, a natural material that will develop a wonderful patina, for both the counters and the backsplash.Designer Federica Asack of Masseria Chic used a leathered sandstone for both her countertop and half backsplash, adding a ledge that’s just deep enough to style. “It allows for a splash-free decorating opportunity to layer artwork and favorite objects,” she says.Designer Molly Watson agrees: “The simple shelf is just deep enough for some special items to be on display,” she notes of a project where carrying the countertop stone up the wall helped keep things visually calm and scaled to the space. Related StoryThe Verdict on Half BacksplashesErin Kelly"Keeping materials simple in this kitchen was important for scale," says designer Molly Watson. "Carrying the countertop up the wall as a backsplash allowed the space to feel larger."Half backsplashes are having a major design moment, but not just because they’re practical. They’re a blank canvas for creativity. From floating ledges and mixed materials to budget-conscious decisions that don’t skimp on style, they’re a smart (and stylish) way to make your kitchen feel lighter, livelier, and totally considered.So, go ahead—do it halfway.Follow House Beautiful on Instagram and TikTok.

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more When DeepSeek released its R1 model this January, it wasn’t just another AI announcement. It was a watershed moment that sent shockwaves through the tech industry, forcing industry leaders to reconsider their fundamental approaches to AI development. What makes DeepSeek’s accomplishment remarkable isn’t that the company developed novel capabilities; rather, it was how it achieved comparable results to those delivered by tech heavyweights at a fraction of the cost. In reality, DeepSeek didn’t do anything that hadn’t been done before; its innovation stemmed from pursuing different priorities. As a result, we are now experiencing rapid-fire development along two parallel tracks: efficiency and compute.  As DeepSeek prepares to release its R2 model, and as it concurrently faces the potential of even greater chip restrictions from the U.S., it’s important to look at how it captured so much attention. Engineering around constraints DeepSeek’s arrival, as sudden and dramatic as it was, captivated us all because it showcased the capacity for innovation to thrive even under significant constraints. Faced with U.S. export controls limiting access to cutting-edge AI chips, DeepSeek was forced to find alternative pathways to AI advancement. While U.S. companies pursued performance gains through more powerful hardware, bigger models and better data, DeepSeek focused on optimizing what was available. It implemented known ideas with remarkable execution — and there is novelty in executing what’s known and doing it well. This efficiency-first mindset yielded incredibly impressive results. DeepSeek’s R1 model reportedly matches OpenAI’s capabilities at just 5 to 10% of the operating cost. According to reports, the final training run for DeepSeek’s V3 predecessor cost a mere $6 million — which was described by former Tesla AI scientist Andrej Karpathy as “a joke of a budget” compared to the tens or hundreds of millions spent by U.S. competitors. More strikingly, while OpenAI reportedly spent $500 million training its recent “Orion” model, DeepSeek achieved superior benchmark results for just $5.6 million — less than 1.2% of OpenAI’s investment. If you get starry eyed believing these incredible results were achieved even as DeepSeek was at a severe disadvantage based on its inability to access advanced AI chips, I hate to tell you, but that narrative isn’t entirely accurate (even though it makes a good story). Initial U.S. export controls focused primarily on compute capabilities, not on memory and networking — two crucial components for AI development. That means that the chips DeepSeek had access to were not poor quality chips; their networking and memory capabilities allowed DeepSeek to parallelize operations across many units, a key strategy for running their large model efficiently. This, combined with China’s national push toward controlling the entire vertical stack of AI infrastructure, resulted in accelerated innovation that many Western observers didn’t anticipate. DeepSeek’s advancements were an inevitable part of AI development, but they brought known advancements forward a few years earlier than would have been possible otherwise, and that’s pretty amazing. Pragmatism over process Beyond hardware optimization, DeepSeek’s approach to training data represents another departure from conventional Western practices. Rather than relying solely on web-scraped content, DeepSeek reportedly leveraged significant amounts of synthetic data and outputs from other proprietary models. This is a classic example of model distillation, or the ability to learn from really powerful models. Such an approach, however, raises questions about data privacy and governance that might concern Western enterprise customers. Still, it underscores DeepSeek’s overall pragmatic focus on results over process. The effective use of synthetic data is a key differentiator. Synthetic data can be very effective when it comes to training large models, but you have to be careful; some model architectures handle synthetic data better than others. For instance, transformer-based models with mixture of experts (MoE) architectures like DeepSeek’s tend to be more robust when incorporating synthetic data, while more traditional dense architectures like those used in early Llama models can experience performance degradation or even “model collapse” when trained on too much synthetic content. This architectural sensitivity matters because synthetic data introduces different patterns and distributions compared to real-world data. When a model architecture doesn’t handle synthetic data well, it may learn shortcuts or biases present in the synthetic data generation process rather than generalizable knowledge. This can lead to reduced performance on real-world tasks, increased hallucinations or brittleness when facing novel situations.  Still, DeepSeek’s engineering teams reportedly designed their model architecture specifically with synthetic data integration in mind from the earliest planning stages. This allowed the company to leverage the cost benefits of synthetic data without sacrificing performance. Market reverberations Why does all of this matter? Stock market aside, DeepSeek’s emergence has triggered substantive strategic shifts among industry leaders. Case in point: OpenAI. Sam Altman recently announced plans to release the company’s first “open-weight” language model since 2019. This is a pretty notable pivot for a company that built its business on proprietary systems. It seems DeepSeek’s rise, on top of Llama’s success, has hit OpenAI’s leader hard. Just a month after DeepSeek arrived on the scene, Altman admitted that OpenAI had been “on the wrong side of history” regarding open-source AI.  With OpenAI reportedly spending $7 to 8 billion annually on operations, the economic pressure from efficient alternatives like DeepSeek has become impossible to ignore. As AI scholar Kai-Fu Lee bluntly put it: “You’re spending $7 billion or $8 billion a year, making a massive loss, and here you have a competitor coming in with an open-source model that’s for free.” This necessitates change. This economic reality prompted OpenAI to pursue a massive $40 billion funding round that valued the company at an unprecedented $300 billion. But even with a war chest of funds at its disposal, the fundamental challenge remains: OpenAI’s approach is dramatically more resource-intensive than DeepSeek’s. Beyond model training Another significant trend accelerated by DeepSeek is the shift toward “test-time compute” (TTC). As major AI labs have now trained their models on much of the available public data on the internet, data scarcity is slowing further improvements in pre-training. To get around this, DeepSeek announced a collaboration with Tsinghua University to enable “self-principled critique tuning” (SPCT). This approach trains AI to develop its own rules for judging content and then uses those rules to provide detailed critiques. The system includes a built-in “judge” that evaluates the AI’s answers in real-time, comparing responses against core rules and quality standards. The development is part of a movement towards autonomous self-evaluation and improvement in AI systems in which models use inference time to improve results, rather than simply making models larger during training. DeepSeek calls its system “DeepSeek-GRM” (generalist reward modeling). But, as with its model distillation approach, this could be considered a mix of promise and risk. For example, if the AI develops its own judging criteria, there’s a risk those principles diverge from human values, ethics or context. The rules could end up being overly rigid or biased, optimizing for style over substance, and/or reinforce incorrect assumptions or hallucinations. Additionally, without a human in the loop, issues could arise if the “judge” is flawed or misaligned. It’s a kind of AI talking to itself, without robust external grounding. On top of this, users and developers may not understand why the AI reached a certain conclusion — which feeds into a bigger concern: Should an AI be allowed to decide what is “good” or “correct” based solely on its own logic? These risks shouldn’t be discounted. At the same time, this approach is gaining traction, as again DeepSeek builds on the body of work of others (think OpenAI’s “critique and revise” methods, Anthropic’s constitutional AI or research on self-rewarding agents) to create what is likely the first full-stack application of SPCT in a commercial effort. This could mark a powerful shift in AI autonomy, but there still is a need for rigorous auditing, transparency and safeguards. It’s not just about models getting smarter, but that they remain aligned, interpretable, and trustworthy as they begin critiquing themselves without human guardrails. Moving into the future So, taking all of this into account, the rise of DeepSeek signals a broader shift in the AI industry toward parallel innovation tracks. While companies continue building more powerful compute clusters for next-generation capabilities, there will also be intense focus on finding efficiency gains through software engineering and model architecture improvements to offset the challenges of AI energy consumption, which far outpaces power generation capacity.  Companies are taking note. Microsoft, for example, has halted data center development in multiple regions globally, recalibrating toward a more distributed, efficient infrastructure approach. While still planning to invest approximately $80 billion in AI infrastructure this fiscal year, the company is reallocating resources in response to the efficiency gains DeepSeek introduced to the market. Meta has also responded, With so much movement in such a short time, it becomes somewhat ironic that the U.S. sanctions designed to maintain American AI dominance may have instead accelerated the very innovation they sought to contain. By constraining access to materials, DeepSeek was forced to blaze a new trail. Moving forward, as the industry continues to evolve globally, adaptability for all players will be key. Policies, people and market reactions will continue to shift the ground rules — whether it’s eliminating the AI diffusion rule, a new ban on technology purchases or something else entirely. It’s what we learn from one another and how we respond that will be worth watching. Jae Lee is CEO and co-founder of TwelveLabs. Daily insights on business use cases with VB Daily If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI. Read our Privacy Policy Thanks for subscribing. Check out more VB newsletters here. An error occured.