html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd"Originally posted on 12 June 2024. Scroll down for details of the Dash 1.9 update.Polygonflow has updated Dash, its world building toolset for Unreal Engine 5.Dash 1.7 adds a new vines tool for growing vegetation procedurally across any 3D model, a new Blend material and an instant color grading system.Dash 1.8 adds Dash Board, a new PureRef-style reference image organizer, and a Chat-GPT-based AI assistant.Dash 1.8.5 adds Data Tables, a new system for layering effects, makes it possible to create terrain using height maps or guide curves, and cuts the price of the software.Dash 1.9 adds support for Runtime Virtual Texturing and a new Advanced Water Shader, and reworks the Content Browser.A new name for Polygonflows GraphN Library, minus GraphN itselfReleased in 2023, Dash is a rebranded version of the library of Unreal Engine 5 tools that used to accompany GraphN, Polygonflows now-discontinued node-based programming environment for Maya and Unreal Engine.It is intended to let artists to build complex environments without having to navigate the Unreal Editors interface, working primarily in fullscreen mode in the viewport.It provides readymade behaviours accessible by typing natural-language search terms into a floating prompt bar for common scene-building tasks like create terrain and apply water, plus scattering tools for dressing environments.As well as game development, Dash can be used for offline work: for example to create animations, visual effects projects or architectural visualizations in Unreal Engine.https://www.cgchannel.com/wp-content/uploads/2024/06/240611_Dash17_WorldbuildingToolUnrealEngine5_tw.mp4Dash 1.7: new vines tool generates procedural vegetation across any 3D modelDash 1.7 adds a lot of new features to the software, but the most eye-catching is Create Vines on Selection, for growing 3D vegetation procedurally across any surface.Despite the name, it isnt confined to growing vines, since you can use texture atlases from the Megascans asset library free for use in UE5 to customize the leaf type.The basic workflow will be familiar to anyone who has used an ivy generator such as the ones available for 3ds Max and Blender, with users able to control the form of the vegetation by adjusting parameters for growth, surface adhesion and gravity.New Blend material and automatic color grading systemOther new features include the Blend material, which makes it possible to create custom ground surfaces by blending from three source surfaces.Polygonflow describes is as being a lite version of Quixel Mixer, blending the surface color, height map and noise settings from the sources.There is also a new Image to Grading system, which makes it possible to color grade the viewport display to match a reference image: either a local file, or a URL.In addition, Dash now includes a library of IES profiles for recreating real-world lights in architectural visualizations, based on free online libraries like IES Library.https://www.cgchannel.com/wp-content/uploads/2024/06/240611_Dash17_VolumeScatter.mp4Updates to the scattering tools, including support for 3D scatteringThe scattering toolset has also been expanded, with the new Volume Scatter tool making it possible to scatter objects in 3D, as well as over surfaces.It is possible to use any mesh as the scatter volume, as shown in the video above, where a blobby mesh is used as a volume within which to distribute a flock of birds.The 2D scattering tools get the option to use any landscape paint layer as a mask, and the randomize the colors of the scattered objects. Automatic AI-based object taggingIn addition, Dash 1.7 makes it possible to tag assets within a users Asset Library automatically using Open AIs GPT-4 AI model.AI tagging was originally introduced in Dash 1.5, but Polygonflow describes the original open-source AI model it was using as fairly limited in quality and speed.The new GPT-based system uses a ChatGPT Enterprise plan, so OpenAI cannot use Dash users data for training its AI models.When tagging assets manually, it is now possible to multi-select objects.Other workflow improvementsWorkflow improvements include a new Reference system, which supersedes the old Variables system for controlling shared properties used by Dash tools.It is also now possible to export assets and all of their dependencies from an Unreal Engine project as .zip archives.Other key changes since we last wrote about Dash include the option to use assets from multiple UE5 projects in an environment, which was added in Dash 1.6.Updated 23 October 2024: Polygonflow has released Dash 1.8.The update reworks Dashs user interface, splitting features into distinct menus, and unifying many floating panels into a single Tools panel.The softwares path-based tools Road Tool, Quick Pipe, Decal Scatter and Path Scatter have also been revamped from the ground up to make them easier to use.New PureRef-style image organizer and new AI assistantNew features in Dash 1.8 include the new Dash Board tool, an experimental new reference image organization tool, described as similar to Miro and PureRef.The update also adds a new Chat-GPT-based AI assistant, which makes it possible to type in plain-language questions and receive answers from the online documentation.Updates to the Surface Scatter tool and Blend materialThe Surface Scatter tool gets several new features, including the option to use the top, bottom and center of objects being scattered as pivot points, and to modify the size of scattered objects according to distance from a target object.The Blend Material added in Dash 1.7 has been updated to support rain and snow.Updated 23 January 2025: Polygonflow has released Dash 1.8.5.New features include Data Tables, an experimental system for layering effects.In the initial release, it is limited to layering masks to control object scattering, and curves to deform terrain, but Polygonflow aims to extend it to other systems in the next release.Create terrain surfaces using guide curves or heightmapsUsing curves to deform terrain is itself a new feature in Dash 1.8.5: in previous releases, it was only possible to use noise patterns to deform a landscape mesh.The update also introduces basic heightmap support.Other updated featuresOther changes include new options to hide visible texture repetitions in the Material Edit and Blend Material tools, and new options to control object rotation in the scattering tools. The update also adds support for Fab, Epic Games new online marketplace, with Unreal Engine assets downloaded using the Fab plugin now added to the Dash Content Browser.Updated 13 March 2025: Polygonflow has released Dash 1.9.The update reworks the Content Browser, making it possible to organize assets into Collections, and adding support for fuzzy search, semantic search and Boolean search operators.The Content Browser also now supports Unreal Engine Blueprints as well as standard assets.Support for RVT workflow, one-click falling leaf system, and a new Advanced Water ShaderThe update also introduces a new Runtime Virtual Texturing (RVT) workflow for generating texture data at runtime, improving interactive performance of a scene.It is intended for texturing terrain, and requires a static mesh.Other new features include a one-click system for adding falling leaves to a scene, and a new Advanced Water Shader that supports waves, a rain-on-water effect, and underwater effects. Price cuts to subscriptions, and perpetual licenses for studios as well as freelancersPolygonflow has also recently cut the price of Dash. For Freelance users those with funding under $250,000/year the cost of monthly subscriptions falls from $20/month to $14/month, while annual subscriptions fall from $190/year to $133/year.For larger studios, the cost of monthly Enterprise subscriptions falls even further, from $89/month to $14/month, although annual subscriptions remain unchanged at $850/year.Studio can also buy perpetual licenses of Dash, which were previously only available to Freelance users.Price and system requirementsDash is compatible with Unreal Engine 5+ on Windows 10+ only.For artists earning under $250,000/year, perpetual Freelance licenses cost $230, while Freelance subscriptions cost $14/month or $133/year.For larger studios, perpetual Enterprise licenses cost $999, while Enterprise subscriptions cost $14/month or $850/year.Read a full list of new features in Dash in the online release notesRead more about Dash on Polygonflows websiteHave your say on this story by following CG Channel on Facebook, Instagram and X (formerly Twitter). As well as being able to comment on stories, followers of our social media accounts can see videos we dont post on the site itself, including making-ofs for the latest VFX movies, animations, games cinematics and motion graphics projects.

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Long-horizon robotic manipulation tasks are a serious challenge for reinforcement learning, caused mainly by sparse rewards, high-dimensional action-state spaces, and the challenge of designing useful reward functions. Conventional reinforcement learning is not well-suited to handle efficient exploration since the lack of feedback hinders learning optimal policies. This issue is significant in robotic control tasks of multi-stage reasoning, where the achievement of sequential subgoals is essential to overall success. Poorly designed reward structures can cause agents to get stuck in local optima or exploit spurious shortcuts, leading to suboptimal learning processes. Additionally, most of the existing methods have high sample complexity, requiring large amounts of training data to generalize to diverse manipulation tasks. Such constraints render reinforcement learning impossible for real-world tasks, where data efficiency and well-structured learning signals are key to success.Earlier research that has addressed these issues has explored model-based reinforcement learning, demonstration-based learning, and inverse reinforcement learning. Model-based methods, including TD-MPC2, improve sample efficiency by exploiting predictive world models but require large amounts of exploration to optimally optimize policies. Demonstration-based methods, including MoDem and CoDER, mitigate exploration problems by exploiting expert trajectories but lack good scaling to high-dimensional, long-horizon tasks due to the need for large datasets. Inverse reinforcement learning methods attempt to learn reward functions from demonstrations but lack good generalization ability and computational complexity. Further, most approaches in this field do not exploit the inherent structure of multi-stage tasks and hence do not exploit the possibility of decomposing complex objectives into more tractable subgoals.To overcome these challenges, researchers have introduced Demonstration-Augmented Reward, Policy, and World Model Learning (DEMO3), a reinforcement learning framework that integrates structured reward acquisition, policy optimization, and model-based decision-making. The framework introduces three main innovations: the transformation of sparse stage indicators to continuous, structured rewards providing more reliable feedback; a bi-phasic training schedule that initially uses behavioral cloning followed by an interactive reinforcement learning process; and the integration of online world model learning, allowing dynamic penalty adaptation during training. Unlike current approaches, this method allows real-time structured reward acquisition through stage-specific discriminators evaluating the probability of progress toward subgoals. As a result, the framework focuses on the attainment of task goals rather than demonstration imitation, significantly improving sample efficiency and generalization across tasks in robotic manipulation.DEMO3 is constructed from the foundation of the TD-MPC2 approach, which learns a latent-space world model for augmenting planning and control steps. The strategy is based on numerous stage-specific discriminators that each learns to forecast the chance of successful transitioning to the upcoming task stage. These discriminators are fine-tuned using the binary cross-entropy loss criterion and assist with online reward shaping, generating richer learning signals compared to sparse conventional rewards. Training adheres to a systematic two-phase process. First, in the pre-training stage, a policy and an encoder are learned using behavioral cloning from a partial set of expert demonstrations. Secondly, the agent engaged in continuous reinforcement learning processes learns to adjust and refine the policy through the process of environment interactions while depending on the derived dense rewards. An annealing process is introduced to improve the efficiency of operations through the transfer of dependence gradually from behavioral cloning to autonomous learning. This smooth transfer enables the progressive transfer of behavior from demonstration-induced imitation to policy improvement independently. The approach is tested on sixteen difficult robotic manipulation tasks, involving Meta-World, Robosuite, and ManiSkill3, and realizes substantial advances in learning efficiency as well as robustness when compared to existing state-of-the-art alternatives.DEMO3 outperforms state-of-the-art reinforcement learning algorithms by far, garnering significant improvements in sample efficiency, learning time, and overall task completion success rates. The method records an average of 40% improved data efficiency over competing methods, with as much as 70% improvement reported for very difficult, long-horizon challenges. The system always reports high success rates with as few as five demonstrations, compared to competing methods that require much larger datasets to achieve comparable success. By being capable of processing multi-stage sparse reward instances appropriately, the system outperforms accurate robotic manipulation tasks like peg insertion and cube stacking with improved success rates within tight interaction budgets. The computational costs are also comparable, averaging around 5.19 hours for every 100,000 interaction steps, hence making it more efficient than competing reinforcement learning models while yielding superior results in learning complex robotic skills.DEMO3 is a significant advance in reinforcement learning tailored for robotic control and is effective in addressing the challenges of dealing with long-horizon tasks with sparse rewards. By leveraging online dense reward learning, structured policy optimization, and model-based decision-making, this framework can achieve high performance and efficiency. The inclusion of a two-phase training procedure and dynamic reward adaptation helps in obtaining spectacular data efficiency improvements with success rates being 40-70% higher compared to existing methodologies on a variety of manipulation tasks. With the improvement of reward shaping, policy learning optimization, and reducing dependence on large demonstration datasets, this method provides the basis for more efficient and scalable robotic learning methods. Future research can be directed towards more advanced demonstration sampling approaches and adaptive reward-shaping techniques to further enhance data efficiency and accelerate reinforcement learning in real-world robotic tasks.Check outthe Paper and GitHub Page.All credit for this research goes to the researchers of this project. Also,feel free to follow us onTwitterand dont forget to join our80k+ ML SubReddit. Aswin AkAswin AK is a consulting intern at MarkTechPost. He is pursuing his Dual Degree at the Indian Institute of Technology, Kharagpur. He is passionate about data science and machine learning, bringing a strong academic background and hands-on experience in solving real-life cross-domain challenges.Aswin Akhttps://www.marktechpost.com/author/aswinak/Hugging Face Releases OlympicCoder: A Series of Open Reasoning AI Models that can Solve Olympiad-Level Programming ProblemsAswin Akhttps://www.marktechpost.com/author/aswinak/From Genes to Genius: Evolving Large Language Models with Natures BlueprintAswin Akhttps://www.marktechpost.com/author/aswinak/This AI Paper from Google Unveils an AI System that Masters Disease Management and Medication Reasoning Better than EverAswin Akhttps://www.marktechpost.com/author/aswinak/Rethinking MoE Architectures: A Measured Look at the Chain-of-Experts Approach Parlant: Build Reliable AI Customer Facing Agents with LLMs (Promoted)

Free-to-play 3v3 shooter Spectre Divide is being shut down six months after its initial launch in September 2024, and just weeks after its arrival on PS5 and Xbox Series X|S. Its developer Mountaintop Studios is also closing. Moutaintop CEO Nate Mitchell confirmed the news in a statement published on social media today.Unfortunately, the Season 1 launch hasnt achieved the level of success we needed to sustain the game and keep Mountaintop afloat, explains the post.Spectre Divide CombatThe team was optimistic following the first week, reporting the game attracted around 400,000 players with a peak concurrent count of approximately 10,000 across all platforms.But as time has gone on, we havent seen enough active players and incoming revenue to cover the day-to-day costs of Spectre and the studio, the post continued. Since the PC launch, we stretched our remaining capital as far as we could, but at this point, were out of funding to support the game.We pursued every avenue to keep going, including finding a publisher, additional investment, and/or an acquisition. In the end, we werent able to make it work. The industry is in a tough spot right now.Spectre Divide will be taken offline within the next 30 days, and any money spent by players since the Season 1 launch will be refunded.The news comes contrary to reports in October 2024 that Spectre Divide isnt going anywhere.The servers arent shutting down, and the updates arent going to stop, said Mitchell at the time, maintaining Mountaintop had the funds to support Spectre for a long time.PlayIGNs positive preview of Spectre Divide in August 2024 heaped praise on the tactical 3v3 shooter for coming to the table with its intriguing Duality system, which saw players controlling two characters during matches. However, the news of its rapid shutdown comes on the heels of a number of other live-service fizzers, including the failure of Rocksteadys Suicide Squad: Kill the Justice League and Sonys Concord.Luke is a Senior Editor on the IGN reviews team. You can track him down on Bluesky @mrlukereilly to ask him things about stuff.

The only thing more worrying than being a teenager? Raising one. Thats a take-home from new Netflix dramaAdolescence, which follows the aftermath of a 13-year-olds arrest on suspicion of murder. Its an exceptional four-parter driven by a desperate question: how could something so horrendous happen, and what is to blame?Jack Thorne and Stephen Grahams script avoids simplistic answers. Until armed police batter down the Millers front door to arrest young Jamie (Owen Cooper), theres nothing to separate them from any other family: two loving parents, two ordinary teenagers Jamie doesnt appear to be the product of abuse, addiction or neglect. Until called upon to act as Jamies appropriate adult during questioning, his plumber dad Eddie (Stephen Graham) has never even been inside a police station.So, what happened? What turned a bright lad whose favourite subject at school is history and who once happily spent hours drawing pictures at the kitchen table, into a sickening newspaper headline? Is Jamie even guilty?With technical skill and enviable performances,Adolescenceexplores various answers to those questions. Without hysteria or moral panic, it asks if Jamie was influenced by online voices, and whether he was a bully, or a victim of bullying. His parents Eddie and Manda (Christine Tremarco) ask themselves if theyd done enough to understand him, and if theyd been too uncurious about what was really going on behind his closed bedroom door?Over four episodes, each filmed in real-time as one continuous shot,Adolescencecolours in the background to this harrowing situation while telling Jamies story. The initial arrest and interview are followed by episodes set among his classmates at school, in custody, and with his family.In the first hour, the one-shot technique pays dividends by approximating the realistic feel of a documentary series like24 Hours in Police Custody. From the drive to the station, to the custody officers list of questions, to the fingerprinting and medical examination, it feels like an observation of real events.In episode two, which follows the pupils at Jamies school, director Philip Barantini (who also used the one-shot technique to blood-pressure-raising realistic effect in restaurant dramaBoiling Point), the one-shot is a feat of preparation, control and choreography. The expertise required to pull off the complex choreography of moving herds of children and actors around a school, is intimidatingly impressive.Episode four is similarly impressive thanks to the empathy-generating acting talent of Graham and Tremarco as Jamies parents. We watch as Jamies family attempts to get the day back after its derailed by a cruelly thoughtless act.Its in episode three though, that the one-shot technique really pays off, thanks to the remarkable work of the young actor who plays Jamie. Almost entirely a two-hander between 15-year-old Owen Cooper andA Thousand Blows Erin Doherty as Briony Ariston, the clinical psychologist tasked with assessing Jamie, it is a remarkable hour showcasing one of the most captivating performances from a young screen actor in recent years.Episode three is the hour ofAdolescenceI couldnt turn away from. First by casting newcomer Owen, then by entrusting him with a script this complex, and by guiding him towards this performance, Barantini and his team have done something extraordinary. It was just announced that Cooper will play the young Heathcliff in Emerald Fennells starry, Margot Robbie-led take onWuthering Heights. Thats sure to be the next high-profile role of many more to come, should Cooper choose to keep acting.Doherty too, is terrific inAdolescences third episode, but shes the solid gold frame for Coopers in-depth oil-painting portrait of a desperately confused, clever, sad and angry child. Hes singularly naturalistic, with a range so wide that its unsettling the same young actor who charmed in one moment can knock the wind out of you with shock in the next. Cooper and Doherty share Mamet-ish tennis match dialogue as Jamie tries to interpret and anticipate Brionys line of questioning, and its never less than compelling.The fact that its taking place like a stage play, in real time and in a single take just makes it all the more extraordinary.Join our mailing listGet the best of Den of Geek delivered right to your inbox!Yes, were here to find more clues to the plot mystery did Jamie do it,whywould Jamie have done it? but theyre incidental to the fascinating picture the Cooper builds of the inside of Jamies head. To say more might spoil the experience, so well stop there. Be certain though, youre going to hear more about this episode and this young actor in the coming months and years.Adolescenceis by no means a perfect drama. It gives one character a speech lampshading its own sidelining of the murder victim which is perhaps intended to stave off criticism that like so many crime shows before, its used a dead girl as a prop through which to explore the male psych but a confession of guilt isnt an excuse.It is though, like all of Jack Thorne and Stephen Grahams collaborations (This Is England,The Virtues,Help) led by empathy, talent and a desire to connect people through storytelling. Ultimately, its a drama about grief not just for the dead child, but also for the one lost through the act of murder, and grief for the family that was shattered the moment the police arrived at their door.Watch it, struggle with its pain, start conversations with your own kids, be bowled over by its third episode, and listen out for the name Owen Cooper.All episodes of Adolescence are available to stream now on Netflix.

One of the most interesting cultures in the world of The Wheel of Time is that of the Aiel people, who dwell in the desert to the east of the Dragonwall mountain range. Like those in the West, they have a prophecy about the Dragon Reborn, but to them he is the caracarn, or Chief of Chiefs: one who will unite the disparate tribes of the Waste. Theres also another key difference we wanted to talk about with showrunner Rafe Judkins and Ayoola Smart, who plays the Aiel Maiden of the Spear known as Aviendha.One thing that I loved the first time I read the books was the Aiel, Judkins tells Den of Geek. I think theyre one of the cultures that is most representative of Robert Jordans ability to build something that feels as if it could be real. The Aiel dont feel like, Oh, these are some fantasy tropes weve thrown together, and this is how they make sense for this group.Tropes aside, the Aiel prophecy about an outsider savior sounds a lot like Dunes Fremen prophecy of the Lisan al Gaib, or Voice from the Outer World. But besides that commonality (and the desert setting), their view of the caracarn is quite different. Beyond the fact that the prophecy was not manufactured as it was in Dune (this is fantasy after all), there is very little reverence for the supposed messiah, as evidenced by Aviendhas attitude towards Rand in The Wheel of Time.Smart explains, When the myth of a prophecy turns into a reality, I think how thats going to make you feel or what you expect or what it is thats actually being fulfilled and in this case who that person is you dont know how thats going to affect you. [Aviendha] spent all of this time thinking about the idea of this person and not the reality of who that person is, and shes not that impressed.Aviendhas opinion might have something to do with the fact that the caracarn wont just unite the Aiel; he will also destroy them, a fact that makes their culture feel more grounded. They feel like a real people with a real culture, real history, real beliefs, real systems of honor, says Judkins. I think that the authenticity of them in the books was something that we were all really excited to bring to life, and all of the departments worked together to infuse every bit of the Aiel that you see on screen with what was there in the books in terms of building their culture.Smart believes Aviendhas initial contempt for Rand is part of the same journey of discovery for her character that the others are going through. One of the things for a lot of these characters, particularly a lot of the younger characters, is that there is a process and a journey to each of their understanding of the worlds that they live in, and also where they fit in that world, says Smart. And Aviendha has to learn a lot about what it means to interact with Rand.In the end, Aviendha provides an important ingredient in Rands rise to power: humility. As he travels to the Aiel Waste in The Wheel of Time season 3, hell find a very different attitude towards his role than he has experienced with the Aes Sedai of the West. As Smart puts it: I think Rand has to learn a lot before hes able to step into the shoes that all of these different people expect him to fill and Aviendha needs to keep him grounded.Not all Fremen believed Paul Atreides was the Mahdi, their off-world deliverer, and its likely that the Aiel tribes will also be divided in their level of confidence in the Chief of Chiefs. But in the end, theres nothing quite like an army of desert warriors to make both Dune and The Wheel of Time season 3 as action-packed as possible.The Wheel of Time season 3 premieres on Prime Video on March 13, 2025.

Mar 13, 2025Ravie LakshmananOpen Source / VulnerabilityMeta has warned that a security vulnerability impacting the FreeType open-source font rendering library may have been exploited in the wild.The vulnerability has been assigned the CVE identifier CVE-2025-27363, and carries a CVSS score of 8.1, indicating high severity. Described as an out-of-bounds write flaw, it could be exploited to achieve remote code execution when parsing certain font files."An out-of-bounds write exists in FreeType versions 2.13.0 and below when attempting to parse font subglyph structures related to TrueType GX and variable font files," the company said in an advisory."The vulnerable code assigns a signed short value to an unsigned long and then adds a static value causing it to wrap around and allocate too small of a heap buffer. The code then writes up to 6 signed long integers out of bounds relative to this buffer. This may result in arbitrary code execution."The company did not share any specifics on how the shortcoming is being exploited, who is behind it, and the scale of the attacks. However, it acknowledged that the bug "may have been exploited in the wild."When reached for comment, FreeType developer Werner Lemberg told The Hacker News that a fix for the vulnerability has been incorporated for almost two years. "FreeType versions larger than 2.13.0 are no longer affected," Lemberg said.In a separate message posted on the Open Source Security mailing list oss-security, it has come to light that several Linux distributions are running an outdated version of the library, thus rendering them susceptible to the flaw. This includes -AlmaLinuxAlpine LinuxAmazon Linux 2Debian stable / DevuanRHEL / CentOS Stream / Alma Linux / etc. 8 and 9GNU GuixMageiaOpenMandrivaopenSUSE LeapSlackware, andUbuntu 22.04In light of active exploitation, users are recommended to update their instances to the latest version of FreeType (2.13.3) for optimal protection.Found this article interesting? Follow us on Twitter and LinkedIn to read more exclusive content we post.SHARE

Mar 13, 2025Ravie LakshmananBrowser Security / EncryptionBrowser maker Mozilla is urging users to update their Firefox instances to the latest version to avoid facing issues with using add-ons due to the impending expiration of a root certificate."On March 14, 2025, a root certificate used to verify signed content and add-ons for various Mozilla projects, including Firefox, will expire," Mozilla said."Without updating to Firefox version 128 or higher (or ESR 115.13+ for ESR users, including Windows 7/8/8.1 and macOS 10.12-10.14 users), this expiration may cause significant issues with add-ons, content signing and DRM-protected media playback."Mozilla said the latest version of Firefox includes a new root certificate that will prevent this from happening. The update is crucial for all users of Firefox running a version prior to 128, or Extended Support Release (ESR) versions before 115.13, both of which were released on July 9, 2024. This includes all versions of Firefox for Windows, macOS, Linux, and Android.Root certificates are designed to identify a root certificate authority (CA), a trusted entity that ensures the authenticity of websites, add-ons and software updates. In this case, the certificate is used to verify that a browser add-on was approved by Mozilla.Should the digital certificate expire, systems that rely on the certificate can no longer meet authenticity and integrity guarantees, causing certain features like add-ons, alerts about breached passwords, or secure media playback to stop working.In the event the update is not applied before the deadline, it also risks causing the blocklists used for flagging harmful add-ons and revocation lists for recognizing untrusted SSL certificates and preloaded intermediate certificates to go out-of-date, putting users at risk of more threats."While it's possible to use Firefox without updating, you may experience problems such as add-ons being disabled, DRM media difficulties and other interruptions," it added. "Skipping the update also means missing important security fixes and performance improvements."Users are highly advised to check and confirm they're running Firefox version 128 and later by navigating to Menu > Settings > About Firefox. It's worth noting that iOS and iPad users are unaffected. Given that the Tor Browser is a modified version of Firefox ESR, it's essential that users update their installations as well.Found this article interesting? Follow us on Twitter and LinkedIn to read more exclusive content we post.SHARE

The council-led scheme aims to rejuvenate an existing council estate with a range of sustainable, low-carbon homes that are 100 per cent social rent.The masterplan, designed by north London practice Satish Jassal Architects, which set up 10 years ago, consists of 31 apartments, four wheelchair-accessible flats, 11 townhouses and, unusually, four intergenerational maisonette homes.Intergenerational housing is a new idea based on an old model: people of different ages living together and sharing their skills and time. In the past, this tended to be within extended families or tightly-knit local communities. But more recently, it has been introduced into some older peoples housing.AdvertisementThe 46 new units are spread over a cluster of red brick-clad blocks, which have been oriented to mirror the zigzag plan of the existing housing blocks. The central block is six storeys high while the townhouses are three storeys.The four intergenerational homes across Rowan Court aim to be flexible and to provide longevity for the scheme by serving the local community for generations to come.The masterplan has also enhanced the existing estate and public realm with a new public square, 96 cycle spaces, refuse stores, improved lighting, planting, paving and new trees.A newly overlooked mews street has created a secure link to public transport via an existing underpass. This is part of a strategy that aims to integrate the new-build development within the existing estate by prioritising pedestrian movement and social interaction.The development is car-free while over 81 per cent of the energy for the homes is produced onsite through renewable sources including PVs and air-source heat pumps.AdvertisementArchitects viewIt is a privilege to finalise this entirely socially rented housing project in collaboration with Haringey Council. Our design not only rejuvenates the existing estate but also integrates new homes and public spaces which will serve the community well into the future. This project stands as a testament to the potential of council-led housing development to create diverse, high-quality living options.Satish Jassal, director, Satish Jassal ArchitectsProject dataLocation Haringey, LondonStart on site March 2022Completion date March 2024Gross internal floor area 4,050m2Construction cost 12 millionConstruction cost per m2 3,000Client London Borough of HaringeyArchitect Satish Jassal ArchitectsMasterplanner Satish Jassal ArchitectsProject manager JJC AdvisoryEcologist Tom Haley EcologyLandscape consultant GroundworksSustainability consultant IceniPlanning consultant MC PlanningFire consultant BB7Transport consultant Scott White and HookinsAcoustic consultant AuriclSustainable urban drainage SwecoDaylight and sunlight consultant Right of Light ConsultingArboriculturist Arboricultural SolutionsStructural engineer Alan BaxterM&E consultant HydrockMain contractor (design and build) Formation Design and BuildEnvironmental performance dataPercentage of floor area with daylight factor >2% Not suppliedPercentage of floor area with daylight factor >5% Not suppliedOn-site energy generation 81%Annual mains water consumption 105 litres per person per dayAirtightness at 50Pa Not suppliedHeating and hot water load Not suppliedOperational energy Not suppliedTotal energy load Not suppliedOverall area-weighted U-value Not suppliedPredicted design life 60 yearsEmbodied carbon Not suppliedWhole-life carbon Not suppliedAnnual CO2 emissions Not supplied

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