In this article:See more ▼Post may contain affiliate links which give us commissions at no cost to you.If you’ve always been fascinated by the dark romanticism of medieval aesthetics, then Gothic Fonts are your bread and butter. There’s something utterly captivating about these dramatic typefaces that transport us straight back to ancient cathedrals, mysterious manuscripts, and candlelit chambers. Gothic fonts aren’t just about looking intimidating or spooky (though they certainly excel at that). These typefaces embody centuries of typographic heritage, carrying the weight of history in every dramatic flourish and angular stroke. From the ornate Black Letter scripts of medieval scribes to modern interpretations that blend gothic sensibilities with contemporary design, these fonts are storytelling powerhouses. Whether you’re designing for a metal band, crafting invitations for a Halloween party, or building a brand that needs serious gravitas, gothic fonts deliver that perfect blend of elegance and edge that’s impossible to ignore. In this deep dive, we’ll explore the most bewitching gothic fonts of 2025, uncover what makes these typefaces so mesmerizing, and discover how to wield their power in your own designs. So dim the lights, light a candle, and let’s embark on this typographic journey into the shadows! 👋 Psst... Did you know you can get unlimited downloads of 59,000+ fonts and millions of other creative assets for just $16.95/mo? Learn more »The Most Darkly Divine Gothic Fonts of 2025 Not all gothic fonts are created equal – some whisper dark secrets while others scream medieval drama. I’ve curated a collection of the most striking gothic typefaces that are making waves in 2025. Here are the fonts that will add serious mystique to your designs: Cattedrale – Gothic Blackletter Cattedrale is a striking Gothic blackletter font with decorative elements and symbols. It embodies the classic blackletter style with a modern twist, perfect for creating dramatic and impactful designs with a medieval flair.Shillow Gothic Font Shillow is a decorative Gothic font that blends traditional Gothic elements with modern aesthetics. Its unique character makes it ideal for creating eye-catching headlines, logos, and display text with a touch of elegance and mystery.Get 300+ Fonts for FREEEnter your email to download our 100% free "Font Lover's Bundle". For commercial & personal use. No royalties. No fees. No attribution. 100% free to use anywhere. Blacker Gothic Blacker Gothic is a serif font that combines Gothic and old-style elements. It offers a timeless look with a hint of antiquity, making it suitable for projects that require a classic yet sophisticated typographic approach.Killuminati – Gothic Type Killuminati is a bold and dramatic Gothic typeface with decorative and serif elements. This display font combines blackletter styling with modern flair, perfect for creating intense, attention-grabbing designs with a dark edge.Swordstone – Gothic Typeface Swordstone is a decorative Gothic typeface with a mystical touch. Its unique letterforms evoke a sense of fantasy and ancient lore, making it ideal for book covers, game titles, or any design requiring a touch of medieval magic.Grenosa Gothic Font Grenosa is a serif Gothic font with decorative Victorian influences. Its elegant and ornate design makes it perfect for creating sophisticated logos, headlines, or decorative text in projects that require a touch of historical charm.Crestfallen – Gothic Font Crestfallen is a sans-serif Gothic display font with a unique, edgy character. Its bold and slightly distressed appearance makes it ideal for creating impactful designs in music, fashion, or alternative culture-related projects.Andalucya – Gothic Typeface Andalucya is a decorative Gothic typeface with a unique and intricate design. Its elaborate letterforms and ornamental details make it perfect for creating stunning headlines, logos, or decorative text in projects that require a touch of exotic elegance.Blatters – Gothic Font Blatters is a serif Gothic font with a horror-inspired twist. Its eerie and unsettling design makes it perfect for creating chilling titles, posters, or text for horror-themed projects or Halloween designs.Groundead – Gothic Font Groundead is a serif Gothic font with decorative blackletter elements. Its bold and slightly grungy appearance makes it ideal for creating impactful display text, logos, or titles in alternative, rock, or metal-themed designs.Wild Gothic – Experimental Blackletter Wild Gothic is an experimental blackletter font with a condensed and edgy design. Its unique and unconventional letterforms make it perfect for creating bold, attention-grabbing headlines or logos in modern, urban-inspired projects.Gothic – Modern Blackletter Font Gothic is a modern take on the traditional blackletter style. Its clean lines and contemporary feel make it versatile for various design projects, from branding to editorial layouts, while still maintaining a Gothic essence.Demons Gothic Demons Gothic is a decorative blackletter font with a dark and ominous feel. Its intricate design and death-inspired elements make it perfect for creating sinister and intense visuals in horror, metal, or gothic-themed projects.Quispe – Gothic Font Quispe is a decorative Gothic font designed for logos and headlines. Its bold and distinctive character makes it ideal for creating eye-catching branding elements or impactful titles in various design contexts.Rohesia – Gothic Font Rohesia is an elegant and ornate Gothic font with decorative elements. Its intricate design and refined details make it perfect for creating sophisticated logos, invitations, or decorative text in luxury or high-end design projects.Raven Hell Gothic Raven Hell Gothic is a sans-serif decorative font with blackletter influences and a Halloween theme. Its spooky and playful design makes it ideal for creating fun and eerie text for Halloween-related projects or horror-themed designs.Lawson – Gothic Font Lawson is a decorative Gothic font designed for logos and headlines. Its strong and distinctive character makes it perfect for creating impactful branding elements or eye-catching titles in various design projects.Modirgan Gothic Display Font Modirgan is a Gothic display font with horror and fantasy influences. Its unique and otherworldly design makes it ideal for creating captivating titles, posters, or text for fantasy, sci-fi, or horror-themed projects.Gentry – Gothic Uncial Font Gentry is a decorative Gothic Uncial font designed for logos and headlines. Its blend of Gothic and Celtic influences creates a unique and elegant typeface perfect for projects requiring a touch of historical or mystical flair.Metal Gothic – Logo Font Metal Gothic is a serif decorative font designed for logos and display text. Its bold and edgy character makes it ideal for creating impactful designs in metal, rock, or alternative music-related projects.Gonaro – gothic and display typeface Gonaro is a free Gothic display typeface with a modern twist. Its unique design combines traditional Gothic elements with contemporary aesthetics, making it versatile for various creative projects requiring a bold and distinctive typeface.Gothic Rapsody – Blackletter Font Gothic Rapsody is a decorative blackletter font with a funky twist. Its playful and unconventional design makes it perfect for creating eye-catching headlines or logos in projects that blend Gothic style with modern, quirky aesthetics.Monastic – Vintage Gothic Font Monastic is a vintage-inspired Gothic font with ornate and modern elements. Its unique blend of old-world charm and contemporary design makes it ideal for creating sophisticated logos, headlines, or decorative text in various design contexts.Stackwin – Display Gothic Blackletter Typeface Stackwin is a modern Gothic blackletter display typeface. Its bold and contemporary interpretation of traditional blackletter style makes it perfect for creating striking headlines, logos, or titles in projects that require a blend of Gothic and modern aesthetics.Shadows – Vintage Gothic Blackletter Typeface Shadows is a serif decorative typeface that combines vintage Gothic and blackletter styles. Its unique blend of modern and retro elements makes it ideal for creating eye-catching designs in projects that require a somewhat spooky font with a Gothic twist.Big Fat Gothic Blackletter Typeface Big Fat Gothic is a bold and imposing blackletter typeface. Its thick, dramatic strokes and traditional gangster old english style make it perfect for creating powerful headlines, logos, or titles in projects that require a strong, authoritative presence.Blackey Bold Decorative Gothic Blackletter Font Blackey is a bold, serif Gothic blackletter font with decorative elements. Its strong character and intricate details make it ideal for creating impactful headlines, logos, or titles in projects that require a blend of traditional and modern Gothic aesthetics. There are more old english fonts here.Old Charlotte – Bold Decorative Gothic Font Old Charlotte is a sans-serif decorative Gothic font with blackletter influences. Its bold and distinctive design makes it perfect for creating eye-catching headlines, logos, or display text in projects that require a strong Gothic presence with a modern twist.Gothic Byte – Blackletter 8Bit Typeface Gothic Byte is a unique blackletter typeface with an 8-bit pixel art style. Its innovative blend of Gothic and retro video game aesthetics makes it ideal for creating eye-catching designs in gaming, tech, or nostalgia-themed projects.Cambridge – Bold Decorative Gothic Font Cambridge is a serif decorative Gothic font with blackletter influences. Its bold and elegant design makes it perfect for creating sophisticated headlines, logos, or titles in projects that require a blend of traditional Gothic style and modern refinement. What Gives Gothic Fonts Their Mysterious Allure? Gothic fonts derive their haunting beauty from several key characteristics that set them apart from other typeface families: Angular, Sharp Letterforms The most defining feature of gothic fonts is their angular construction. Unlike the smooth curves of humanist typefaces, gothic fonts embrace sharp angles, pointed serifs, and dramatic contrasts. These harsh edges create an immediate sense of drama and formality that feels both ancient and powerful.Heavy, Dark Strokes Gothic fonts are known for their bold, dark appearance. The thick strokes dominate the white space, creating a dense, imposing texture on the page. This heaviness gives gothic fonts their famous “blackletter” appearance and contributes to their serious, authoritative presence.Ornate Details and Flourishes Many gothic fonts feature intricate decorative elements – from elaborate swashes to ornamental capitals that look like they were lifted from illuminated manuscripts. These details add layers of visual interest and enhance the font’s connection to medieval craftsmanship.Vertical Emphasis Gothic letterforms tend to be compressed horizontally and stretched vertically, creating a tall, narrow appearance. This vertical emphasis adds to their formal, cathedral-like grandeur and makes them particularly striking in headlines and titles.Where Gothic Fonts Cast Their Spell Gothic fonts possess a unique versatility that might surprise you. While they’re natural choices for certain niches, their dramatic flair can elevate designs across multiple industries: Music Industry Metal bands, gothic rock groups, and classical orchestras all turn to gothic fonts for their album covers, merchandise, and branding. These typefaces perfectly capture the intensity and drama that defines these musical genres.Gaming and Entertainment Fantasy games, horror films, and medieval-themed entertainment rely heavily on gothic fonts to establish atmosphere. From video game logos to movie posters, these fonts immediately signal adventure, mystery, and otherworldly experiences.Luxury Branding High-end brands often incorporate gothic elements to convey exclusivity, tradition, and craftsmanship. Think luxury watches, premium spirits, and boutique fashion houses that want to emphasize their heritage and sophistication.Event Design Gothic fonts are perfect for Halloween parties, medieval-themed weddings, academic ceremonies, and any event that calls for drama and elegance. They transform ordinary invitations into memorable experiences.Publishing and Literature Book covers for fantasy novels, horror stories, and historical fiction often feature gothic fonts. These typefaces help genre books stand out on shelves and immediately communicate their content to readers.When to Avoid the Gothic Touch While gothic fonts are undeniably powerful, they’re not suitable for every design context. Here’s when you might want to consider alternatives: Modern Tech Brands Unless you’re intentionally going for a retro-tech aesthetic, gothic fonts can feel outdated for contemporary technology companies. Clean, modern sans-serifs typically better reflect innovation and forward-thinking values.Children’s Products Gothic fonts can appear scary or intimidating to young audiences. For children’s books, toys, or educational materials, friendlier, more approachable typefaces usually work better.Medical and Healthcare In medical contexts, gothic fonts might undermine the sense of trust and cleanliness that patients expect. Clean, professional typefaces better convey competence and care.Fast-Casual Dining While gothic fonts work wonderfully for upscale restaurants or themed establishments, they might feel too formal or dramatic for casual dining experiences where approachability is key.Choosing the Perfect Gothic Font for Your Project Selecting the right gothic font requires careful consideration of several factors: Historical Accuracy vs. Modern Interpretation Decide whether you need authentic medieval character or a contemporary take on gothic style. Traditional blackletter fonts offer historical accuracy, while modern gothic interpretations provide more flexibility and readability.Legibility Requirements Consider how much text you’ll be setting in the gothic font. Ornate gothic typefaces work beautifully for headlines and logos but can become difficult to read in large blocks of text.Cultural Sensitivity Be aware that certain gothic fonts, particularly German blackletter styles, carry historical associations that might not be appropriate for all contexts. Choose fonts that align with your project’s cultural sensitivity requirements.Brand Personality Match Ensure the gothic font aligns with your brand’s personality. A playful, modern brand might benefit from a quirky gothic interpretation, while a luxury brand might prefer a more refined, traditional approach.Gothic Font Alternatives That Capture the Magic If full gothic fonts feel too intense for your project, consider these alternatives that capture gothic elements while remaining more approachable: Magic Fonts Typefaces like Cinzel or Cormorant Garamond incorporate gothic-inspired details while maintaining excellent readability. These fonts offer a subtle nod to gothic style without overwhelming the design. You can find all our magic fonts here. Modern Gothic Sans-Serifs Fonts like Impact or Bebas Neue capture the vertical emphasis and dramatic presence of gothic fonts in a clean, contemporary package. Decorative Display Fonts For special applications, decorative fonts with medieval or mystical themes can provide gothic atmosphere without the formality of traditional blackletter typefaces. The Future of Gothic Typography As we move deeper into 2025, gothic fonts continue to evolve. Digital design tools allow for more sophisticated interpretations of traditional forms, while contemporary designers push the boundaries of what gothic can be. We’re seeing increased interest in variable gothic fonts that allow designers to adjust weight, width, and ornamental details on the fly. This flexibility makes gothic fonts more versatile than ever before. The rise of dark mode interfaces has also given gothic fonts new relevance in digital design, where their dramatic contrast works particularly well against dark backgrounds. Common Gothic Font Questions Answered What’s the difference between gothic and blackletter fonts? Blackletter is a specific category within the broader gothic font family. While all blackletter fonts are gothic, not all gothic fonts are blackletter. Blackletter specifically refers to the dense, angular scripts used in medieval manuscripts.Are gothic fonts hard to read? Traditional gothic fonts can be challenging to read in large amounts, especially for modern audiences. However, contemporary gothic interpretations often improve readability while maintaining the style’s dramatic impact.Can I use gothic fonts for body text? Generally, gothic fonts work best for headlines, logos, and short passages. For body text, consider using a more readable font and reserve gothic styling for emphasis.What’s the most versatile gothic font? Fonts like Old English Text or modern interpretations such as Cinzel offer good versatility, balancing gothic character with practical readability across different applications.Embracing the Dark Side of Typography Gothic fonts offer designers a direct connection to centuries of typographic tradition and artistic expression. They remind us that type can be more than just a vessel for words – it can evoke emotions, tell stories, and transport viewers to different times and places. Whether you’re crafting a brand identity that demands attention, designing an invitation that needs to feel special, or creating a poster that must stop viewers in their tracks, gothic fonts provide a powerful tool for visual storytelling. The key to successfully using gothic fonts lies in understanding their history, respecting their power, and applying them thoughtfully. When used with intention and restraint, these dramatic typefaces can transform ordinary designs into extraordinary experiences. So go ahead, embrace the gothic aesthetic in your next project. Let these fonts whisper ancient secrets and cast their typographic spells. In a world of safe, sanitized design choices, sometimes what you need is a little medieval magic to make your work truly unforgettable.

Cases A New Best: Fractal Meshify 3 Case Review, Thermal Benchmarks, & NoiseMay 15, 2025Last Updated: 2025-05-15We analyze the Fractal Design Meshify 3’s design, specs, build quality, LEDs, and thermalsThe HighlightsThe Meshify 3 comes with 3 fans and focuses on looksAt its price category, there’s a lot of stiff competitionOverall, we like the caseOriginal MSRP: $140 to $220Release Date: May 2025Table of ContentsAutoTOC Our fully custom 3D Emblem Glasses celebrate our 15th Anniversary! We hand-assemble these on the East Coast in the US with a metal badge, strong adhesive, and high-quality pint glass. They pair excellently with our 3D 'Debug' Drink Coasters. Purchases keep us ad-free and directly support our consumer-focused reviews!IntroToday we’re reviewing the Fractal Meshify 3. It ranges from $140 to $220 depending on the level of “integrated atmospheric lighting” you want, but to be fair to Fractal, it does look good with the angular mesh front panel. The good news upfront with this review is that we actually like the case overall.Editor's note: This was originally published on May 15, 2025 as a video. This content has been adapted to written format for this article and is unchanged from the original publication.CreditsTest Lead, Host, WritingSteve BurkeTesting, WritingPatrick LathanCamera, Video EditingVitalii MakhnovetsCameraTim PhetdaraAndrew ColemanWriting, Web EditingJimmy ThangFractal's has added some interesting new features: an air guide in front of the PSU shroud that genuinely helps GPU thermals in our testing, excellent cable aligner clips, and a bizarre PSU filter that blends seamlessly into the side of the case.This case was going to launch months ago, but was quietly pulled from shelves by Fractal at the last minute because the PCIe slots were too tight. Multiple reviewers, including us, noticed that these PCIe slots were too tight for GPUs to slot properly, an issue we had recorded in our notes for the review and were about to film when Fractal sent an email that it was halting the launch. Fractal manually reworked this, meaning someone went through all the cases and shaved them down.Originally, Fractal would have launched just before the worst of the tariffs, but now is launching into a far more expensive import situation. Fractal says that, for now, its MSRP is unchanged.But we’re here to review the case. We have a 3-hour documentary about the tariffs’ impact.The case comes with 3 fans and clearly has a focus on looks with its lighting and front panel design, but also manages to make a number of mechanical choices that affect cooling.Let’s get into the Meshify 3 review.Meshify 3 Ambience Pro RGB OverviewThis is Fractal's third generation of Meshify cases, starting with the Meshify 3 and the larger Meshify 3 XL. We're reviewing the shallow front-to-back Meshify 3 today, which is the size equivalent of the first generation's Meshify C and the second generation's Meshify 2 Compact (watch our review). The Meshify C (watch our review) was $90 at launch in 2017, followed later by the Meshify 2 (watch our review) at $110.The Meshify 3 is launching from $140-$220 (depending on SKU). It’s not distant from Fractal’s Torrent case. We liked that case. It’s priced at around $190 to $230. The increased Meshify series cost goes towards new features.The flashiest new feature is the "integrated atmospheric lighting" in the top-tier Ambience Pro RGB SKU. Fractal also has committed to proprietary connectors for these cases, which we’re not thrilled about. Fractal additionally has a web tool for the new Adjust Pro fan and RGB hub.The cases are sold at $140 for 3x 140mm fans without LEDs, $160 for 3x 14mm RGB fans using proprietary connectors, and $220 for 3x RGB fans with a lighting control hub and additional case lighting around the front panel, shroud, and power button.Meshify 3 Ambience Pro RGB SpecsMeshify 3 TG3.5"/2.5" mountsUp to 2x HDD or 4x SSDDedicated 2.5" mounts2 (6 total)5.25" drive bays0Expansion slots7Motherboard compatibilityE-ATX (max 277 mm), ATX, mATX, Mini-ITXPower supply typeATXFront interface1x USB 3.2 Gen 2x2 Type-C 20Gbps2x USB 3.0 5Gbps1x Combined Mic/AudioTotal fan mounts6x 120 mm or 5x 140 mm + 1x 120mmFront fan mounts3x 120/140 mm (3x Momentum 140 mm PWM/RGB Included)Top fan mounts2x 120/140 mmRear fan mounts1x 120 mmSide fan mountsN/ABottom fan mountsN/ADust filtersPSUFront radiatorUp to 280/360 mm (max 155 mm width)Top radiatorUp to 280/240 mm (max 148 mm width)Rear radiator120 mm (max 128 mm width)Bottom radiatorN/APSU max length180 mmGPU max length349 mmGPU max height176 mm (7 slot) including cablesCPU cooler max height173 mmCable routing space34.5 mmCable coverYesCable organizers3x Cable Aligners, 3x Internal Straps, 3x Rear External StrapsCaptive thumbscrewsTop Rad. Bracket, PSU BracketTool-less push-to-lockSide Panels, Bottom Filter, Front Panel, Top Panel, PSU BracketCase MaterialSteelLeft side panelTempered GlassRight side panelIndustrial SteelCase dimensions (LxWxH)423 x 229 x 507 mmCase dimensions w/o feet/protrusions/screws423 x 229 x 483 mmNet weight8.0 kgPackage dimensions (LxWxH)596 x 350 x 550 mmGross weight10.3 kgSpecs copied from manufacturer materials, please read review for our own measurements and opinionsThe BuildLet’s get into the build quality and features.Some of the exterior is similar to the Torrent, especially the way the top panel slides off. Unlike the Torrent, the top panel is mesh in the Meshify 3, although only the central portion is actually open due to the thick plastic frame underneath. The front panel pops off from the bottom like the North cases, and the top edge (in the Ambience Pro RGB) has pogo pins to connect the ambient front panel lighting.There are three plastic "cable aligners" that can be snapped over the main cable channel. We found them to be well-placed and surprisingly sturdy even with large bundles of power supply cables wedged behind them. Our only complaint is that they're keyed for no discernible reason other than preventing users from flipping the Fractal logo upside-down. The cable management space behind the motherboard is a uniform depth at just over 3cm across the entire case. There's a massive cutout above the motherboard that runs its entire length, although the cutout at the bottom is undersized and difficult to use when an ATX board is installed. Overall, cable management is above average thanks to the cable aligners and the amount of space, with some velcro straps on the back for exterior cable management. The PSU shroud terminates in a plastic "air guide" angled up towards the GPU. It reminds us a little of the NZXT toilet bowl fan from the 2022 H5 Flow (watch our review), but more so the extremely similar "PSU optional cover plate" from Corsair's old 5000D Airflow (watch our review). The 5000D Airflow's single intake fan wasn't positioned to make that part matter, though, whereas the Meshify 3's intake-heavy configuration will actually benefit.The only discrete dust filter in the case is for the PSU. It ejects from the side, which is always a plus for ease of removal, but it's also built into the leg of the case so that there's no externally visible handle. This is completely unnecessary, but it's one of those small features that shows the care that was put into the case's appearance and great attention to detail.Drives can be mounted to a set of adjustable brackets behind the motherboard tray; Fractal has provided a complicated compatibility matrix, but basically, you can either fit up to 2x 3.5" drives or 4x 2.5" drives. An additional 2x 2.5" drives can be attached directly to the floor of the case underneath the air guide, but if you use those slots, you may want to leave the air guide out to make cables accessible.The front of the case can fit either 3x 120mm fans or 3x 140mm fans. The rails rotate to switch between the two sizes and there are cutouts at specific heights for each individual fan, which means the rails don't obstruct the fans at all, but also there's little freedom to reposition fans or mix and match different sizes. All Meshify 3 SKUs ship with three front fans preinstalled, so this is less of an issue than it would be on a bare chassis. When fans are installed on the rails, the fans and rails can be removed as a single unit by undoing two screws, which is awesome.The removable top bracket is extremely easy to work with and fits radiators up to 280mm with plenty of room. Simultaneously installing a 360mm radiator at the front of the case would technically be possible using standard 30mm thick rads, but without much room left for fittings, fans, or thicker radiators, so we don't recommend it. Fractal notes that the front mount is compatible with 360mm (3x120) radiators of up to 420mm total length with the air guide or 445mm without it. Critically though, this does not mean support for 420mm (3x140) radiators.If any radiators are installed at the front of the case, the cable bar has to be shifted back, which makes it harder to route power cables. In addition, maximum GPU length in the Meshify 3 is already only 349mm, and installing a front radiator directly eats that clearance. We recommend relying on the top radiator slot or moving up to the Meshify 3 XL if you really need space for liquid cooling and especially for longer cards.Along the same lines, Fractal claims compatibility with so-called E-ATX boards up to 277mm wide, but that describes the maximum size that can be installed without completely blocking cable cutouts. Realistically, if you want to install anything even slightly larger than ATX, you should be looking at the Meshify 3 XL instead. Even with a normal ATX board, we shifted the cable bar all the way forward to leave space for the 24-pin power cable.As a finer detail point, we’re happy to see that Fractal has finally compromised by adding screw holes to the plastic tabs on the side panels. If you want to add some extra security while moving your case, you can put screws through the tabs to lock them down.The fans and LEDs are complicated and confusing, so that’ll require a whole section -- but we’ll get into the thermal testing first.Meshify 3 Ambience Pro RGB Thermals Grab a GN15 Large Anti-Static Modmat to celebrate our 15th Anniversary and for a high-quality PC building work surface. The Modmat features useful PC building diagrams and is anti-static conductive. Purchases directly fund our work! (or consider a direct donation or a Patreon contribution!)Fractal's review guide claims that the RGB fans are quieter, lower CFM, but higher static pressure (at max speed) than the non-RGB versions of the same fans. Our thermal results with the stock fans are representative of the RGB case SKUs, though any major physical reasons for performance would still be reflected. The standardized fan test is representative of the Meshify 3 in general.For reasons we’ll explain in the fan control section, we had no way to skip the fan hub and connect the fans directly to the motherboard as we usually would for testing. We validated that the fans reached their rated max speed of 1,800RPM +/- 10% with a laser tachometer. However, the tach signal sent back by the Fractal Adjust Pro hub doesn't line up with standard 4-pole fan behavior: HWiNFO misreports 2295 RPM when the fans are really spinning at just over 1,800 RPM in reality. Fractal's software accounts for this and reports RPM accurately.As for comparison cases, we’ll mostly focus on the Antec C8 ARGB (read our review) and Antec Flux Pro (read our review) as close matches. The closest match in appearance and function may be Fractal's own Torrent Compact RGB. We haven't added the Torrent Compact back to our charts since our testing overhaul, but in our review, it performed similarly to the larger original Torrent. That is in our charts, so we can use that as a rough equivalent.We have plenty of other cases on the charts for your own comparisons. Let’s get into the data.CPU Full Load Thermals - Noise-NormalizedWe’ll start with noise-normalized thermals. We use our hemi-anechoic chamber that we spent $250,000 building for validating the noise levels, which allows us to heavily control the noise floor and get super accurate capture.This is the chart. The Fractal Meshify 3 dominates here, planting itself as the new chart leader and within error of the prior leaders. The Meshify 3's all-core average of 40 degrees Celsius over ambient and 44 degrees for the P-cores is significantly better than previous efforts from the Meshify 2 Compact (watch our review) at 48 degrees average and the Meshify C at 54. Those two cases shared a basic design. The Meshify 3 is more of a departure; Fractal has added an airflow guide to the bottom of the case, the stock fans are higher performance, and all three stock fans are installed in the front of the case. That's an arrangement that's worked well for CPU cooling in the North XL (read our review) and Torrent using our test bench, and evidently it works extremely well in the Meshify 3, which is now the coolest case on the chart. The Torrent was a little warmer than the Meshify 3 at 42 degrees above ambient, while the Meshify 3 is instead tied with the previous best results from the Lian Li Lancool 216 (watch our review) and Lancool 207 (read our review). The Antec Flux Pro is a case that Fractal is likely specifically targeting for competition and, like the Lian Li cases, it's within one degree of the Meshify 3. This test is a weak point for the Antec C8 ARGB, which averaged 50 degrees due to its bottom intake layout.GPU Full Load Thermals - Noise-NormalizedHere’s the chart for GPU thermals when noise-normalized.GPU cooling performance in the Meshify 3 was also strong. The equivalent cases from the previous Meshify generations didn't have particularly strong stock performance, with the Meshify 2 Compact averaging 52 degrees above ambient for the GPU and the Meshify C averaging 57. This is still noise-normalized, so it's not purely a matter of more powerful fans in the Meshify 3, which averaged 43 degrees for the GPU and 46 for the GPU memory. Judging by the performance of the North XL and the Torrent here, it seems possible that the Meshify 3's air guide actually does do something. The North XL and its conventional (although ventilated) full-length PSU shroud averaged 44-45 degrees for the GPU depending on the chosen side panel, while the Torrent with its top-mounted PSU and complete lack of a shroud at the bottom of the case averaged 40 degrees. The Meshify 3 with its shroud and air guide averaged 43 degrees, right in the middle. There are more variables at work here, though, so we need another test to know for sure.As for the other highlighted competitors, the Antec C8 ARGB averaged 42 degrees and the Flux Pro averaged 41. Technically they both beat the Meshify 3's 43 degree average, but they're all among the best performing results on this chart.GPU Full Load Thermals - Full SpeedAs part of our full speed testing, we ran a test pass with a cardboard box extension taped onto the end of the PSU shroud to bring it up flush with the front intake fans. This test is at full speed case fans and controlled CPU and GPU fans.Without this extension, the GPU in the Meshify 3 averaged 41 degrees above ambient versus 45 degrees with it. That's a significant increase with the extension, and it shows that it made sense to shorten the shroud and angle it up like a skate ramp. Adding the extension also raised noise levels from a baseline of 37.5 dBA to 38.7 dBA, which we can only really confidently state is a real difference because of our investments in the hemi-anechoic chamber and our test equipment. This is a real change. Although hardly a detectable difference to the human ear, it is a real one and some people might notice it. Fractal’s new shroud design is superior to a square-edge one both thermally and acoustically.Since we've already seen that the Meshify 3 outperforms its predecessors when noise-normalized, it's no surprise at all that it outperforms them when its 1,800 RPM stock fans are maxed out. 37.5 dBA for the Meshify 3 is definitely louder than the 31-32 dBA levels from the Meshify C and Meshify 2 Compact, but thermal performance isn't even close, with the Meshify C only able to maintain GPU temperatures at 56 degrees above ambient. The C8 ARGB tied the Meshify 3's GPU temperature in this test, which is impressive for the Meshify 3 given that the C8 ARGB has bottom intake fans pointed directly into the GPU. The stock Flux Pro and Torrent remain chart toppers at 38 degrees and 39 degrees respectively thanks to their overkill stock fans; this is also evident from the noise levels, with the Torrent's powerful fans pushing it to a maximum of 42.3 dBA to the stock Meshify 3's 37.5 dBA.GPU Full Load Thermals - Standardized FansStandardized fan testing is next.All of the Meshify 3 SKUs ship with fans, so we're just going to use the standardized fan test as an opportunity to compare directly against the previous Meshify generations when they have the same loadout. The Meshify 3 has three defined 140mm fan mounting locations at the front, so rather than sticking our two 140mm intake fans somewhere in the middle, we were forced to pick either the upper two slots or the lower two.The Meshify C and Meshify 2 Compact both had GPU averages of 47 degrees above ambient, while the Meshify 3 literally bookended the chart at 41 degrees with the fans in the lower slots and 53 degrees in the upper ones. If you alter the stock fan configuration, be sure to at least keep one fan in the bottom slot at the front of the case.CPU Full Load Thermals - Standardized FansOn to CPU thermals while using standardized fans: There wasn't much difference in CPU thermals between the upper and lower slot tests; although the upper slot technically did better with an all-core average of 39 degrees, the lower slot arrangement is preferable due to the GPU thermals we just discussed. The Meshify C and Meshify 2 Compact tied at 41 degrees all-core, not that far from the Meshify 3's 40 degree average.VRM & RAM Full Load Thermals - Noise-NormalizedReturning to the noise-normalized results, the Meshify 3 tied the Flux Pro for the best VRM temperature on the chart at 27 degrees above ambient. That's significantly better than its predecessors at 35 degrees for the Meshify 2 Compact and 39 for the Meshify C. The Torrent averaged 29 degrees and the C8 ARGB with its bottom intake layout averaged 33. The ventilated case roof and airflow definitely help here.The SPD hub (or the RAM temperature average) was better, with the Meshify 3's average of 20 degrees above ambient beating all other stock case results on the chart. The Torrent at 21 degrees and Flux Pro at 22 were also high performers, while the C8 ARGB's more GPU-focused cooling left it with a warmer 24 degree average.Fans and LEDsAnd now we’re back to the topic of fans and LEDs.The Momentum RGB fans connect through daisy-chained USB Type-C connectors. Fractal describes the connector as "Proprietary USB-C," meaning that the connectors are just USB-shaped out of convenience; the fans are NOT USB devices. This part confused us, so here's a breakdown:The regular Meshify 3's fans use regular 4-pin PWM fan connectorsThe Meshify 3 RGB's fans use Fractal proprietary connectors, but they're pre-routed with an adapter that terminates in a regular 4-pin fan connector and a 3-pin ARGB connector, so the fans can be connected to a normal motherboard out-of-the-boxThe Meshify 3 Ambience Pro RGB has the same fans as the other RGB SKU, but they're pre-routed to Fractal's Adjust Pro hub. A "legacy splitter" cable is included for OUTput so that regular ARGB devices can be daisy-chained onto Fractal's devices, but the INput adapter cable from the Meshify 3 RGB is not included. In other words, if you get the Ambience Pro RGB, you're using the hub (or waiting for Fractal to sell an adapter cable separately)The Adjust Pro Hub can be controlled through a web tool or Microsoft's Dynamic Lighting feature. Fractal can get away with using a simple web app because the Pro Hub is just a USB device, so it doesn't need low-level access to control the motherboard's fan and RGB headers. There’s no launch-on-startup bloatware and the settings are saved locally to the hub. Currently, the app claims to be fully compatible with Chrome, Opera, and Edge (but not Firefox). A sustained internet connection isn't required for this. We were glad to see Dynamic Lighting compatibility, even if it's not perfect. For instance, if you enable Dynamic Lighting, it breaks Fractal's tool, and if you haven't activated Windows then you can't disable Dynamic Lighting without editing the registry.Fractal's software has a selection of prefab lighting patterns to show off the gen 2 lighting, but the default Northern Lights pattern may be our favorite. The indirect lighting around the edges of the front panel and across the PSU shroud are mostly striking in a dark room. It's unfortunate that such a big part of the case's appeal is limited to the $220 version.Meshify 3 Ambience Pro RGB Conclusion Visit our Patreon page to contribute a few dollars toward this website's operation (or consider a direct donation or buying something from our GN Store!) Additionally, when you purchase through links to retailers on our site, we may earn a small affiliate commission.We like the Meshify 3 overall, but we're torn on several points. As an immediate positive, as reviewers who don’t normally comment a whole lot about looks, we do think they did well to pull off the LEDs and front panel on the Meshify 3. Fractal has consistently done well to execute on this style.As for the more difficult points: First off, the Meshify C launched at $90 and the Meshify 2 Compact at $110. Those weren't the lowest prices in context. The Meshify C, however, was on the affordable end of the scale even for that time. Given that Fractal picked the Meshify 3 MSRPs well before the new tariffs, we believe there's a good chance they'll go up. The Meshify 3 isn't in the medium-budget tier you might assume based on the history of the series. If you're looking for cases in that vein, Lian Li has options like the Lancool 217 (watch our coverage), while Antec has some equivalents to the Meshify 3 RGB like the C8 ARGB and Flux Pro.That's not to say that the Meshify 3 isn't worth the money, just that it’s embattled on all sides. There are a lot of options in this price category, which is good for consumers. The build quality is on par with what we expect from Fractal based on the last few years' worth of cases like the North (watch our review) and Torrent. It’s built well. Thermal performance was extremely good, and although the specs are different for the non-RGB fans as we've explained, we can assume that the performance is also extremely good for the non-RGB case variants. Based on that, the $140 and $160 options are the most competitive.As for the $220 Ambience Pro RGB, it's basically a $60-$80 upcharge for lighting, but we really like that lighting. That is, however, a big price jump. If you're considering the Ambience Pro RGB with the extra cost for the lighting, you should be comparing it to other flagship showy cases like the HAVN HS420 (read our review) or HYTE Y70 (read our review) (if you can buy one as they can be difficult to find in the US due to the tariffs). You should also look through Fractal's documentation carefully to make sure you like the RGB ecosystem of software and connectors before you commit.You can check out the competition like the Flux Pro, C8, and Corsair’s FRAME 4000D (read our review). We have more reviews coming up, but overall, we like Fractal’s new case.

Casa CG / Alventosa Morell ArquitectesSave this picture!© Adria GoulàHouses•Creixell, Spain Architects: Alventosa Morell Arquitectes Area Area of this architecture project Area:  2130 m² Year Completion year of this architecture project Year:  2024 Photographs Photographs:Adria Goulà Manufacturers Brands with products used in this architecture project Manufacturers:  Barnacork, Jaume Olivé Fusteria, METCOR Lead Architects: Marc Alventosa, Xavier Morell More SpecsLess Specs Save this picture! Text description provided by the architects. Casa CG was designed for a couple seeking a change. The clients previously lived in a large house and wanted to build a smaller home that felt right for two people. Entirely clad in cork, Casa CG merges with its surroundings while being thermally efficient and making the most of a modest budget.Save this picture!Save this picture!Save this picture!Save this picture!We designed a compact house with a rectangular floor plan and an asymmetrical roof. This allowed us to gain square meters for a multi-purpose space at a lower cost by increasing the height of only one-half of the house to accommodate a mezzanine. On the ground floor, the kitchen, living, and dining areas are grouped along an open space with windows on three sides. A bedroom and a bathroom are located on a more intimate scale below the mezzanine.Save this picture!Thin wooden partitions on the interior soften the concrete structure and maximize the usable space. From the outside, Casa CG blends with the tones of the surrounding pine forest thanks to its cork cladding, which also increases the house's thermal inertia.Save this picture! Project gallerySee allShow less About this office MaterialsWoodConcreteMaterials and TagsPublished on May 15, 2025Cite: "Casa CG / Alventosa Morell Arquitectes " 15 May 2025. ArchDaily. Accessed . <https://www.archdaily.com/1030099/casa-cg-alventosa-morell-arquitectes&gt ISSN 0719-8884Save世界上最受欢迎的建筑网站现已推出你的母语版本!想浏览ArchDaily中国吗?是否 You've started following your first account!Did you know?You'll now receive updates based on what you follow! Personalize your stream and start following your favorite authors, offices and users.Go to my stream

Today, MarkTechPost had the pleasure of interviewing Joey Conway from NVIDIA to discuss their exciting work on open-source large language models, including Llama Nemotron Ultra & Parakeet. Highlights from the interview: NVIDIA’s Open Source Powerhouse: Discover how NVIDIA is pushing the boundaries of open-source AI with the release of cutting-edge models like Llama Nemotron Ultra and Parakeet TDT. Llama Nemotron Ultra: Smaller Size, Giant Performance: Learn how NVIDIA achieved on-par performance with models twice the size, enabling deployment on a single GPU node. Explore their innovative FFN fusion technique for significant speedups. Reasoning on Demand: Uncover the unique “reasoning on/off” feature in Llama Nemotron Ultra, offering unprecedented control for production deployments and cost optimization. Revolutionary Speech Recognition with Parakeet TDT: Dive into NVIDIA’s state-of-the-art ASR model that transcribes one hour of audio in one second with only a 6% word error rate – 50 times faster than other open-source alternatives! The “How”: Architectural Innovations: Get insights into the advanced architectures and optimizations behind these models, including FFN fusion, limited context attention, and the Token Duration Transducer (TDT)  Democratizing AI with Open Data: Learn about NVIDIA’s commitment to the open-source community through the release of model weights and massive, high-quality datasets for both language and speech. Future Directions: Get a sneak peek into NVIDIA’s plans for multilingual support, even smaller edge-optimized models, and advancements in real-time streaming for speech recognition. Production-Ready AI: Understand how these models are designed with real-world deployment challenges in mind, focusing on accuracy, efficiency, and cost-effectiveness. Jean-Marc Mommessin: Joey, welcome to Marketechpost! We’re thrilled to have you here and to delve into the impressive open-source models NVIDIA has been releasing. To start, could you please introduce yourself and your role at NVIDIA? Joey Conway: Hi Jean-Marc, it’s great to be here. I’m Joey Conway, and I work in product management for some of the deep learning software at NVIDIA. Our team focuses on large language models like Nemotron and Llama Nemotron, as well as text-to-speech models such as Parakeet. Jean-Marc Mommessin: Wonderful. And you’ve been at NVIDIA for over seven years now, witnessing significant waves of innovation in AI. Let’s talk about your recent release, Llama Nemotron Ultra, a 253 billion parameter model. From what we’ve seen, it delivers performance on par with models like Llama 405B and DeepSeek R1, which are about twice its size. Remarkably, it can run on a single 8x H100 node. What else can you tell us about Llama Nemotron Ultra and what makes it so impressive? Joey Conway: We’re big believers in the open-source community and the fantastic work being done there. With Llama Nemotron, our goal was to build upon the existing foundations, particularly Llama, for which we greatly appreciate Meta’s contributions. We also observed significant progress in reasoning within the open community earlier this year. Inspired by this, we wanted to contribute and see how we could enhance Llama, especially for enterprise use cases. Our focus was primarily on improving reasoning capabilities and agentic tasks like tool calling and chat. We aimed to take the strengths of the open-source community, enhance them, and then contribute those improvements back. Jean-Marc Mommessin: Did you identify specific gaps in existing models that you aimed to address? You mentioned reasoning, but could you provide an example or two of enterprise agentic tasks where you felt there were shortcomings that Llama Nemotron Ultra overcomes? Joey Conway : Yes, I think looking back to the beginning of the year, a key challenge in enterprise deployments was handling complex queries requiring significant thought and reflection. These could be multi-step processes or involve substantial calculations and the use of external tools. At that time, there weren’t many strong open-weight models capable of robust reasoning. The progress we’ve seen in the last few months in this area is very encouraging. Another critical aspect for enterprises is the ability to accurately call APIs and closely follow instructions in user queries. We wanted to ensure that while we focused on improving reasoning, we didn’t compromise these essential production-level capabilities. Furthermore, we often noticed that when both reasoning and instruction following were well-addressed, they typically resided in separate models. Our aim was to simplify this by creating a single model that excels in both. This was the landscape we observed when we started this project around January and February. Jean-Marc Mommessin: That makes perfect sense and aligns with what we’re seeing in the industry as well. Now, let’s dive into the “how.” Your paper mentions FFN fusion as a key optimization. Could you elaborate on this technique, starting with a high-level explanation? Joey Conway: Absolutely. Our focus on optimization stemmed from the realization that deploying state-of-the-art models often requires a significant deployment footprint. We wanted to optimize this to fit within more common GPU setups. We explored various techniques, including our Puzzle neural architecture search. For dense transformer models, particularly those in the Llama family, we discovered a way to reduce or eliminate redundant attention layers. This process aligned the feed-forward network (FFN) layers in a sequence, allowing us to explore fusion methods. Our fundamental goal on the GPU is to maximize parallel execution. Fusing these aligned FFN layers enables greater parallel computation than was previously possible. By removing redundant layers, we found opportunities to essentially merge or fuse the remaining ones. This is a key example of how we tackle the challenges of running these models at scale. Importantly, this technique often yields greater improvements with larger models, which was beneficial for our Ultra model based on Meta’s Llama 3.1 -405B. Jean-Marc Mommessin: And this FFN fusion significantly improves the model’s throughput, achieving notable speedups. If I recall correctly, it’s in the range of 3 to 5x for the Ultra model? Joey Conway: That’s right, the speedups for the Ultra model are in that range. Additionally, by reducing the model’s size in terms of weights, we also lowered its memory footprint. This allowed us to utilize a larger KV cache. For Llama Nemotron Ultra, we could fit it onto a 8x H100 80GB setup, which is quite significant as it fits within common node configurations. So, FFN fusion provided both a substantial compute speedup and a reduction in memory usage, enabling us to handle larger context lengths. These are very exciting outcomes for us. Jean-Marc Mommessin: Let’s switch gears to data curation. AI data is crucial, and your training pipeline seems very sophisticated. You touched on “instruction following” earlier. Could you elaborate on your data curation process and how you ensured high-quality data, especially considering you leveraged other models in the process? Image source: NVIDIA Joey Conway: Transparency and openness were key in our approach. We wanted to share as much as possible about our data, techniques, and tooling so the community could understand and even use it themselves. Our primary goal with data curation was to improve accuracy across several key domains, including reasoning tasks like math and coding, as well as non-reasoning tasks like tool calling, instruction following, and chat. Our strategy involved curating specific datasets to enhance performance in these areas. Within our supervised fine-tuning process, we differentiated between “reasoning on” and “reasoning off” scenarios. For example, in math and coding, we curated data for simple questions that don’t require complex reasoning, as well as more intricate problems that do. This helps the model learn when and how to apply reasoning. A key part of this process was leveraging high-quality models from the community as “experts” in specific domains. For instance, we used DeepSeek R-1 extensively for reasoning-intensive math and coding tasks. For non-reasoning tasks like basic math, coding, chat, and tool calling, we utilized models like Llama and Qwen. Our aim was to blend the best capabilities of these community models into a single model. We’ve also made this curated dataset publicly available on Hugging Face, with around 30 million question-answer pairs. This allows the community to explore, use, and build upon our work. We were also excited to see our partner ServiceNow recently announce their apprehend Nemotron model, which was trained using our dataset to enhance their own reasoning capabilities. Jean-Marc Mommessin: That’s fantastic that you’re sharing the dataset. Given that you used other models to generate some of this data, what kind of quality checks did you implement to ensure the reliability of the training pairs? Joey Conway: Data quality was absolutely paramount. Since we were generating a significant portion of the data using other models, we implemented a rigorous multi-layered quality assurance process. First, for each expert model used to generate data in a specific domain, we would generate multiple candidate responses for the same prompt. Then, we employed a separate set of “critic” models to evaluate these candidates based on correctness, coherence, and adherence to the prompt. Second, we implemented a scoring mechanism. Each generated question-answer pair received a quality score based on the critic model’s evaluation. We set a high threshold, and any pair that didn’t meet this standard was discarded. Third, human review was integrated at various stages. Our team of data scientists and engineers manually inspected samples of the generated data to identify any systematic errors, biases, or instances of hallucination. This human oversight was crucial for catching nuances that automated systems might miss. Fourth, we focused on the diversity of the generated data. We wanted to ensure we weren’t just getting variations of the same types of questions and answers. We implemented strategies to encourage the expert models to generate a broad range of examples within each domain. Finally, after training Llama Nemotron Ultra on this curated data, we conducted extensive evaluations against benchmark datasets and in real-world use cases. This feedback loop helped us further refine our data generation and filtering techniques. So, it was a comprehensive approach involving expert generation, automated criticism and scoring, human review, diversity checks, and rigorous downstream evaluation to ensure the high quality of our training data. Jean-Marc Mommessin: The quality of the synthetic data is so important. Could you elaborate on the stages you take to ensure high accuracy when generating this data? Joey Conway: Absolutely. When doing synthetic data generation, there are a few key stages to ensure high accuracy. The first is the prompts – the seed data and how we prompt the model. The second is the quality of the responses. On the prompting side, we focus on prompting models where we believe they excel. For example, we might use Llama for chat-related prompts but avoid using a non-reasoning model for math. It’s crucial to align the prompts with the core strengths of the model. For vetting the responses, we invest time in both human manual review and automated methods. Going forward, we anticipate increasing our use of verifiers and reward models, similar to what we’ve done on the Reinforcement Learning (RL) side. The reason we’ve open-sourced much of this is that there’s a lot of nuance involved, and we wanted the community to engage with these challenges. Enterprises like ServiceNow have specific goals, and some of our data might be more or less useful to them. By making it available, they can vet it themselves. We also provide tools like classifier models to help categorize content, such as news or sports, allowing users to make informed decisions about the data blends they use for training. Jean-Marc Mommessin: Perfect. Is there anything else you’d like to highlight regarding this pipeline? Joey Conway: Yes, I’d like to touch on the Reinforcement Learning (RL) aspect. Following the supervised fine-tuning stage, where we enhanced core skills, we’ve just begun to explore the potential of RL with Nemotron. We believe this will be a significant area of future development. What’s exciting about RL is that its effectiveness is largely tied to the available compute time. The more time we invest, the better the model becomes at specific tasks. In our RL stages, we’ve developed methods to automate the process of asking the model a question, grading its answer, and providing feedback to allow it to learn and improve. You can see on the slide the domains where we’ve applied this: scientific reasoning, instruction following, and chat. If you look at the leaderboards, you’ll see that even with new models emerging, we’ve maintained a strong position in these areas, largely due to the effectiveness of RL in achieving top-tier accuracy. We’re optimistic that we’ll see more of this in the community, with more discussion and publication of techniques and data. We’ve started sharing some of our work in this area and will have much more to come in the next three to six months. Jean-Marc Mommessin: You mentioned RL and instruction following, which ties back to the beginning of our conversation. It seems like you’ve come full circle here. Joey Conway: Exactly. The exciting aspect here is automating the feedback loop wherever possible. For chat, we published a fine-tuned reward model last fall. Those who followed our work might recall that our Llama Nemotron model topped the chat leaderboards then. This was because the reward model provides an automated way to teach the original model whether its responses are good or bad. It essentially grades responses based on helpfulness, conciseness, verbosity, groundedness, and similar factors. This granular feedback per generated response allows the model to improve significantly, often more so than through supervised fine-tuning alone, which typically involves a few passes without a continuous feedback loop. Similarly, for instruction following, we use a verifier and a dataset to teach the model whether it followed instructions well or needs to try again. We’re eager to expand this approach to more domains. We’ve already published datasets related to coding and math since the release of this model a few weeks ago, and these have become popular on Hugging Face. I anticipate significant growth in this area within the community. Jean-Marc Mommessin: Alright, so one of the big innovations here, and you touched upon it, but I want to emphasize it, is the ability to toggle reasoning on and off via the system prompt. This is quite unique, and I’m sure many will follow suit. Could you expand on the idea behind this, how you see it applying to agents and beyond, its value, and the key challenges in implementing it? Joey Conway: The reasoning on and off capability was a core goal from the outset. We observed that models in the community often excelled in either reasoning or non-reasoning tasks, and we wanted to simplify deployment by having a single model that could handle both. We had to determine the best way to teach the model when to reason and when not to, while also providing enterprises with explicit control, as they often have deeper domain knowledge than we do. The motivation behind this is that reasoning generates significantly more tokens, which can lead to higher latency and cost. While crucial for solving complex problems, it’s not always necessary. We wanted to give enterprises the control to balance accuracy with latency and cost, allowing them to decide when to employ reasoning and when to opt for faster, less computationally intensive responses. Initially, we weren’t sure how to achieve this, as it hadn’t been widely implemented in the community. Our approach in the supervised fine-tuning stage was to explicitly teach the model by presenting the same question with two different answers: one with detailed reasoning and one without. This essentially doubled our dataset for this specific purpose. However, the outcome is a single model where users can simply include “use detailed thinking on” or “use detailed thinking off” in the prompt to control the model’s reasoning process. On the training side, this required more effort to teach the model this distinction. What we have today is essentially a v1, and I expect others will follow this approach. We’re also excited about future developments, such as time or token limits for reasoning and more granular controls. I’m optimistic that we’ll see further breakthroughs in this area within the next six to nine months, as the problem-solving power of reasoning is significant, but it comes with trade-offs that the community will continue to refine. Jean-Marc Mommessin: We all know that the real test comes in production. Production environments are sensitive to latency, cost, and while accuracy and reasoning are vital, excessive reasoning can lead to scalability issues and increased latency. The flexibility you’ve introduced is fantastic, and I can see numerous production use cases that will greatly benefit from the ability to control reasoning on a per-query basis. So, when you were developing this model, you aimed to balance accuracy and efficiency. Could you share some insights into how you made these trade-offs, the timeline for building the model and the team involved, and how you determined the optimal compromise between these two critical factors? Joey Conway: Balancing accuracy and efficiency is always a challenge. Our initial goal was to achieve both, which is a difficult undertaking. We started with the “Super” model, which was the most recent Llama 3.1 70B release from Meta, as our baseline for accuracy. We weren’t sure if we could simultaneously improve accuracy and reduce the model size. We found that through our training techniques and distillation process, we could indeed boost accuracy. We even released an initial checkpoint reflecting this. However, we wanted to go further by incorporating strong reasoning capabilities, aiming for state-of-the-art reasoning scores. This is where the SFT and RL stages came in, which required significant time for synthetic data generation since this type of data didn’t exist. During training, we carefully considered the number of epochs for each skill and continuously measured accuracy. Our goal was to improve performance across all six key areas rather than excelling in just a couple. This balancing act took more time as we experimented to find the right combinations. However, we felt it was crucial to ensure world-class performance in these six enterprise-relevant scenarios, including chat and instruction following. For areas like MMLU, we focused on maintaining performance and preventing regression rather than actively trying to improve scores. So, there were definitely priorities and trade-offs involved. Ultimately, we believe these were the right focus areas for our enterprise customers. Jean-Marc Mommessin: You are releasing this model family as part of the open-source community. We’ve discussed the gaps you aimed to address and the unique reasoning on/off feature for production scalability. Could you share your thoughts on how NVIDIA and your team view the role of these models within the broader open-source and LLM ecosystem, especially given your work building upon the Llama base? Joey Conway: NVIDIA has a long history of contributing models to the open-source community. What excites us about Llama is its strong traction with enterprise customers. While NVIDIA Research publishes extensively across various domains, our goal with Llama Nemotron was to build upon Llama’s momentum in enterprise adoption by focusing narrowly on specific areas. The base Llama models already cover many things exceptionally well, so we saw an opportunity to build on top of that and be very targeted in our enhancements. The recent LlamaCon event and Meta’s announcements sound very promising, and we’re excited about Llama 4 and the ongoing work there. Moving forward, we anticipate continuing to identify specific areas where we can add significant value, while Meta continues to build excellent general-purpose models suitable for enterprise production. From our perspective, reasoning will likely remain a key focus, and we’re also excited about Meta’s advancements in this area. Tool calling, instruction following, and chat are also areas we’ll continue to develop. One area we’re particularly interested in exploring is multilingual capabilities. For large enterprises, supporting multiple languages is crucial. While many models handle individual languages well, we aim to focus on a few key languages and ensure world-class accuracy for reasoning, tool calling, and chat within those. This is likely the next major area of expansion for us, beyond the exciting developments in model architectures like Llama 4’s new MoE architecture, which we’re also keen to explore for potential distillation and optimization for NVIDIA GPUs. So, there’s a lot of exciting work ahead. Jean-Marc Mommessin: When you say multilingual, are you thinking of supporting a broad range, like 50 languages, or a more focused set, perhaps around 5 or 10 initially, given the benchmark challenges you mentioned? Joey Conway: We’ll probably start with a more focused set, perhaps around 5 to 10 languages. The challenge is that the community currently lacks comprehensive benchmarks for tasks like reasoning or tool calling across a wide variety of languages. As we develop these multilingual models, we’re also having to create evaluation data simultaneously, which takes time. If those benchmarks were readily available, the process would be smoother. However, we see this as an exciting challenge. Our initial focus will likely be on a smaller set of languages where we can establish strong performance, given the current limitations in community-wide benchmarks. Jean-Marc Mommessin: Let’s shift gears and talk about another state-of-the-art open-source model you recently released: Parakeet TDT 0.6 B parameters, V2. This model has set a new standard for automatic speech recognition (ASR), transcribing one hour of audio in just one second. That’s 50 times faster than other open-source ASR models, and remarkably, it achieves only a 6% word error rate. This is truly impressive. What else would you like to highlight about this model before we discuss the “how” behind its incredible performance? Joey Conway: It’s worth noting that NVIDIA has been working on ASR models for a long time, even before I joined. We’ve also released many open models in this space over the years. The teams working on this are exceptional, and they consistently strive to balance accuracy with latency and throughput. Parakeet V2 is the latest in this line of high-performance models from NVIDIA. Jean-Marc Mommessin: It sounds like the advancements will keep coming. So, let’s delve into how you achieved this remarkable performance with Parakeet TDT. What kind of architecture did you use? I understand it’s based on a Fast Conformer architecture with specific optimizations like 8x depth-wise separable convolutional downsampling and limited context attention. Could you explain how you arrived at this approach and whether these optimizations primarily enhance speed and throughput or if they also contribute to accuracy and the ability to process long audio segments like a full hour in one shot? Joey Conway: Yes, we’ve explored various architectures for ASR over the years, and the Conformer architecture, originally from Google, has shown great promise. Our goal with Parakeet TDT was to take the Conformer architecture and make it significantly more efficient and faster without sacrificing quality. We’ve implemented several key optimizations.  First, as you mentioned, the depth-wise separable convolution downsampling. At the input stage, we significantly downsample the audio, which reduces the computational cost and memory requirements for processing. Second is the limited context attention. By focusing on smaller, overlapping chunks of audio, we can maintain accuracy while achieving a speedup in processing. Third, on the encoder side, we also utilize a sliding window attention technique, which allows us to process longer audio files without having to split them into shorter segments. This is crucial for handling long-form audio like a full hour in a single pass. Beyond the Conformer architecture, Parakeet TDT incorporates a Token and Duration Transducer (TDT). Traditional Recurrent Neural Network (RNN) transducer technology processes audio frame by frame. What we’ve done with TDT is enable the model to predict both the tokens and the expected duration of those tokens. This allows it to make decisions to skip over redundant frames, significantly speeding up the transcription process. This TDT innovation alone contributes to around a 1.5 to 2x speedup. So, there’s a combination of architectural choices and specific optimizations that contribute to Parakeet TDT’s impressive speed and accuracy. Jean-Marc Mommessin: I want to go back to one or two of those. Those are amazing, frankly. The speed increase is remarkable. Joey Conway: Yes, and we have another technique called a label looping algorithm. Essentially, when we’re doing batch inference, this algorithm allows us to advance the tokens independently for different samples. This separation of the workflow enables us to sweep and loop over frames and labels more efficiently, significantly speeding up the decoding process. Lastly, on the decoder side, we’ve moved some of the computation into CUDA graphs, which is a more efficient way to run many small kernels. This optimization alone provided around a 3x speed boost. So, as you can see with TDT models, we’ve been able to achieve speeds comparable to Connectionist Temporal Classification (CTC) decoders, which are also known for their speed, while maintaining high accuracy. Our overall theme is always to balance speed improvements with maintaining or even enhancing accuracy. Techniques like CTC decoders have been around for a while and are fast but might not be as accurate. It really depends on the use case, but we’re always striving for that balance. Jean-Marc Mommessin: Can we revisit the limited context attention? Do you see this technique having broader applications in other areas down the line? Joey Conway: Yes, I believe so. Patterns like the sliding window attention are already used in other areas, such as LLMs. Our research teams are constantly experimenting, looking at successful techniques from different domains, and trying to apply them in new ways. Interestingly, some of the researchers who worked on Parakeet TDT also work on Llama Nemotron, so there’s a cross-pollination of ideas. I do expect that some of these techniques will find broader applications going forward. We also anticipate further improvements to TDT and the Conformer architecture, as we’ve been working on them for several years now. I don’t see these core technologies going away anytime soon; we’ll likely continue to refine them. Jean-Marc Mommessin: Leaving the TDT aside, do you see other potential applications for the Token and Duration Transducer concept in other domains? Joey Conway: That’s a good question. I’m not immediately seeing a direct application of the TDT concept outside of ASR. Its history is rooted in RNNs and RNN transducers, which have primarily been used in speech recognition. However, some of the underlying techniques we’ve applied to it, like using CUDA graphs for optimizing kernel execution, are general techniques that we use whenever we identify bottlenecks in a model’s pipeline. So, while the TDT itself might be domain-specific, some of the optimization strategies we’ve employed could certainly translate to other areas, including large language models. Jean-Marc Mommessin: let’s talk about data. AI data is always a key topic. How do you ensure that the data used to train Parakeet TDT is diverse enough to handle various accents, dialects, vocal ranges, pitches, and noisy background conditions, which often negatively impact ASR performance? Joey Conway: You’re absolutely right. As humans, we naturally filter out accents and background noise to understand speech. However, deep learning models are only as good as the data they’re trained on. Early on, limited data for specific accents or languages resulted in poor performance for those variations. What might have initially seemed like edge cases have become increasingly common, highlighting the need for more representative data. We’ve invested significant effort in curating our datasets to reflect this real-world diversity. We use techniques like classifiers to analyze our data and understand the distributions of accents, dialects, and acoustic conditions. We’ve worked with customers like YUM! Brands, who have drive-through use cases with significant highway noise, illustrating the importance of training the model to handle such challenging environments. Ensuring the right blend and distribution of these conditions in our training data is crucial for the model’s robustness. I’m also excited to announce that we plan to open-source a substantial speech dataset, around 100,000 hours, where we’ve meticulously performed this kind of curation. This dataset will include variations in sound levels, signal-to-noise ratios, background noise types, and even telephone audio formats relevant for call centers. Our goal is to provide the community with high-quality, diverse data that enables models to perform well across a wide range of real-world scenarios. Jean-Marc Mommessin: That’s fantastic news about the open-sourcing of the speech dataset! My final question regarding the Parakeet family: you currently have the 600 million and 1.1 billion parameter models. How do you envision future development for this family? What are the potential directions? Joey Conway: We’re considering development along two main dimensions: model size and the number of supported languages. In terms of size, we’ve released models at the smaller and mid-range to demonstrate the potential, similar to our approach with Llama Nemotron Super. We plan to explore larger models, potentially around 2 billion parameters, which we anticipate will handle even more languages and dialects. On the smaller end, we’re even considering models down to around 50 million parameters. The motivation here is to address use cases at the edge where a smaller footprint is necessary, such as enabling real-time audio processing for robots in noisy environments. We’ll be exploring the right trade-offs for such applications. Technologically, we plan to work on streaming capabilities for TDT. Currently, much of the processing is done in an offline batch mode, but we want to enable real-time, live transcription. And as mentioned, we’re excited about releasing the large, curated speech dataset. Finally, for those looking to deploy these models in production, we recommend exploring techniques like word boosting, which allows for customization of text normalization to include domain-specific terms and acronyms. We aim to provide a wide range of options for users to get started and tailor the models to their specific needs. Jean-Marc Mommessin: I’m very familiar with the NVIDIA Orin platform. Would these Parakeet models currently run on NVIDIA Orin? Joey Conway: Yes, I believe the 0.6 billion parameter model likely would run on Orin. I would need to double-check the exact specifications, but I’m quite confident it’s feasible. Jean-Marc Mommessin: Orin packs a significant punch. I especially love the robotics use case you mentioned. While there’s been a lot of focus on robot vision, the ability to hear and understand quickly is equally crucial, especially for safety. A model that’s 50 times faster and highly accurate in understanding another modality seems like a perfect fit for robotics. Joey Conway: Yes, and the slight hesitation I had earlier was due to the understanding that in robotics, there are often multiple models running simultaneously, including vision models. So, resource allocation is a consideration. However, our push towards smaller, more efficient models is precisely to address these kinds of multi-modal edge computing scenarios. The low latency and real-time processing capabilities of Parakeet are indeed very beneficial for enabling robots to react quickly and safely to auditory cues. Jean-Marc Mommessin: Anything else you’d like to add as a final thought on the Llama Nemotron Ultra and Parakeet families? They’re both open-source, fast, high-throughput, cost-efficient, and run on smaller footprints – are these the key takeaways? Joey Conway: Yes, that’s a great summary. Those were the core objectives we set out to achieve. We aimed for state-of-the-art accuracy, optimized footprints for efficient GPU utilization in terms of latency and throughput, and a commitment to open-sourcing everything to empower the community. We’ve strived to be as community-friendly as possible by releasing datasets, using permissive licenses, and making it easy for people to experiment. We’re eager to see the community’s feedback and the innovative applications they build upon our work. We’re also looking forward to learning from their experiences. Jean-Marc Mommessin: Where are all these models and datasets available? Joey Conway: Everything we’ve published is on Hugging Face – the models and the datasets. The software stack to run them comes from NVIDIA and is available on NGC, our content repository. Much of the underlying software is also open-source and can be found on GitHub. We also provide pip wheels for easier installation. The Nemo framework is the central hub for much of this software stack, whether you want to run the models or fine-tune them. We’ve tried to make it as user-friendly as possible. We use the same software internally to build the models, so it should be relatively straightforward for others to pick up and deploy as well. Jean-Marc Mommessin: Well, Joey, this has been fantastic. I’m continually impressed by NVIDIA’s commitment to giving back to the community with state-of-the-art models that will undoubtedly find their way into production. Thank you so much for your time and insights. I look forward to our next conversation. Joey Conway: Thank you, Jean-Marc. It was my pleasure, and we appreciate the opportunity.  Jean-marc MommessinJean-marc is a successful AI business executive .He leads and accelerates growth for AI powered solutions and started a computer vision company in 2006. He is a recognized speaker at AI conferences and has an MBA from Stanford.Jean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/NVIDIA AI Releases HOVER: A Breakthrough AI for Versatile Humanoid Control in RoboticsJean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/Speech-to-Speech Foundation Models Pave the Way for Seamless Multilingual InteractionsJean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/Lowe’s Revolutionizes Retail with AI: From Personalized Shopping to Proactive Customer AssistanceJean-marc Mommessinhttps://www.marktechpost.com/author/jean-marc0000677/Google DeepMind’s Gemini Robotics: Unleashing Embodied AI with Zero-Shot Control and Enhanced Spatial Reasoning

With last year’s release of iOS 18, AirPods Pro got even better. Apple added new gestures, improvements to gaming support, and more. Head below for a recap of each of these features and details on how to use each of them. Available on AirPods Pro 2 and AirPods 4 With iOS 18, AirPods Pro 2 and AirPods 4 users can interact with Siri and incoming notifications by nodding their heads up or down. Accept a call or reply to notifications and messages: Nod your head up and down. Decline a call or dismiss notifications and messages: Shake your head side to side. To use head gestures to interact with Siri, you’ll also need to make sure Announce Calls and Announce Notifications are enabled. Open the Settings app and choose “Notifications” and make sure the “Announce Notifications” setting is turned on. Once the “Announce Notifications” setting is enabled, here’s how to manage Head Gestures: With your AirPods connected to your iPhone, open the Settings app and tap your AirPods at the top. Scroll down and tap “Head Gestures” Toggle on the feature and choose with gesture is linked to “Accept, Reply” and “Decline, Dismiss.” Voice Isolation Available on AirPods Pro 2 and AirPods 4 Voice Isolation is a new feature available for AirPods users that helps ensure the caller’s voice is heard in loud or windy environments. Powered by machine learning and the H2 chip inside, Apple says that this feature isolates and enhances voice quality while removing significant background noise for the listener. Note that Voice Isolation has been a feature on the iPhone, iPad, and Mac for several years. This year, however, it’s supported directly on AirPods Pro 2 and AirPods 4. Here’s how to enable Voice Isolation on your AirPods: While on a call, swipe down from the top of your screen to access Control Center Tap the “Controls” button at the top of the interface Tap on “Voice Isolation” Gaming improvements Available on AirPods 3, AirPods 4, AirPods Pro, and AirPods Max iOS 18 also brings Personalized Spatial Audio with dynamic head tracking to gaming for the first time. To ensure this feature works for you, open the Settings app, navigate to your AirPods settings, and scroll down to “Personalized Spatial Audio.” If you haven’t previously set up this feature, you’ll be guided through a process that includes a Face ID-style scan of your ears to personalize the Spatial Audio experience. This feature applies to things like music and videos, and is now applicable to gaming thanks to iOS 18. Apple also says that iOS 18 brings support for improved voice quality, including 16-bit, 48kHz audio, for chatting with teammates while gaming with AirPods Pro 2. Latency for AirPods Pro 2 users has also been upgraded. Custom Adaptive Audio Available on AirPods Pro and AirPods 4 with Active Noise Cancellation iOS 18 brings more granularity to the Adaptive Audio feature on AirPods Pro 2 and AirPods 4. For those unfamiliar, adaptive mode “blends Active Noise Cancellation and Transparency mode together to control the level of noise you hear in your headphones based on the changing noise conditions in your environment.” With iOS 18, you can now customize Adaptive Audio to better fit your needs and “allow more or less noise.” With your AirPods connected to your iPhone, open the Settings app and tap your AirPods at the top. Scroll down and tap “Adaptive Audio” Move the slider left to allow for “Less Noise” when using Adaptive Audio or to the right to allow for “More Noise.” Hearing Health Last year, Apple supercharged AirPods Pro 2 with new hearing health features. Now, you take a hearing test with your AirPods Pro to find out if you have hearing loss. You can then use AirPods Pro as a hearing aid if you have mild to moderate hearing loss.  Apple explains: With the incredible audio quality of AirPods Pro, the user’s personalized hearing profile is automatically applied to music, movies, games, and phone calls across their devices without needing to adjust any settings. This first-of-its-kind software-based Hearing Aid feature brings users the ability to fine-tune their experience at any time, making access to hearing assistance easier than ever at an approachable price point Learn more:  Best AirPods Pro accessories Add 9to5Mac to your Google News feed.  FTC: We use income earning auto affiliate links. More.You’re reading 9to5Mac — experts who break news about Apple and its surrounding ecosystem, day after day. Be sure to check out our homepage for all the latest news, and follow 9to5Mac on Twitter, Facebook, and LinkedIn to stay in the loop. Don’t know where to start? Check out our exclusive stories, reviews, how-tos, and subscribe to our YouTube channel

Design, at its best, is not just about making something new; it’s about re-seeing what’s already there. In Charu, a chair designed by Harry Noble M under the mentorship of Sweety Taur, material, memory, and meaning converge into a form that does far more than offer a place to sit. It raises a quiet but powerful question: who has been allowed to sit, how, and why? Historically, chairs have never been neutral. From thrones to office seats, they’ve marked status and reinforced hierarchy. The colonial planter’s chair, its wide, sprawling arms designed for leisure, was once a symbol of patriarchal power and colonial dominance. Charu draws directly from this legacy, not to continue it, but to subvert it. Its form echoes the past, but its voice is unmistakably contemporary. Designer: Harry Noble M Crafted in cane by traditional artisans in Ahmedabad, Charu mimics the shape of the planter’s chair only to unravel its symbolism. Its structure exaggerates space, not to glorify “manspreading,” but to critique it. The gaps between the armrests turn posture into protest. Before anyone even sits, the chair begins to speak. This isn’t just furniture. It’s storytelling through design. Inspired by a deeply personal memory of sitting beside a Charu Kasera, a short stool traditionally used in Indian households, Menon extends this recollection into a wider inquiry: What histories are embedded in the objects we take for granted? How do caste, class, and gender shape the ways we sit and the spaces we’re allowed to occupy? The making of Charu was rooted in cultural anthropology and human-centered research. Mask-making exercises explored object symbolism; media archives and user surveys uncovered how the planter’s chair, once a colonial relic, found new meaning in domestic settings. Voices across regions and backgrounds mapped the chair’s transformation from a status object to a relic of inherited bias. Design references were wide-ranging. Case studies included Laurel’s chair, which visually resists patriarchal form, and Anna’s, which encourages inclusive posture. Charu builds on this lineage, grounding itself in local craft while raising globally resonant questions about ownership, space, and comfort. Menon’s ergonomic approach was equally radical. A body-storming session with peers revealed that true comfort doesn’t come from mimicking Western ergonomic standards, but from rethinking them. Supporting the mid-thoracic region, not just the shoulders, encourages longer and more natural sitting. The downward-sloped seat, angled armrests, and gentle curves avoid strain while rejecting entitlement. The very form denies slouching, it demands intention. Materials mattered. While bamboo was more accessible, it lacked the pliability needed for the chair’s sculptural arcs. Cane, symbolically elite, regionally relevant, and artisan-friendly, was the natural choice. Even as material costs complicated the woven storage element, the final build stayed honest to its conceptual clarity. The process moved from sketches and scaled models to full-size prototypes. Final fabrication, led by Hussain Bhai in Ahmedabad, infused the chair with a sense of pride and regional authenticity, anchoring the project in lived craft rather than industrial detachment. Visually, Charu is part sculpture, part artifact. Shaped like an oversized basket, it blends the rustic and the refined. The bowl-like base offers a generous welcome; the high back curves into a pointed, leaf-like peak; the rocking silhouette evokes both tradition and tenderness. From the side, it could be mistaken for a farmer’s harvest basket, except it holds critique instead of grain. This adaptability allows Charu to slip seamlessly across settings. It would feel at home in a breezy coastal villa or a sunlit porch, in a boutique resort or a mindful co-living space. Even modern interiors looking for warmth, tactility, or a story could find in Charu a compelling anchor. And while this edition stands as a flagship concept, akin to a fashion showstopper, its journey doesn’t end here. Menon envisions future iterations: simplified arcs for scalability, extended seating for calf support, and thoughtful additions like cup holders or textural inlays for daily use. It’s a living form, not a fixed one. The post A Revolutionary Cane Chair Challenging History, Hierarchy, and How We Choose to Sit first appeared on Yanko Design.

North Boulder Library / WORKacSave this picture!© Bruce DamonteLibrary•Boulder, United States Architects: WORKac Area Area of this architecture project Area:  12800 ft² Year Completion year of this architecture project Year:  2024 Photographs Photographs:Bruce Damonte Manufacturers Brands with products used in this architecture project Manufacturers:  ELEVATE, Holcim, Alucobond, American Hydrotech, Daltile, Forbo, Guardian Glass , InCord, Kawneer, Montel, Overhead Door Corp., Swing Set Mall, Wilsonart More SpecsLess Specs Save this picture! Text description provided by the architects. The Boulder Public Library issued an open Request for Proposal (RFP) in 2018 for a new branch library in North Boulder, a project the community had anticipated for over two decades. The RFP called for an "iconic" building, which many competitors interpreted as a visually striking design. However, WORKac www.work.ac - the architecture firm based in New York City and led by Amale Andraos and Dan Wood - proposed a vision where the library's iconic status would stem from its sustainability and its positive impact on the community and environment.Save this picture!Save this picture!Save this picture!This innovative approach resonated with the library. The building stands out as an original project rooted in WORKac's significant past experiences. Andraos and Wood have always been deeply committed to issues in education, a dedication that culminated in Andraos' role as Dean of the Graduate School of Architecture, Planning and Preservation (GSAPP) at Columbia University, where Dan Wood is an Associate Adjunct Professor. At the time this project was commissioned, their Kew Gardens Hills Library in Queens, NY had just recently opened, a source of pride for its community, and their joyful Miami Museum Garage - which inventively transforms the simple and often frustrating act of parking a car into an unexpected opportunity for social interaction - had reached wide international resonance.Save this picture!Save this picture!Rooted in community engagement - The North Boulder Library is situated within a diverse neighborhood that blends new developments for young professionals, art studios, galleries, and two manufactured home communities that include Boulder's largest Spanish-speaking population. The chosen site is a triangular plot bordered by Broadway to the west and Three Mile Creek to the south, with stunning views to the Boulder Flatirons. WORKac's approach to the project was deeply rooted in community engagement.Save this picture!Save this picture!WORKac worked for almost eight years on the project, including a three-year Community Engagement and Site Planning process, which entailed more than twenty public presentations of the design during different phases to community groups, politicians, and stakeholders. More than 3,000 people attended the opening ceremony on June 29, 2024. "Today and every day we endeavor to render architecture more human, to turn the pragmatic fantastic, and to reclaim the 'best' in 'best practice' away from the technocratic and towards the creative. We approach every project, regardless of scale, program, type or context with the same passion, drawing resolute realism together with polemical optimism," say Amale Andraos and Dan Wood.Save this picture!Site, Program and Architecture - Boulder's unique geographical position at the intersection of the Rocky Mountains and the Great Plains has historically shaped its rugged architectural vernacular. The North Boulder Library design celebrates this context, acknowledging the area's complex relationship with the natural environment. Through its connections with the urban surroundings, the library not only reflects its environment but also enhances its visual and functional relationship with the local community.Save this picture!The design of the North Boulder Library was directly informed by the community's input, leading to the inclusion of key programs such as Boulder Reads, which supports literacy development for children and adults, and a "Maker Kitchen," which evolved from the community's desire for a maker space together with ideas for a community garden and kitchen area. "Our greatest delight is for others to feel a sense of joy, of belonging, and of possibilities for the future," state the architects.Save this picture!The building negotiates the triangular site that includes a seasonal creek running diagonally through it with a building that respects the scale of its residential neighbors to the north while opening up to views of the Flatiron Mountains and Rocky Mountain foothills to the south and west. The library is designed with the major community spaces on the second floor. The lower northern side integrates a shallow, fully- accessible ramp that allows these second-floor community and ESL classrooms to open at night when the library is closed, reinforcing the library's role as a community hub. This ramp is enhanced by a public art installation by Montreal-based Daily tous les jours that plays music as users ascend or descend. Despite its modest size, the building has four entrances and a variety of public spaces that seamlessly extend outdoors, connecting with both the residential neighborhood to the north and the Fourmile Canyon Creek park to the south.The building's design is both intriguing and unexpected. Its irregular geometry, a convergence of triangular forms, mirrors and influences the internal layout. This interplay of shapes creates a series of surprising spatial experiences.Save this picture!Save this picture!The main public floor is divided into a large reading room for adult patrons and a children's area with a private nook for story-reading and windows onto a slide that can be accessed through a rope climbing structure, allowing kids to climb up through the building and slide down into the library's new playground. Other key areas on the ground floor include the Maker Kitchen, which connects to an edible garden and playground, and large windows that offer breathtaking views of the mountains. The interior design incorporates custom elements like a wallpaper by graphic designer Andrew Freeman, principal at afreeman, featuring historical photos from Boulder's archives, celebrating the region's indigenous heritage. The building's exposed ceiling structure adds to the space's acoustic performance and aesthetic richness.Save this picture!WORKac's architecture is both unpretentious and inspiring. It embodies a sense of freedom that invites people to engage with the space and take ownership of it. This approach reflects a profound commitment to civic responsibility. Sustainability is a central focus of the project, with initial plans aiming for net-zero energy. Although some features were scaled back due to the COVID-19 pandemic and subsequent economic challenges, Boulder's stringent sustainability regulations ensured that the library maintained its high green building standards. A rooftop solar array supplies a significant portion of the building's energy, while the site includes a rainwater garden planted with native, butterfly-attracting flowers and shrubs to protect the seasonal creek from runoff.Save this picture!A testament to the power of thoughtful design - The North Boulder Library is a testament to the power of thoughtful, community-driven design. Despite a modest budget, WORKac has created a building that is both beautiful and functional, serving as a model for equitable public architecture. Funded entirely by the City of Boulder, the library stands as a beacon of progressive values, sustainability, and community engagement, reflecting the spirit of the city it serves. WORKac is the recipient of the 2023 Arts and Letters Award in Architecture, a prestigious honor given by the American Academy of Arts and Letters to recognize exceptional American architects whose work embodies artistic excellence and has made a significant impact on the field of architecture. They are currently working on the Beirut Art Museum in Lebanon and projects at Vassar College, including a renovation to its main library.Save this picture! Project gallerySee allShow less Project locationAddress:Boulder, United StatesLocation to be used only as a reference. It could indicate city/country but not exact address.About this officeWORKacOffice••• MaterialSteelMaterials and TagsPublished on May 14, 2025Cite: "North Boulder Library / WORKac" 14 May 2025. ArchDaily. Accessed . <https://www.archdaily.com/1030123/north-boulder-library-workac&gt ISSN 0719-8884Save世界上最受欢迎的建筑网站现已推出你的母语版本!想浏览ArchDaily中国吗?是否 You've started following your first account!Did you know?You'll now receive updates based on what you follow! Personalize your stream and start following your favorite authors, offices and users.Go to my stream

For many of us, 2020 was a year of upheaval and transformation. We all faced our own challenges, and for Lebanese designer Donna Maria Feghali, it marked a creative shift stemming from what she describes as a “really intense personal journey.” Feghali candidly shares: “Looking back, I realized it totally reflected in my creative work and in this collection, which is way different from anything I’ve ever done before.” That year, she established her Paris-based studio, and now, she introduces Eshrin, a furniture collection dedicated to that pivotal time. Named after the Arabic word for twenty, Eshrin is an exploration of contrasts – structured yet fluid, bold yet understated – bridging past experiences with a new creative vision. Eshrin is Feghali’s first collection produced in Egypt, created in collaboration with Cairo-based manufacturer Nineteen Furniture. The series includes a dining table, dining chair, coffee and side tables, a buffet, and two couches, each piece embodying her signature blend of sculptural presence and refined simplicity. The Eshrin Dining Table is the central piece of the collection, embodying a sculptural approach to furniture. Its base, comprising four arched Egyptian limestone cylinders in Golden Sinai and Grey Triesta, supports a Macedonian white marble tabletop, creating a striking contrast between solidity and lightness. Complementing the table, the Eshrin Dining Chair echoes its curvature of the base with a sleek silhouette and curved backrest. Crafted from acid-treated beech wood and upholstered in bouclé fabric, it blends structure with softness, offering a seat that is both comfortable and visually refined. Like the dining table, the Eshrin Buffet is also designed with a cylindrical base, balancing the solidity of its structure. The rounded edges extend beyond the frame of the storage, providing a natural grip to open doors that reveal ample storage. The Eshrin Side Table, sculptural in its own right, merges bold geometry with organic warmth. The solid beech wood base, finished with an acid treatment, anchors the piece, while the pitch pine burned wood top adds a tactile dimension. The Eshrin Coffee Tables have a resemblance to both the dining table and the side table. With their arched cylindrical bases and perfectly balanced table tops, they reinforce the collection’s play on form and weight. Rounding out the collection, the minimalist linear Eshrin Couch features subtle curves that soften its structured silhouette. Available in two variations – one featuring an acid-treated beech wood base with white bouclé upholstery, the other with a lacquered beech wood base and textured beige fabric – the couch is a soft landing spot for solo relaxation or open conversation. We all came away from 2020 changed in some way with our perspectives shifted and our priorities reshaped. That year marked the beginning of a new creative chapter for Feghali, one that led to Eshrin. Through this collection, she translates a deeply personal journey into form, material, and balance, proving that even in times of uncertainty, something new and meaningful can emerge. To learn more about Donna Maria Feghali’s Eshrin collection, visit donnamariafeghali.com.

Save this picture!Luum Temple / CO-LAB Design Office. Image © César BéjarArtificial intelligence (AI) is no longer a futuristic idea in architecture — it is a concrete reality that is reshaping how we design. In seconds, computational systems can process and evaluate a wide range of variables — formal, programmatic, contextual, and regulatory — guiding architects toward highly optimized solutions. But as we embrace this algorithmic revolution, a critical question arises: can architectural intelligence be reduced to data-driven logic? In response, alternative approaches are gaining momentum — ones that value ways of building grounded in sensory experience, adaptation to place, and the intergenerational transmission of knowledge. In the exchange between artificial and ancestral forms of intelligence, a deeper understanding begins to take shape. Intelligence does not reside in the tools themselves, but in the intention and sensitivity with which we use them to navigate complex realities.Historically, architectural intelligence has expressed our ability to respond to spatial, climatic, cultural, and functional challenges. Early on, this intelligence was intuitive and empirical, rooted in vernacular knowledge passed down through generations and shaped by hands-on interaction with the built environment. Buildings were constructed using local techniques, available materials, and a deep awareness of context, revealing a form of intelligence that was practical, responsive, and deeply adaptive.With the rise of modernity and the application of the exact sciences to construction, architectural intelligence came to rely more heavily on technical and rational methods — calculations, standardizations, and codes. The emergence of digital technologies in the late 20th century, and more recently the growing use of AI, has vastly expanded the design toolkit. Generative algorithms, machine learning, and parametric modeling not only accelerate design processes but also introduce a new layer of systemic intelligence. These tools support more efficient decision-making. As Mario Carpo argues in The Second Digital Turn (2017), this shift is not only technological but also epistemological: we are witnessing a transformation in the way architecture is conceived, where human authorship blends into statistical and computational systems. In this landscape, AI becomes a design agent, capable of learning patterns and proposing solutions that often defy human intuition. Related Article How AI Will Make Everyone a Better Designer: For Better or Worse Save this picture!Save this picture!Yet as these technologies advance, there is also a renewed appreciation for traditional and natural forms of intelligence. Increasingly, contemporary projects are incorporating lessons from nature and vernacular practices. This is not a contradiction, but rather a reflection of a deeper tension: a reevaluation of what counts as "intelligent" when technical efficiency is considered alongside ecological, cultural, and social complexity. Within this broader perspective, the collective intelligence of communities also emerges as a key factor in decision-making processes.Save this picture!Save this picture!In the 1990s, philosopher Pierre Lévy introduced the idea of collective intelligence — a form of knowledge that is distributed across individuals and contexts, drawing on the contributions of many to generate shared insight. In this view, everyone has something to contribute, depending on the context, and each contribution holds value. Collective intelligence, then, is based on mutual recognition and the enrichment of knowledge through collaboration.Recognizing the role of the collective in architecture, the concept of architectural intelligence evolves into something more holistic. It is no longer just about mastering tools, but about cultivating the ability to connect innovation with tradition, data with intuition, global with local — all while respecting the knowledge of individuals and regions. This shift reframes architectural intelligence not only as a technical skill but also as an ethical and political act. Designing today requires listening to materials, to places, to people. Intelligence is no longer something imposed on the world through rules or systems; it is something that emerges from dialogue with the world.This expanded understanding is especially urgent in the context of climate change, where architecture must draw on all available forms of intelligence — natural, artificial, and collective — to adapt. Fittingly, this is the theme of the 2025 Venice Biennale. Curated by Carlo Ratti under the title Intelligens. Natural. Artificial. Collective, the exhibition highlights the need for architecture to reach across generations and disciplines — from the sciences to the arts. As Ratti puts it, architecture must become “as flexible and dynamic as the world we are designing.” The Biennale features projects such as Living Structure, in the Natural Intelligence section, which explores what it truly means to build with nature. Led by architect Kengo Kuma, the installation investigates how traditional Japanese woodworking techniques, combined with AI, can turn irregular timber into structural material, pointing to a future that relies equally on reverence for nature and technological innovation. The Collective Intelligence section, meanwhile, focuses on how wisdom is built and shared through collective practices — from the favelas of Rio and refugee camps in Bangladesh to self-managed markets in Nigeria — showcasing urban ecosystems that reveal how material economies and social networks function in harmony.Save this picture!These and other initiatives suggest that architectural intelligence in the 21st century is less about seeking a single "perfect solution" and more about building networks of thoughtful, situated, and collaborative decisions. Intelligence is no longer an isolated technical attribute, but a relational quality — the ability to interpret the world through multiple lenses (technological, cultural, environmental) and translate that understanding into coherent, ethical, and responsive architectural solutions. In the balance between algorithms and ancestry, a new way of designing is emerging — one where intelligence is defined not by the tools we use, but by the quality of the decisions we make and the impact they have on people’s lives.Save this picture!We invite you to check out ArchDaily's comprehensive coverage of the 2025 Venice Biennale.This article is part of the ArchDaily Topics: What Is Future Intelligence?, proudly presented by Gendo, an AI co-pilot for Architects.Our mission at Gendo is to help architects produce concept images 100X faster by focusing on the core of the design process. We have built a cutting edge AI tool in collaboration with architects from some of the most renowned firms such as Zaha Hadid, KPF and David Chipperfield.Every month we explore a topic in-depth through articles, interviews, news, and architecture projects. We invite you to learn more about our ArchDaily Topics. And, as always, at ArchDaily we welcome the contributions of our readers; if you want to submit an article or project, contact us.