GIMP Development Update
Article URL: https://www.gimp.org/news/2026/08/16/dev-update-august-2026/ Comments URL: https://news.ycombinator.com/item?id=49326156 Points: 229 # Comments: 200
Latest News Archive - Page 137
Rare Pallas’s cat captured on camera in northern Iran mountains
Footage shows a rare sighting of one of Iran’s most elusive wild felines.
Superflow AI
AI agents that QA your website before launch Discussion | Link
Zambia incumbent takes early election lead as opposition alleges armed raid
President Hakainde Hichilema appears on course for outright win as observers cite violence and a tilted campaign field.
Ferrari's first ever electric car sold for record $40m
The Luce's launch drew backlash from some commentators who said it broke from the brand's signature dramatic styling.
Ebola outbreak in DR Congo becomes deadliest in country’s history
A top UN official says 'speed, scale, and solidarity' needed 'before this virus gets even further ahead of us'.
Yattayo
A physical slider to-do board, faithfully rebuilt in 3D Discussion | Link
Trump orders to scale back US-South Korea military drills
US President Donald Trump said annual military drills with South Korea send an "inappropriate and hostile" signal to North Korea.
Israeli settlers pitch tents for new illegal outpost in occupied West Bank
UN Special Rapporteur Albanese warns that Israel is 'using settlers to advance ethnic cleansing' in the West Bank.
Can the AU make its current Sudan mission count?
The African Union is seeking progress in Sudan, but must overcome deep battlefield and diplomatic divisions.
Ukraine war briefing: Kyiv could hit Russia with domestic ballistic missiles in months, former defence minister says
Mykhailo Fedorov says Ukraine is innovating its arsenal of weapons quickly; Moscow hit with ‘one of the most massive drone attacks’. What we know on day 1,637 Ukraine could be capable of striking Russia with domestically made ballistic missiles in three to six months , the former Ukrainian defence minister Mykhailo Fedorov has estimated. Kyiv has so far relied mostly on long-range drones and cruise missiles for deep strikes against Russia, but attacks with ballistic missiles will be far harder for Russian forces to thwart. In an interview with CBS News , Fedorov said: “We need to defeat Russia in every technological cycle.” Though Ukraine is innovating quickly, Fedorov warned that Russia is also advancing rapidly. Fire Point , a Ukrainian defence manufacturer, is developing ballistic missiles and conducted a launch test in June. Fedorov was one of the key drivers of Ukraine’s highly effective drone programme but was controversially fired in July. Ukraine on Sunday launched one of its largest drone attacks since the start of the war , causing a fire at a Wildberries distribution warehouse near Moscow and killing at least six people, according to Russian authorities. The defence ministry in Moscow said it had shot down 1,478 Ukrainian drones in the past 24 hours – the highest ever total claimed, Dan Sabbagh reports . Moscow’s regional governor Andrey Vorobyov described the overnight assault as “one of the most massive drone attacks in recent memory”. In the attack, Ukraine hit a missile fuel production facility in Russia’s Rostov region, the Ukrainian military said on Sunday. It said the company “manufactures solid rocket propellant for multiple launch rocket systems, as well as for a range of missile systems and airborne weapons”. A Spanish fighter jet on Sunday shot down a drone that had breached Romanian airspace near the border with Ukraine and Moldova, Nato said. The interception of the drone – which entered from Moldova – was carried out by an F-18, deployed on Nato duties, the Romanian defence ministry said. Debris fell in an unpopulated area of the Galati region, near the Ukrainian border. A growing number of drones have crossed into Nato states in eastern Europe as Russia pursues its invasion of Ukraine. The EU foreign policy chief, Kaja Kallas, has said she wants to increase by one-third the number of Russian entities sanctioned over the Ukraine war , German newspaper Die Welt reported on Monday. The bloc has adopted 21 rounds of sanctions against Russia since 2022. “For autumn I am putting forward the most far-reaching sanctions listings since the start of the war,” Kallas told the paper. “Once adopted, they would immediately raise the total number of sanctioned Russian entities by a third.” In July, the EU adopted a watered down sanctions package only approved after protracted negotiations among member states, after some objected to tougher measures. In Ukraine, a barrage of Russian drones and missiles on Sunday killed two people and wounded 14 at ArcelorMittal’s steel plant in Kryvyi Rih , the home town of the Ukrainian president, Volodymyr Zelenskyy. The plant, one of Ukraine’s biggest steel producers, said it had partially halted operations because of the strike. Another attack hit Kryvyi Rih on Sunday evening, killing one person. Strikes also killed two people in the Zaporizhzhia region. In Kyiv, a popular outdoor book market at Pochaina, long the place to find rare and antiquarian volumes, was hit by the Russian attack . Bookseller Dmytro Semenukha saw all four of his stalls burn to the ground. “There used to be a store. And books, and flags of all the countries, all the countries. Tons of everything. And that’s it,” the 45-year-old told Agence France-Presse. In a social media post on the overnight raid, Zelenskyy said that “wherever the Russians can reach with their ballistic missiles, they strike civilian infrastructure”. Over the past week, Zelenskyy said, Ukrainian cities had been pummelled by “more than 1,550 attack drones, nearly 1,560 guided aerial bombs, and 62 missiles” , as he renewed his appeal to allies for more air defence. Russian officials said on Monday that an overnight Ukrainian missile strike had killed six people and wounded another four, including a 14-year-old child, in the Belgorod region. Continue reading...
The Life and Death of Direct File [pdf]
Article URL: https://www.ischool.berkeley.edu/sites/default/files/vinton_report_5.pdf Comments URL: https://news.ycombinator.com/item?id=49325185 Points: 197 # Comments: 98
The federal keyword lists that canceled billions in research funding
Article URL: https://www.highereddive.com/news/inside-the-federal-keyword-lists-that-canceled-billions-in-research-funding/826203/ Comments URL: https://news.ycombinator.com/item?id=49325159 Points: 223 # Comments: 107
Trump says US to ‘substantially reduce’ military drills with South Korea
US president says he's 'not happy' about the drills, citing his 'very good relationship' with North Korea's Kim Jong Un.
Ebola outbreak in Democratic Republic of the Congo now deadliest in country’s history
At least 2,325 people have died from the virus, according to official data, with outbreak on track to be biggest in history The Ebola outbreak in the Democratic Republic of the Congo is now the deadliest in the country’s history, with at least 2,325 people dead, according to government data, surpassing the toll from the 2018-20 outbreak. The DRC’s public health institute said confirmed cases had risen to 4,945, including 101 detected in the previous 24 hours. Continue reading...
Israel releases 35 Palestinian prisoners back into Gaza
Emotional reunions greeted 35 Palestinians prisoners released by Israel into Gaza.
Markdown SVG upgrades
I started building my markdown-svg-renderer tool in May , but I've since added enough features to it that it's worth talking about here again. It's evolved into my ideal tool for sharing Markdown transcripts that include SVG documents. Given my proclivity for drawing pelicans riding bicycles this is a problem that I needed to solve! The tool is very simple. Navigate to markdown-svg-renderer in your browser and paste in some Markdown to see it rendered... or save that Markdown to a CORS-friendly URL or a GitHub Gist and paste in a URL to that document. The URL option will give you a bookmarkable page, for example https://tools.simonwillison.net/markdown-svg-renderer#url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F6f9e48293be5c916652d29f0dc0b0657 - which bakes in the URL to this Gist . If you visit the Gist you'll see raw SVG: In the rendered tool that looks like this instead: As you can see, that SVG block in the Markdown has been transformed into a rendered SVG (in this case animated) plus several tabs. The tabs are the really fun bit. The PNG and JPEG tabs render that SVG to those image formats in the browser and lets you copy or download them - useful for sharing on platforms that don't support SVG directly. The MP4 tab is new today - it examines the SVG to see if it contains any animations, attempts to guess how long the looped video should be, then renders a whole bunch of frames of the animation and loads 30+MB of ffmpeg.wasm so it can compile those frames into an MP4 video using the full power of FFMPEG compiled to WebAssembly and running in the browser. Being able to turn an animated SVG into a MP4 again makes it easy to share on platforms that can't support SVG animation natively. It's a neat trick! Tags: svg , markdown , tools
Hansel by Seedling
Your email, your server, your keys so you're not locked out Discussion | Link
US states call for big changes to Instagram and Facebook as Meta child privacy trial begins
US states are suing the social media giant to force an overhaul of its platforms for young users.
v16.3.1-canary.21
Misc Changes Anchor the async local storage instances to global symbols: #97255 test: deflake use-cache-size-zero warm reload: #97421 Scaffolding for concurrentRouterQueue flag: #97413 Reorganize client router modules: #97402 Credits Huge thanks to @unstubbable , @gnoff , and @acdlite for helping!
How switching your bank account could earn you up to £220
New research suggests staying put is costing British savers billions in missed interest every year.
Vendo
Let your users build their own features inside your product Discussion | Link
Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things
Friday's big release was Qwen 3.8 27B , an Apache 2 licensed 27B parameter vision-capable LLM from Alibaba's Qwen research lab. I've been looking forward to this one: 27B is an excellent size for running a model on a reasonably specced laptop, and its predecessor Qwen 3.6 27B was impressive. Qwen's self-reported benchmarks for this model are eye-opening. They show a boost from both Qwen 3.6 27B and the closed-weight Qwen 3.7-Plus, which was one of Qwen's strongest models of any size as recently as May this year . It will be interesting to hear what independent benchmarks have to say about the model. I've been running the model on two different machines: my 128GB M5 Max MacBook Pro, and an NVIDIA DGX Spark . On both machines I'm running LM Studio and their 17GB Q4_K_M quantized build . I also tried using llama-server directly on the Spark. The default of extra high results in spectacular over-thinking Qwen's documentation describes the model as defaulting to xhigh for the reasoning effort, and the LM Studio GGUF I've been trying preserves that default: Qwen3.8 comes with official support for reasoning_effort , which can be used to adjust reasoning depth and control cost: xhigh (default): for complex tasks demanding thorough analysis medium : balancing accuracy and speed low : efficient reasoning optimizing for speed and cost This is a hilarious default. It's absolutely not a good way to run the model, especially on consumer hardware. I've been finding the results extremely entertaining. I quickly ran into problems with LM Studio's default context limit of 8,192 tokens - Qwen was using them all up thinking about even the most mundane of problems. I loaded the model with the full 262,144 maximum context length and that problem went away. Here's the pelican riding a bicycle SVG I got from my first attempt with that increased context length. It took 21 minutes to generate, using 22,276 reasoning tokens to produce 3,223 tokens of output. You can read the reasoning trace here . This is by far the best pelican SVG I've been able to generate with a model that runs on a local machine - and this Qwen is pretty small, just a 17GB file on disk. There's a lot to like about this: The bicycle frame is the right shape It has legs on each side of the bike - that's very rare Good, clear pelican pouch The wings extend to touch the handlebars! The motion lines are behind, not in front It has a tasteful background - nice sun, clouds, hill, flowers and grass. Was that worth waiting 21 minutes for? Absolutely not. Here's that same prompt run with reasoning turned off - transcript here . This one produced 3,715 tokens and took 137s - just over two minutes. And just for completeness, I used OpenRouter to run the same prompt through the much larger Qwen 3.8 2.4T-A95B (released last week ) and got this snazzy animated SVG : Your browser does not support HTML5 video. I said Qwen at xhigh has a tendency to over-think things, but how bad really is it? I tried a much simpler prompt, again with that default extra high setting: draw an svg of a circle Qwen's reasoning trace started like this: The user is asking for an SVG drawing of a circle. Simple request — but I want it to be a carefully crafted piece. Let me make something that goes beyond just <circle> : a single self-contained SVG file with character — maybe a geometric "circle study," with subtle animation, layered rings, and a distinctive palette. Keep the scope right: they asked for an SVG of a circle. So the core is a circle. But I can add craft: concentric guide circles (like a compass/geometry drawing), tick marks, a soft gradient fill on the main circle, restrained ambient motion (a slowly rotating dashed ring, pulsing glow). Respect prefers-reduced-motion? That's more for CSS; SVG SMIL or CSS inside SVG will do. Palette options: deep teal ink on warm paper? Or bold vermilion circle on off-white with navy construction lines — Bauhaus/compass-drawing vibe. Let me go with a "geometric study" look: cool slate background, or bright paper white? Paper white is fine if it's not the cream-and-terracotta combo. [...] Several minutes later it produced this absolutely beautiful animated circle, which was entirely not what I had asked for! Your browser does not support HTML5 video. My strong recommendation: ignore that default. Run Qwen 3.8 27B on low or even no reasoning levels at first. It's a great model, but wow that default setting is a bad place to start. It's very good at bounding boxes A fun way to test a vision model is to see how well it can return bounding boxes around items in a photograph. I've seen previous Qwen models deal well with this, so I decided to put it to the test drawing bounding boxes around some pelicans. I've seen asking for 0-1000 scale produce good results in the past. I tried this: llm -a https://static.inaturalist.org/photos/714731804/large.jpg \ -m lmstudio/qwen/qwen3.8-27b \ ' Return JSON bounding boxes for the pelicans in this photo, 0-1000 scale for each dimension ' Here's the reasoning trace , which produced this: [ { "bbox_2d" : [ 195 , 290 , 370 , 780 ], "label" : " pelicans " }, { "bbox_2d" : [ 445 , 320 , 675 , 850 ], "label" : " pelicans " } ] This is such a good match . Here are those boxes rendered on top of the photo: Building a tool to label bounding boxes That visualization of the bounding boxes was taken using a new custom tool that I had Qwen 3.8 27B build for me, running offline on my laptop. I forgot to dial down the thinking effort so it was massively over-engineered , but it did manage to produce this full interface from this single prompt : [ {"bbox_2d": [195, 290, 370, 780], "label": "pelicans"}, {"bbox_2d": [445, 320, 675, 850], "label": "pelicans"} ] Build an HTML page which has an input box for accepting the URL to an image and a textarea for accepting the above style of JSON. It appends the image to the page, measures its width and height, then treats the coords in the bbox_2d as scaled from 0-1000 and scales them against the actual width and height, then it renders labelled boxes over the image. This screenshot shows one of the features I did not ask for - a demo scene, for if you don't have a photograph to test the tool with: Here's the relevant segment of the thinking trace, where it decided to draw its own pelicans purely because I had used the label "pelicans" in the example JSON I gave it in the prompt: Also a "load sample" that uses a known image? Can't depend on external images, but… the image URL input is user-provided; I could add a "try with sample" button [...] Hmm, I can draw a simple scene on canvas, export it as a data URL, and load it into the image — that's self-contained and demo-able! [...] But the user's coords are for an actual pelican image; a generated placeholder can still demo the scaling. Generate a 1000x1000 placeholder: gradient water + two blob-like "pelican" silhouettes placed at the given bboxes (using the same scale — cute: silhouettes at the exact 0-1000 positions, showing the boxes align). This makes for a fun, self-contained demo. Keep it simple: sky gradient, sun, water, two pelican-ish shapes (ellipse body, circle head, beak). Place at bbox centers. (I'm slightly nervous that models around the world might have a bias towards drawing pelicans at any chance they can get, brought on by nearly two years of exposure to my own stupid benchmark.) Is all that over-thinking necessary? Maybe it is, at least a bit. I tried with reasoning turned off and got this version , ( transcript here ), which nearly works but shows the boxes in the wrong place: So without reasoning it didn't quite one-shot a working tool. I'm sure it could get there with some follow-up prompts, but this is a good example of how reasoning can make a difference. Yes, it can drive coding agents One of the biggest questions around local models is whether or not they have enough horsepower to successfully run a coding agent loop. Coding agents require long context, strong code generation support and reliable tool-calling. On paper Qwen 3.8 27B has all three of these, so is it up to the task? My initial experiments with Pi have been very promising. I chose Pi because it has a shorter system prompt than most other options, making it a better fit for trying out smaller models. I configured Pi to use Qwen 3.8 27B running in LM Studio on the Spark (shared via tailscale serve ) by adding this to ~/.pi/agent/models.json : { "providers" : { "spark" : { "baseUrl" : " https://spark-18b3.tail68a31.ts.net/v1 " , "api" : " openai-responses " , "apiKey" : " dummy " , "models" : [ { "id" : " qwen3.8-27b " , "reasoning" : true } ] } } } Then ran pi --provider spark --model qwen3.8-27b in my ~/dev/datasette folder and prompted: how does auth work? After a sequence of reasoning and tool calls that accessed a bunch of different files it produced this reply , which is very solid. Just one problem: I wanted to share that transcript. So I pointed Pi and Qwen 3.8 27B at the JSONL transcript file in ~/.pi/agent/sessions/--Users-simon-Dropbox-dev-datasette-- and prompted: Write Python code to convert this jsonl to markdown And it built and tested this pi_jsonl_to_md.py , which did exactly what I needed. Here's that session transcript , published using the tool that it created. The quest for speed So far this is all looking very promising. We have a 17GB model that runs on high-end consumer hardware and can write code, drive tools, annotate images and generally do everything that I need from an LLM for getting real work done. There's one very significant catch: it feels slow - especially when it starts over-thinking, but even without that it's not particularly sprightly. I've been getting around 15-30 tokens a second from LM Studio. That's not terrible, but it's slow enough that it's going to be hard to win me away from hosted API models, which can return results a whole lot faster. Artificial Analysis track token speed and show OpenAI 5.6 Sol at 74 tokens/second and 5.6 Luna at an impressive 184/second. The good news is that the community have been exploring ways to speed things up since the model was first released two days ago. One of the most promising optimizations is baked into the model itself. Qwen supports Multi-Token Prediction , an architecture trick where a cheaper mechanism guesses several tokens ahead and the main model can then quickly verify if the guesses were correct. This can have quite a dramatic effect on inference performance. Based on this tweet from llama.cpp creator Georgi Gerganov I tried running the model with MTP like this on the Spark: llama serve \ -hf ggml-org/Qwen3.8-27B-GGUF:Q4_K_M \ -hfd ggml-org/Qwen3.8-27B-GGUF:Q4_0 \ --spec-default \ --spec-type draft-mtp \ --reasoning-preserve And sure enough, this gave me a significant boost. I had GPT-5.6 in Codex run a comparative benchmark on the Spark and the --spec-type draft-mtp server outperformed the LM Studio default GGUF by around 72%. I expect we'll see a whole lot more innovation around serving this model faster over the next few weeks. The MLX community likely have some tricks brewing as well. Some observations The fact that a 17GB file can do all of this stuff on my home machines is a miracle . Once again, I'm delighted and amazed at how much progress local models have made this year. A year ago this would have been competitive with the best and most expensive of the proprietary models - today it can run on a capable laptop. The only thing holding this back from being a daily driver is performance. It feels pretty slow on both the M5 Mac and the DGX Spark. That's the catch with these dense (non-Mixture-of-Experts) models - they require a whole lot of memory bandwidth to perform well, and neither of the machines I have access to are top performers in that regard. The most important thing about Qwen 3.8 27B is what it demonstrates . We can have an open weights general purpose model with a long context, effective tool calling, strong vision ability, and competent code generation, and we can fit the whole thing in just a 17GB file. The models at this size continue to get better at an impressive rate. We don't need to spend half a million dollars on datacenter-class hardware just to run a competent model. Tags: ai , generative-ai , local-llms , llms , qwen , pelican-riding-a-bicycle , llm-reasoning , llama-cpp , llm-release , coding-agents , lm-studio , ai-in-china , nvidia-spark , pi
What could stop Israeli settler attacks on Palestinians?
Violence in the occupied West Bank has intensified under Israel's far-right Netanyahu government.