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NVIDIA is reportedly working on a feature that could let future GeForce GPUs use an SSD as extra VRAM. When a graphics card runs out of VRAM, it could use data stored on a fast NVMe SSD instead. Your SSD won’t be as fast as real VRAM, but it could help when a game or AI app needs more memory than your graphics card has. That could mean fewer stutters and better performance in some situations. The feature is reportedly based on RTX IO and Microsoft’s DirectStorage technology.

A Japanese indie dev added full Czech language support to his Steam game after noticing a single person from the Czech Republic had wishlisted it The move earned tons of support from fans, and even Czech studio Warhorse who loved the dedication

Need a cool escape? Head to a cafe inside a karst cave in southwest China's Chongqing, where rich coffee, natural coolness, and a stunning cave interior make for the perfect summer retreat. #ChinaCool#

Pixar co-founder Edwin Catmull joins the Higgsfield Global Film Festival as a jury member. 5x Oscar Winner. Ex-President of Walt Disney Animation Studios. Executive producer of Toy Story. Turing Award laureate. The man who invented 3D graphics will judge the first generation of AI filmmakers.

Okay, the @VulcanBench results for Qwen3.8-Max are in, and it is not what I expected. First, for anyone new to VulcanBench, here's a quick TL;DR on the eval suite: 23 frontier-hard software engineering tasks taken from real merged OSS PRs, run in a Docker sandbox, 3 runs per task across all three of its effort levels. No puzzles, no random abstract stuff, all real things engineering teams would do with these models. It looks like Qwen3.8-Max has a major overthinking problem, it uses a LOT of tokens and is very slow, period, no other way to see it. My cost to run this benchmark was $126.25, to run the exact same eval suite with DeepSeek V4-Flash was only $13.60. This makes Qwen3.8-Max an insanely expensive model. The tasks Qwen genuinely can't solve fail at every effort level, extra reasoning didn't help. The regression is almost all in work it already handles: six tasks that low solves every single time account for 83% of the 26-point drop, three of them collapsing to zero. It's not losing the hard problems. It's losing the ones it already knows how to do. Since Qwen3.8-Max hit a lot of wall clock budget caps, I thought I'd share more about this. - VulcanBench caps both steps (50–200) and wall clock (5–60 min), each scaled by repo size. - This is aligned with how comparable harnesses bound agents, DeepSWE caps rollouts at 100 environment steps, sitting right inside my step range; Terminal-Bench enforces a per-task wall clock; SWE-bench Verified scaffolds typically allow 20–60 min per instance with 250–350 step limits. - Every model on my chart gets the identical budget, and Qwen is the slowest model I've tested at 20–25 min/task. Soooo... Alibaba positions Qwen3.8-Max as trailing only Claude Fable 5. But on the kind of real coding work engineering teams would actually throw at it, under a fixed budget, its best setting lands mid-pack and its default lands last, so common. If you want to optimize for accuracy, Grok 4.5 is the move. If you want accuracy per dollar, DeepSeek V4-Flash is hard to beat, heck it's 10× cheaper than Qwen and you get higher accuracy. Qwen just isn't in the game at this point, this is not a model I could see engineering teams using for daily coding work.

🚨 BREAKING: Apple filed for a PRELIMINARY INJUNCTION against OpenAI AND asked a federal judge to put them under forensic supervision "Apple respectfully moves the Court for a preliminary injunction to stop THE THEFT OF ITS TRADE SECRETS" Apple filed NINE sworn declarations, a 28-page memorandum and a concurrent motion for expedited discovery What Apple now says, under oath: Chang Liu: 8 years at Apple, now OpenAI "Member of Technical Staff" exploited an authentication bug to steal Apple trade secrets "on AT LEAST FIVE SEPARATE OCCASIONS" from February to April 2026, WHILE working for OpenAI Liu downloaded "THOUSANDS OF PAGES of Apple's most sensitive trade secrets" The stolen files, NAMED: >DisplayNotes.key — "several hundred pages" on Apple's custom display power development program >Architecture analyses. Fabrication decisions. Testing results >Engineering data for an UNANNOUNCED Apple product: 'touch, display, and power systems" >Final.key + V2.key — compilations of two undisclosed Apple R&D projects >and those are "only four of the dozens of proprietary documents Mr. Liu stole" Liu fed OpenAI "a steady stream of Apple proprietary information that he actively concealed" Liu also "coached Yu-Ting "Alyssa" Peng, then still INSIDE Apple, how to access and copy files from Apple workstations "to avoid trouble with the security team" and directed her to communicate with him on the encrypted LINE app "to avoid detection" Tang Yew Tan: 24-year Apple VP, now OpenAI's Chief Hardware Officer, "used an Apple internal project codename for an unannounced product to elicit still more trade secrets from job candidates." Tan's own messages, quoted in the motion: >"Just like last time, bring some parts you worked on" >"mlb, battery, shields type of stuff is interesting" OpenAI recruiter, quoted: "No, you won't sign anything at the exit interview. If they do ask you to sign anything, let me know asap." APPLE TOLD FEDERAL JUDGE: >"OpenAI knows its misappropriation is wrong and has tried to conceal it." >"This is not a case of 'mere hiring'... it is a case of repeated instances of deliberate theft." Apple says OpenAI went after its SUPPLIERS: >OpenAI "directed a trusted Apple partner [name redacted] to perform [Apple's proprietary metal finishing] process for them, knowing it was proprietary to Apple... because they were involved in this partnership while at Apple." Apple put its own Surface Finishing Manager, Jackie Hughes, under oath to prove it. Apple named ELEVEN MORE former Apple employees at OpenAI — beyond Liu, Tan, and Peng — Fourteen people total. Apple also filed a concurrent motion for EXPEDITED DISCOVERY demanding depositions: - Liu. Tan. Peng. - A fourth unnamed OpenAI employee - Plus OpenAI itself, under oath, through Rule 30(b)(6) Apple has asked a federal judge to put OpenAI under forensic supervision RIGHT NOW: >Forensic inspection of ALL OpenAI devices >ALL cloud storage, Slack, email >Including anything that "previously contained" Apple data — deleted included Demanding the "first available hearing date," citing "imminent threat" to its trade secrets. APPLE: > "The harm is happening now — every day that passes without an injunction allows OpenAI to embed their knowledge of Apple's stolen information into its hardware development efforts." Hearing: October 1, 2026. Judge Edward J. Davila. ITS HAPPENING