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Here's our second wave of Xbox Game Pass games for October 2026
The second batch of Xbox Game Pass games this month includes the console debuts of two genuine corkers.
Coming to XBOX Game Pass: Final Fantasy VII Remake Intergrade, The Séance of Blake Manor, and More
Ghosts to question and a planet to save. Sounds like a perfectly reasonable few weeks to me! We have another batch of games coming soon to Game Pass, so clear a little room in that “Play Next List” and let’s get to it!
Readers Are Pleading To Make American Healthcare Greater
KFF Health News gives readers a chance to comment on a recent batch of stories.
New batch of Zelda 40th Switch 2 console and Pro Controller contain replaceable battery
UK video game and toy retailer Smyths have just received a new batch of stock of the Zelda 40th anniversary Nintendo Switch 2 console and the Zelda 40th anniversary Pro Controller and these new…
Supermassive Games Layoffs Arrive With Over 70 People Let Go
More than 70 people have seemingly lost their jobs at Supermassive Games, as another batch of layoffs hits the gaming industry.
VB Health Launches Public Seven-Part Supplement Quality Standard
New company-wide standard, effective across the VB Health portfolio, establishes requirements for research, clinically relevant dosing, formula transparency, sourcing, U.S. manufacturing and every-batch testingDENVER, Oct. 03, 2026 (GLOBE NEWSWIRE) -- VB Health, a Denver-based dietary supplement company co-founded by a U.S.-licensed physician, launched the VB Health Supplement Quality Standard today, a new public seven-part framework that establishes company-wide requirements for how its supplem
Sunland Park residents raise health concerns over proposed concrete plant near homes
Residents living near the intersection of Pete Domenici Hwy and McNutt Rd in Sunland Park are concerned about a proposed concrete batch plant near neighborhood.
Apple TV just added a bunch of free classic movies, here’s everything new
Apple TV keeps adding new batches of classic movies to kick off each month, with 13 fresh films available free for subscribers today.
CAS launches program for breakthroughs at science frontiers
The first batch of 10 projects under the program was unveiled at the media event, targeting research in fields such as the synthesis of new elements, the nature of dark matter and dark energy, microscopic measurement of chemical bonds and the creation of synthetic cells.
This year's MacArthur Fellows include researchers who fuse science and justice
The MacArthur Foundation has just announced its latest batch of 20 fellows. Among the recipients of the $800,000 "no-strings-attached" fellowships are researchers who were recognized for their work at the intersection of science and justice.
New Pokemon Winds and Waves leaks have emerged, including the map, possible look at the Champion, more
Just when you may have thought that the major Pokemon Winds and Waves leaks were over, a new batch falls into our laps. The latest round of leaks comes from X user @grubbinscrubbin. A number of different images were posted online from the game’s beta, including what might be a look at the Champion. Note that everything is based on...
5 novels that offer horror and thrills for the season change
This batch of horror novels comes with plenty of reasons to keep the lights on — may your fictional nightmares stay safely between the covers.
MediaTek’s flagship laptop chip is the Dimensity CX C10 Max, debuts in a Lenovo Googlebook
The initial batch of Googlebook laptops that debuted earlier today use either Intel or Qualcomm chipsets, but MediaTek has confirmed...
Heat Rotom ex, Kommo-o, Zinnia's Trust, and More English Cards...
The first batch of English cards from Delta Reign has been revealed! The set will release on November 6th. As posted before, our set will be a combination
Latest batch of Nintendo Switch backwards compatibility fixes for Switch 2
Nintendo has been striving to get all third party Nintendo Switch games up and running and compatible with the Nintendo Switch 2. The company has been working with third party developers to ensure any…
Nintendo has issued new batch of Switch 1 backwards compatibility fixes for Switch 2
Nintendo has now released new Switch 1 backwards compatibility fixes for Switch 2, and here's the full list.
Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading
Engram extends standard token embeddings with learned multi-token lookups. Recurring local patterns retrieve vectors directly, reducing the need to reconstruct them through attention and feed-forward layers. With Engram model architecture optimization, it allows for lower HBM capacity to be needed for models at the same quality. This does not mean there won’t be an insane demand for HBM but it just means that model architecture will continue to innovate around constraints. This model architecture design is naturally codesigned for parameter offloading: each token accesses a few embedding rows whose addresses depend on token IDs, not hidden states. The runtime can prefetch those rows from host DRAM while earlier layers compute, keeping the table outside HBM without transferring entire weight matrices. Our Memory model contains our latest estimates of quarter by quarter HBM, DRAM, & NAND supply and demand. Offloading frees HBM for model weights and KV cache, potentially supporting larger batches or more concurrent sessions. When DRAM becomes the next constraint, NVMe offers another tier. Recommendation systems already cache frequently or recently accessed embedding rows in faster memory while backing colder rows with SSDs. After NVIDIA roadmap had to change due to massively despec’ing Rubin Ultra from 1024GB to now ~200GB of HBM per chip, model architecture optimizations like emgram maybe helpful. Our DeepSeek-V4.1-Flash configuration uses roughly 189 GiB of memory for Engram. We replace it with a memory-mapped (mmap) file and measure serving performance with offload to SSD. Later on in our report, we will show our Engram offloading experiments along with the official InferenceX agentic inference serving results on Engram models like DeepSeekv4.1 Flash across all 6 NVIDIA GPU SKUs along with MI355X. Unsurprisingly, the CUDA Moat is still mogging MI355X on the ultra popular DeepSeekV4.1 Flash model. We also show how even on high capacity HBM SKUs, offloading emgrams to DRAM could result in even better performance for most of the pareto than keeping the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario is to real world agentic inference workloads, AMD has committed to collaborating on MI455X UALoE72 too. DeepSeek did not release the original paper’s two trained Engram models. We replicated its setup on fineweb-edu using the released code and training hyperparameters, at an estimated 6E18 FLOPs per run. We observed the same U-shape scaling: Engram improved performance over pure MoE baselines. We also reproduced DeepSeek’s results, where earlier-layer representations with Engram resembled those of later layers. Like the original Engram paper, it is possible to probe Engram’s gate scores to see what n-grams DeepSeek-V4.1-Flash makes the most use of. Our gate scan finds names, code fragments, relational phrasing, and boilerplate. These examples prioritize interesting-ness over gate strength. One unexpected result was Wright : Ace Attorney. These examples suggest learned memory optimizes the training objective, not a judgment of which facts deserve storage. Licenses, bibliography fragments, API scaffolding, and website furniture can provide prediction shortcuts, so the value of additional Engram capacity may depend on what survives data preparation. This does not show that table capacity is “wasted”: the evaluation-corpus scan establishes neither training exposure nor the capacity occupied by each category. For offloading, strong gates do not identify cache-hot rows. Low gates do not automatically save reads either: computing the gate requires the retrieved key and undoes the performance gain of a fused kernel. Skipping reads would require a separate usefulness predictor before retrieval. In the original paper’s inference-time ablation, factual-knowledge benchmarks retained just 29–44% of their original performance, while reading comprehension retained 81–93%. This is due to the training–inference mismatch. The resulting degradation therefore measures this trained model’s dependence on Engram, not the performance difference between models trained with and without it. In our ablations, suppressing Engram worsens token likelihood across all evaluated domains, especially encyclopedia text and several code corpora. Surprisingly, GSM8K accuracy stays within measured run-to-run variation and removing Engram has no effect. Engram is not a detachable dictionary beside an unchanged MoE. Removing it changes downstream features and expert selection. We tested whether rerouting hurts or compensates by holding tokens fixed in a teacher-forced experiment on CRUXEval, a code-reasoning benchmark of small Python functions where the model predicts a function’s output from its code and an input, and scoring the reference answer. Removing Engram raised answer loss from 0.2848 to 0.3093 bits/token. Forcing the ablated model to use the original Engram-on expert choices made it worse still, at 0.3375 bits/token. Rerouting partially compensates for the missing memory. Memory features and expert selection work together, rather than following a clean “memory stores facts; experts reason” division. On the same CRUXeval, removing Engram during either phase reduced accuracy and increased generated tokens; removing it throughout produced the largest changes. Keeping Engram for prefill leads to more correct answers than keeping for decode likely due to semantically richer KV cache transferred to decode workers, allowing it to mitigate some of the performance loss. Engram’s table is large, but each lookup is small. DeepSeek-V4.1-Flash requests 24 rows at each of two Engram layers, about 12.4 KiB per processed token position across the model, or 3.1 KiB per GPU when split across four GPUs. Currently as of Day 7 since Model Release, MI355X is still 2-4x worse performance per dollar compared to B200 even when normalized by Mi355X’s lower TCO. Our full total cost of ownership breakdown comes from our AI Cloud TCO Model along with monthly market surveys of over 100+ gpu clouds & gpu cloud customers. On the Day 0 release of DeepSeekv4.1 Flash, NVIDIA vLLM works out of the box with zero issues across all 6 SKUs: H100, H200, B200, B300, GB200, GB300! This was thanks to the amazing work by the NVIDIA & Interact teams! In comparison, AMD vLLM did not work on day 0 for DeepSeekv4.1 Flash.Source: SemiAnalysis InferenceX AMD’s vLLM documentation points to using vllm/vllm-openai-rocm:deepseekv41-flash-0909, but from hour 0 of the model release to hour 23, AMD has not publicly released the image. AMD claims, “SPEED IS THE MOAT,” yet it has still not released it by the 23rd hour. We wish that, going forward, the AMD team has a better process for hour 0 model releases. Eventually when they did publicly release for “day 0” image support, performance-wise, it is currently up to 14.8x worse perf per dollar than H200 and up to 42x worse perf per dollar than B200/B300. The power of the CUDA MOAT is NVIDIA’s collaboration with its massive 6 million-developer community ecosystem including most of the vLLM & SGLang & Tokenspeed maintainers which means that CUDA is optimized on day 0. Overall, AMD did make significant improvements but the performance per dollar is still currently 2-4x worse than B200. AgentX Engram DRAM Offloading Improving Performance The HBM and DRAM offload use the same GPU kernel to select and dequantize rows. With HBM, it reads GPU memory; with Unified Virtual Addressing (UVA), it reads pinned host memory directly. Both support full decode graphs. Moving the table into HBM accelerates only the sparse lookup, leaving decoder computation and communication unchanged, resulting in little overall benefit while consuming memory otherwise available to KV cache. Another benefit of Engram offloaded to DRAM which means you can reduce the communication overhead by using less HBM GPUs per replica. For example, when enabling Engram offloading on B300, we are able to switch from TP4 to now TP2 which improves the pareto curve by up to 1.6x. When iso-model quality, less HBM is required as the engrams could be offloaded to host DRAM. Thus HBM bandwidth matters way more than HBM capacity. For inference workloads where memory bandwidth matters the most, 4-hi HBM provides the best $/bandwidth and therefore lowest cost per token. If China continues to make more and more revolutionary model architecture innovations, soon it could potentially 0Hi HBM stacks. [ ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) [ Long Live the Short King: Why 4-hi HBM Wins ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Myron Xie, Bryan Shan, and 3 others · Sep 13 [ Read full story ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Moreover, on B300 and week-0 stack, moving the Engram table back to HBM did not improve results and stay within run-to-run variance. This is a result of the work optimizing DRAM offload, such as async, and overlap. SSD Offloading On B200, we created a unoptimized vLLM fork and stored the Engram tables in memory-mapped files on local SSDs. File backing lets the OS reclaim table pages when other applications need RAM. Pages already cached in memory can be served without reading the SSD again. Furthermore, note that we were unable to turn on GDS The unoptimized SSD implementation changes how rows reach the GPU. It copies row IDs to the CPU, deduplicates them, gathers the requested rows into pinned buffers, copies those rows back to the GPU and dequantizes them. This work runs between segments of the GPU execution graph. Native UVA performs row selection and dequantization directly on the GPU, avoiding the CPU round trip. A warm filesystem cache removes physical SSD reads, but leaves the coordination, row gathering and transfers. This is why a file already cached in RAM can still perform worse than a pinned DRAM table. The comparison measures the whole serving path; it does not separate the time spent on each of these operations. B200 DRAM dominates both measured SSD serving curves in total tokens per dollar and P90 interactivity. Near 125 tokens/s/user, DRAM delivers 121 million total tokens per dollar versus 52 million for SSD. For production serving, SSD offloading is likely not worth the tradeoff. On the B200 configurations we measured, SSD offloading loses on both measures: every observed SSD point has a DRAM alternative that delivers higher P90 interactivity and more total tokens per dollar. The only points where Cheaper storage does not automatically produce a cheaper inference service. Moving Engram to SSD leaves the same four expensive GPUs and the rest of the server in place. Reclaiming RAM only creates an economic benefit if it enables a cheaper server configuration or additional useful capacity. The current unoptimized path provides neither benefit, and the filesystem cache still consumes RAM when table pages are resident. Next we will look at the mechanisms and specific implementation of ngrams from DeepSeekv4.1 Flash, LongCat, Qwen3.8 Flash Next.
Two Washington Nationals Execs Recognized Among Best Across MLB
A pair of Washington Nationals were recognized among the next batch of rising executives across the MLB heading into the offseason
Zingerman’s candy business breaks out with its sights set on national growth
The Ann Arbor-based small-batch confections business has a new managing partner and Ecuadorian chocolate supplier.
BUSINESS SPOTLIGHT: Get messy at Slime Time Studios Marblehead
The following is an interview with Stacey Barnes, co-owner of Slime Time Studios Marblehead, conducted by Discover Marblehead. Slime Time Studios MHD on Spring Street offers a fun, hands-on experience where kids can create their own craft project and mix up a custom batch of slime. With plenty of opportunities to personalize their creations, kids
5 Small Business Ideas for People Who Want a 4 Day Workweek
These small business ideas allow for longer weekends by batching jobs, charging recurring fees, or concentrating work on a given four-day period.
NJ readying ballots amid questions about Caldwell, vote-by-mail
As Trump postal changes head to the nation's highest court, officials stick to deadline to send first batches for midterms
Vermont awards first batch of $195 million in federal rural health funds
Rural workforce development and nursing homes receive the first round of $11.7 million in funds.
South Tampa fire damages 4 businesses, owners face long recovery
A batch of businesses in South Tampa are on a long road to recovery after a fire.
15 discouraging hours with Onimusha: Way of the Sword, and 10 brilliant ones with He Who Watches
In the last few weeks, while playing some video games that I might review, I emailed two cries for help. I sent the first to a rep for Capcom, confessing that the company’s samurai game Onimusha Way of the Sword (out today for PC and console) was crushing me. “Feels like I’m playing ‘hard’ mode, not ‘normal,’” I wrote. “And I don’t want to have to knock it down to “story”. I’m exploring, trying to level my gear, but these two-phase boss fights with no mid-fight checkpoints are brutal.” I wagered I was only about halfway through the game, if that. I wasn’t sure I could keep up with the steepening difficulty curve. Was I missing something? Then, on Monday, I took some photos of some puzzles that were baffling me in the mind-bending He Who Watches (out now on PC), wrote out lengthy descriptions of how I’d been trying to solve them and asked Bobby Vanden, the game’s solo developer, for a nudge in the right direction. I told Vanden I’d spent hours on these puzzles. “I’m stuck in triplicate,” I told him. Could he tell me if the solutions I was attempting were even on the right track? I didn’t mention that the puzzles—coupled with major time pressures from other work—were stressing me out so much that playing the game was giving me headaches. This double dose of panic was unusual. I’m used to managing a workload full of reporting and reviewing, used to a crowded schedule and the need to stay calm amid the bustle. But I was stressed about these games. No one was forcing me to review them, nor even play them. I’d simply found them interesting enough to start, hoped they’d be interesting enough to write about and I’d sunk hours into them assuming I’d made the right call. Suddenly, however, I felt trapped. I was emailing for a way out. Above: This guy took me about an hour to beat. The feedback I got from Capcom confirmed my fears. They didn’t say it, but I will: Onimusha Way of the Sword is not for me. It’s a brutally hard game in need of a normal difficulty level. It’s a game that spikes so severely during its abundant boss fights—yet offers such flawed ways to improve when outside of them—that it feels like a bait-and-switch. In the new Onimusha, you play as famed samurai Musashi Miyamoto, aided by a magical soul-absorbing gauntlet that is possessed by a lady who offers advice. (Way of the Sword is a continuation of Capcom’s long-dormant Onimusha series, but that set-up had me wondering if the company was cribbing from their ill-fated Bionic Commando reboot; read about “wife-arm” when you get a chance). Way of the Sword is partially set in 17th century Kyoto, an explorable city where Miyamoto can fight demons, help civilians and eventually rescue ghostly dogs. The city evolves over time, with new mini adventures and obtainable loot on offer, all feeding into systems that promise to upgrade your gear and sword-fighting skills. Upgrades, however, are so incremental as to be imperceptible, causing the exploration of Kyoto to feel like inconsequential busywork. From that hub, players can go on linear missions into forests and old temples, where they will encounter many of the game’s tough bosses. Combat in Way of the Sword is akin to many modern melee games. Players are asked to mix attacks with dodges and parries. They’re encouraged to deplete an enemy’s stamina bar in order to do greater damage to its health bar. The old Onimusha games’ signature move was the issen, a counter-attack so sudden it’s all but pre-emptive. You strike just as they begin to strike toward you, beating them to the cut. By definition, the issen is a high risk move, leaving you wide open to pain. It feels risky in the game, especially against bosses, who can maul you in just a few blows. A game might train you to perform an issen well by offering a variety of lesser enemies who are not as tough as the boss but get close. Or it might offer a toehold against bosses by saving or checkpointing the player’s progress when a boss’ first health bar has been destroyed and before the second health bar appears. It might offer the less skilled player a chance to over-level their character, should the player simply commit to playing through its optional sidequests. Way of the Sword does none of this. Fighting its trivially easy grunt enemies and then its ferociously adept bosses is like playing a game of chess where I’ve got a rook, while the opposing side is all pawns and five queens. Bosses simply don’t checkpoint. You may be able to clear a boss’ first phase without taking much damage. Good for you. Do it again, every time you fail the second phase. As for the the central Kyoto hub, I kept pace with all of its added side activities and never felt like I was overpowered. Bosses could still easily buckle me. The new Onimusha, I concluded, is just too discouraging to keep playing. The advice I got from Capcom had been well-intentioned. They reminded me of the game’s various systems. They alerted me to an optional assist that flashes recommended button inputs (basically: counter this move; dodge that move). It was a little helpful. So was dropping down to “story mode,” which I tried last night. Story mode turns on those button prompts by default. It makes countering and dodging way too easy, nearly automatic. I don’t consider myself a master of action games like these, but I’ve cleared the likes of God of War, Stellar Blade, Star Wars Jedi and others of sub-Sekiro difficulty and had a fun time doing so. Not here. Not yet. Unless they patch Onimusha: Way of the Sword and add a middle difficulty or just checkpoint the damn bosses when they’re between health bars, my streak of loving Capcom games released in 2026 will likely end at two. It’s a shame, because I was having a good time finding those ghostly dogs. And then there’s He Who Watches, a phenomenal first person puzzle game with Portal vibes, except instead of a portal gun you’ve got a magical bow that shoots one arrow that can activate switches or be used to drag blocks. The twist is an actual twist: you can also walk on walls and the ceiling, reorienting gravity as you do, thereby placing blocks onto those other surfaces. Walking on walls and ceilings to solve problems is really the best thing. Would that I could in reality. He Who Watches consists of locked-room challenges, each brief enough to only require about a minute to actually solving, though it will take five, 10, eventually 30 minutes to figure out said solutions. They are not obvious! It’s a game of layered mechanics and shocking solutions. For example, see if you can follow this: You can drag a block to a wall. Then you can walk on the wall, which now feels like the floor, and drag that block across the wall. Later, back on the floor, you might realize you can look up. The block is still on the wall, stuck to it. You can shoot your magic arrow to its underside. Doing so creates a tether, so that you can yank the block off the wall and carry it, as if it were a balloon, into the spot where you need it to be to solve the puzzle. Here, watch Vanden explain some of the game’s basics in this launch trailer: As with any great puzzle game, the solutions to He Who Watches’ puzzles elicit relief and amazement. Oh my god, that worked! I didn’t even think that could be possible! Learning to solve the game’s puzzles feels like learning magic. But, oh, does the game get hard. Its Steam reviews, mostly glowing, are full of players remarking how quickly He Who Watches made them sweat. Wrote one: “loving this one already although my brain is hurting!” Wrote another: “As you get further in the game it feels like you need an IQ level of at least 120+.” Vanden has shown some mercy. Each locked room puzzle includes an optional junior version of the puzzle, meant to teach you. Difficulty nevertheless ramps severely. By the time I was emailing Vanden for help, I was struggling to even clear one of the hint puzzles. When I messaged him, my stress was exacerbated by strange things I’d found in the game’s various hubs: suspicious passageways, odd blocks and some intriguing locked doors. These were hints of secrets, I realized, yet I sensed I needed to play further into the game to understand them. I was stuck, but I wanted to see the rest. Vanden offered to give me the exact solutions, to solve those three puzzles for me, but first he gave four nudges. Three were for the specific puzzles, but his best hint was for all and ultimately proved to be a terrific life lesson: go back a bit, he suggested. Do the puzzles right before those. They were teaching you something. Focus on what their lesson was. Don’t rush, in other words. Recognize what you’ve accomplished. Build off of that. I did so. I absorbed the lessons. I saw those three tough puzzles in a new light. I solved one the night after he wrote back, another the morning after. I left a third for another time. I didn’t need it and I wanted to plunge deeper into the game, closer to the moment when I was sure I could start unlocking those secret doors. My head stopped hurting, too. He Who Watches feels special. It’s got more challenges, and I’m undeterred. It’s also nice that its puzzles don’t have a surprise second health bar. Game File is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe Item 2: In brief… 🎮 Ilari Kuittinen, co-founder of Helsinki-based Housemarque (Super Stardust HD, Resogun, Returnal) has stepped down from his studio, after a 31-year run, saying he’s “ taking a rare and well-deserved breather.” Sony purchased Housemarque in 2021, and the studio released its newest game, Saros, earlier this year. Trend-watch: Sony-owned Insomniac saw its founder Ted Price retire in early 2025, after a 30-year run. Sony-owned Sucker Punch saw its co-founder Brian Fleming step down in late 2025, after a 28-year run. 👀 Savvy Games Group chief Brian Ward is stepping down from the Saudi-government-backed games conglomerate, Bloomberg reports. No word on a long-term successor yet, nor if this augurs any closer integration between Savvy and Electronic Arts. EA was purchased by a consortium led by Saudi’s sovereign wealth fund, in early August. 💿 Square Enix has denied a Japanese media report that the company was planning to go private. In very different Square Enix news, the company revealed that the physical version of Final Fantasy VII: Revelation, the April 2027 finale of its radical remakes of FFVII, will include just one disc in its case, requiring a download for the rest. The first two FFVII remakes in the trilogy shipped on two discs apiece. While Square hasn’t commented on the reason why, a feature here in Game File last month broke down the processes and costs for physical games. The expense of a second disc comes out of the game publisher’s cut of each copy. Square could be saving in excess of a dollar a copy with this move. 🟥 Grand Theft Auto IV’s 26-minute ’‘extended look” gameplay showcase that premiered on Netflix last week—and was exclusive to the platform for six hours—drew 31.1 million views in its first four days, the streamer announced. (Netflix calculates views as total viewed hours divided by runtime; excludes replays). Compared to YouTube: The version that later premiered on Rockstar Games’ YouTube channel is sitting at 22.6 million views after seven days (YouTube’s more liberal counting system tallies anyone who viewed even just the first few second.) Compared to other Netflix mega-events: Last year, Stranger Things season 5’s first four episodes, which debuted together, drew a record 59.6 million views in their first few days on Netflix. For more of a live event type of comparison, in 2024, the Jake Paul vs. Mike Tyson boxing match drew 65 million concurrent streams as it happened; Netflix didn’t release live numbers for the GTA premiere. ☁️ Microsoft is changing the way it charges for cloud gaming, from an all-you-can-play offer for Xbox Game Pass subscribers, to caps for the subscription’s tiers (15 hours per month at the Ultimate tier), with the option to buy more hours in bulk beyond that. The company also said it will sell batches of cloud gaming time to non-Game Pass subscribers, details TBA. Microsoft does not release figures for cloud game usage, but said its changes would impact 4% of Game Pass subscribers. That implies a small portion of its subscribers exceed the 15-hour monthly mark. Cloud gaming offers the promise of playing games without the need for console or PC hardware, as the graphics, sound and controls are all transmitted via a streaming connection. Microsoft notes that its cloud gaming service can be used for a range of things, including Xbox One players using it to play newer-gen Xbox Series games via streaming; and people playing games via streaming, sans any console, “in markets where consoles are less available or affordable.” (That latter use case could even be relevant in Xbox’s home market soon, as console prices keep rising.) Take Two Interactive chairman Strauss Zelnick recently told investors he expects game-streaming tech, which has been only lightly adopted by gamers for over a decade, to be widely used within three years. 🇺🇸 The Trump administration has published multiple agenda-driven web video games to the White House’s website. One called Build The Wall partially clones Tetris as it asks players to build a wall to stop a “zombie border siege.” While actual Tetris involves clearing lines and basically not building a wall, the Trump-backed game omits the line-clearing aspect (and omits the fun as well). On Instagram, Tetris’ official license holders reacted by stating: “At Tetris we believe in the power of connection and bringing people together, not dividing them. To our fans everywhere: we love you, we see you, and we’re grateful to have you in our community. P.S. The Tetris Company was not involved in the creation of ‘Build the Wall.’ P.P.S.: We take copyright infringement very seriously.” Item 3: The week ahead: Tuesday, September 8 Game releases: Mewgenics (consoles; already out on PC) is an engrossing tactical combat game (with cats). It is getting its console port right after the release of a Star Wars tactics game and ahead of the late September launch of a Fire Emblem–a bumper crop for the genre. Wanderburg (PC) is an auto-shooting game like Vampire Survivors, but you’re a castle on wheels Event: Nintendo airs a 30-minute Nintendo Direct (10am ET) focused on The Legend of Zelda’s 40th Anniversary. A full unveiling of the upcoming remake of The Legend of Zelda Ocarina of Time is expected. Will they also show footage from next year’s live action movie? Tease the next big 3D Zelda? Add Link to Mario Kart World? Shadow-drop a new Tingle game? Wednesday, September 9 Event: Nintendo again! On this day, they’re planning to air a 45-minute Nintendo Direct (10am ET) focused on games heading to Switch 2 this winter. Followed by about an hour of gameplay demoed by the company’s Treehouse team. The September Nintendo Directs are always some of the year’s biggest. The 2025 edition included announcements of several major 2026 Switch/Switch 2 games: Pokémon Pokopia, Mario Tennis Fever, Yoshi and the Mysterious Book, Fire Emblem Fortune’s Weave. Plus the return of the Virtual Boy. Friday, September 11 Game release: EA Sports NHL 27 (PlayStation, Xbox) is a hockey game. There are so few that an indie studio that had been making wacky sci-fi first-person shooters just announced that, hey, we’re going to fill a void and make a hockey game for PC.
Newsom says he plans to endorse in S.F. House race
Gov. Gavin Newsom plans to endorse in the San Francisco congressional race to replace Nancy Pelosi, and that he would likely do so as part of a batch of endorsements in California races.
All 16 new Russian Starlink-rival satellites short of target orbit
The 16 satellites form the second batch of the Rassvet-3 constellation, which now only has 12 out of 32 launched satellites set for long-term orbit.
LZ Sees Surprising Result in Search for Dark Matter
Key Takeaways Dark matter is the mysterious substance that accounts for the vast majority of matter in our universe. LUX-ZEPLIN (LZ) is a world-leading dark matter detector and specializes in searching for WIMPs, or weakly interacting massive particles. A new LZ study found one particle interaction that is difficult to explain with known background processes and could potentially have been caused by a WIMP. LZ continues to run to see if additional data strengthens or weakens the hint of a dark matter interaction. For the better part of a century, people have been trying to understand dark matter. This invisible substance makes up roughly 85% of the mass in the universe but has never been directly detected. Determining exactly what it is remains one of the biggest questions about our world. Now, a new analysis from the LUX-ZEPLIN (LZ) experiment has recorded a single particle interaction that researchers have great difficulty explaining with known background signals from normal matter. The result does not yet meet the statistical threshold required to claim a discovery, but is the most compelling hint of dark matter reported by the experiment to date. LZ is an international collaboration of 250 scientists and engineers from 39 institutions. The detector is managed by the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) and operates nearly one mile below ground at the Sanford Underground Research Facility (SURF) in South Dakota. The experiment uses 10 tonnes of ultrapure liquid xenon to search for dark matter and is optimized to look for WIMPs, or weakly interacting massive particles. The results were presented in a scientific talk at the 2026 TeV Particle Astrophysics conference in Japan. The paper will be released on the online repository arXiv and submitted to the journal Physical Review Letters. “We’re very intrigued to see this event in the data, in the region where we expect dark matter to show up and the competing backgrounds are very low,” said Rick Gaitskell, a professor at Brown University and the spokesperson for LZ. “With only one event, we don’t want to get ahead of ourselves. We are not claiming to have seen dark matter. But we have seen something interesting that we want to share with the scientific community for their input.” The LZ collaboration studies experimental data in batches. In the new result, researchers analyzed 220 live days of data collected between March 2023 and April 2024. The collaboration had previously searched this dataset for faint signals from the simplest kinds of WIMP interactions. The new analysis searched for a broader range of possible WIMP interactions that could deposit more energy in the detector. LZ is particularly sensitive to such signals while also minimizing false positives. “This was a detailed study in a region we hadn’t explored within this dataset, and we spent months of additional effort to understand all the possible causes of background events,” said Sam Eriksen, a senior research associate at the University of Bristol in the U.K. and lead author of the study. “We understand our detector and the backgrounds so well that even a single outstanding event, like the one we found, is important. We expect dark matter events to be extremely rare, so only a handful could mark the first detection of WIMP dark matter.” If the anomalous event was caused by dark matter, the WIMP that generated it would likely have a mass of at least 200 GeV/c2 (gigaelectronvolts), or more than 200 times the mass of a proton. It would also suggest a specific type of interaction between WIMPs and ordinary matter beyond the simplest model. The LZ results have not reached “5-sigma” significance, the statistical threshold considered a discovery in physics. The new analysis is 2.6 sigma, meaning there is approximately a 0.5% chance that the event could be explained by known backgrounds. With additional data, researchers can test whether the finding continues to grow in significance or fades away. LZ has already accumulated the world’s largest dark matter dataset and will continue to accrue WIMP search data at SURF, substantially improving their search statistics. LZ searches for dark matter by looking for signature flashes of light from energy deposited in the detector. The collaboration leverages multiple methods to prevent or account for particle interactions caused by normal matter. This includes the mile of rock that shields the detector from cosmic rays from space, a water tank and outer detectors that protect the central detector from background neutrons, and a suite of computational tools that disentangle particle interactions and reject dark matter mimics. “Outlier events in the data are not unexpected, but they usually stand out as a background of some kind when you look at them deeper,” said Aaron Manalaysay, a physicist at Berkeley Lab and the chair of LZ’s Institutional Board. “This is the first example in any experiment I’ve worked on of an outlier that appears valid in every way. Of course, we’re still twisting our brains trying to think if there’s a rare background mechanism we could’ve missed, but it’s thrilling to wonder if this could be the first hint of a dark-matter observation.” LZ is supported by the U.S. Department of Energy, Office of Science, Office of High Energy and Nuclear Physics, and the National Energy Research Scientific Computing Center, a DOE Office of Science user facility. LZ is also supported by the Science & Technology Facilities Council of the United Kingdom; the Portuguese Foundation for Science and Technology; the Swiss National Science Foundation; the Australian Research Council Centre of Excellence for Dark Matter Particle Physics; and the Institute for Basic Science, Korea. Thirty-nine institutions of higher education and advanced research provided support to LZ. The LZ collaboration acknowledges the assistance of the Sanford Underground Research Facility. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
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“Actually, that’s where the gold is,” said Alasdair Russell, my graduate school friend who leads a pre-clinical genome editing group at Cambridge. He was talking about the winding road of science that is omitted from published papers. “When you’re discussing how to do the experiment, and why this way is better than another way, and what does the data really mean? I know what it shows, but what does it mean?” At RAAIS 2026, he described how his group has begun logging the twisting path of discovery as it happens, recording the verbal and written exchanges that normally disappear. Ideas become nodes in a living graph: they branch when a meeting produces two plausible experiments, merge when separate lines of evidence converge, and go dark when someone quietly stops pursuing them. In his implementation, one agent scores novelty, while another tries to learn “how scientists think and how they navigate through a complex world of data,” so that high-potential nodes can trigger deeper investigation. As frontier AI labs deploy agents toward scientific discovery, giving AI authentic scientific taste remains a trillion-dollar dilemma. The bottleneck is that the record we have kept for centuries of science might be insufficient to get us there. The experiments that never make the paper Peter Medawar, 1960 Nobel laureate and “father of transplantation,” asked in 1963 whether the scientific paper was a fraud, and answered yes: the form of the paper misrepresents the thinking that produced it. Sixty years on, the diagnosis is unchanged. A paper presents a clean progression from hypothesis to result to conclusion. Lost along the way are the unconventional theories, the abandoned or unaffordable methods, and the underwhelming and inconclusive data. It reads like a browser history with every dead end deleted: the ten open tabs, the four rephrased queries, the wrong turn down a subforum. All scrubbed, leaving one clean path from question to answer as the canonical path. What has changed since then is that the discarded material is now worth something. No high-impact journal wants these artifacts, but raw trial and error is the most likely source of the training data required to develop scientific intuition, or what researchers call taste. Earlier attempts to capture the discards were motivated by scientific integrity. The Journal of Negative Results in Biomedicine launched in 2002 to publish rigorous studies that disputed established models or exposed ineffective treatments. Its archive preserved negative conclusions after they had become papers, rather than the live alternatives and arguments that produced them. BioMed Central closed it in 2017, saying the mission had been served now that other journals publish null results. A less generous reading is that in fifteen years it published around 200 papers because almost nobody wants to read a negative result, let alone write one up when it will not count toward academic tenure. AI models are different. Even an uninteresting negative result can be useful, provided it is labeled. Earlier this year, Anthropic put a version of this to the test. The company pulled 129 decision points from real Claude Code sessions between January and March 2026, showed models the work up to a human detour, and asked what should happen next. Claude Mythos Preview beat the human choice 64% of the time, while Opus 4.5 managed 51%. The comparison was tilted toward the models because Anthropic deliberately chose moments where the human decision had room for improvement. On 127 further scenarios where the human action was already strong, the models improved on it only about 20% of the time. The study was possible because Anthropic’s researchers work inside a tool that logs by default. The reasoning, detours and outcome are produced in the same working environment. Biology has no equivalent. Its reasoning happens in hallways, at benches, in Slack threads and on whiteboards, while the outcome arrives weeks later somewhere else. The record has to emerge from the work itself. Ask scientists to reconstruct it afterwards and we’ll create another polished account. Subscribe A log is not a label Before any of this becomes training data, a negative result has to say what failed. The first paper published in the Journal of Negative Results in Biomedicine examined 234 negative studies across five leading medical journals. Only 30% discussed statistical power, and half clearly defined a primary outcome. Tell a model an experiment failed, without telling it whether the assay was underpowered, a reagent had degraded, or the hypothesis was simply wrong, and it will learn noise with confidence. Decision histories have a second missing label too. When a lab considers five experiments and runs one, only the chosen branch returns an outcome. The other four are experimental counterfactuals. Researchers call this the selective labels problem: the data reveal results only for the actions someone chose to take. Such a record can teach a model to imitate a lab’s taste, but it cannot establish that the taste was good. It also smuggles local constraints into general lessons. A lab that never ran cryo-EM because it did not own a microscope teaches a model that cryo-EM is rarely the right call. Alasdair’s nodes preserve the candidate set, which is the necessary first step. To be useful, each decision record needs six fields: The evidence available at that moment, and nothing that arrived later. The candidates considered, including the ones dismissed in a sentence. For each candidate: the expected result, the confidence attached to it, and the cost in time and money. The route chosen, and the reason. What happened next. How the evidence changed the scientist’s view. These must be timestamped before the outcome, because hindsight turns uncertainty into inevitability. Disagreement also has to survive. Averaging three scientists into one clean rationale reproduces exactly the information loss we are trying to fix. But there is an obvious failure mode here. Once decisions are logged and scored, people log for the record post-facto. Anyone who has watched an electronic lab notebook fill up with retrospective tidying knows how quickly a research tool becomes a compliance exercise. A record that costs a scientist ten minutes of honest reflection per decision is worth far more than one that costs an hour of performance. A publication initiative called Registered Reports offers a useful starting point. Here, researchers submit their rationale, methods and analysis plan for peer review before the data exist, and the journal commits in principle to publish if they follow the approved plan. Nature has now expanded the format across every field it covers. This approach to paper writing timestamps intent before the outcome, but it freezes one plan. A useful search history must also preserve how the plan changed, which alternatives were rejected, when, and on what evidence. Subscribe Run the runner-up Autonomous labs show what happens when decisions and outcomes are connected in a loop. Liverpool’s mobile robotic chemist ran 688 experiments over eight days in a ten-variable formulation space. A batched Bayesian search used each result to choose the next experiments and found photocatalyst mixtures six times more active than the starting formulations. Every completed experiment changed what the system did next. The robot optimized within a goal and search space that humans had already chosen. It did not decide which scientific question mattered. So what this work demonstrates is narrower, but still useful: a search history pays off when the options return standardized outcomes quickly. Open-ended biology is harder because branches can take weeks and the discarded alternatives may never be run. Some exploration therefore has to be bought. Where two branches are plausible and the stakes justify the cost, a lab should sometimes run the runner-up. Otherwise the record captures what today’s scientists usually chose and stays silent on what they systematically overlooked. A funder could ring-fence a small fraction of a grant for the branch not taken, provided that the decision record and the outcome are both deposited. That costs money, but so does having every lab rediscover the same abandoned path. Test whether taste transfers When it comes time to evaluate if our new AI system exhibits taste, the comparison should run across laboratories and fields. At selected decision points in a live research campaign, we should freeze the six fields: the evidence, the candidates, expected results, confidence, costs and the choice made. Experts then rank the options before the outcomes are known, and those outcomes are checked independently later. We could give models one of two diets - papers alone, or papers plus decision histories - and ask them to rank the next experiment on unfamiliar projects. Then, we score information gained per dollar and week, calibration, and how quickly weak branches are abandoned. If histories improve choices only inside the lab that produced them, they amount to useful organizational memory. If they improve choices on unfamiliar problems elsewhere, Alasdair’s group will have captured something science has never managed to write down: a transferable record of taste. Until that happens, a scientific search history is a promising record, not yet a training set.
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To review this month’s supposed remake of 2013’s Assassin’s Creed IV: Black Flag, I must first correct the record. Assassin’s Creed Black Flag Resynced isn’t a game about pirates (and assassins) in the 18th century Caribbean. Sure, sure, that’s what the trailers would have you believe. They’ve go their clips of Edward Kenway swinging his swords and steering his pirate ship into cannon-blasting combat against British frigates. Is Resynced truly a pirate game? Of the 47 hours I spent playing Resynced over the past few weeks, I will admit I spent maybe 44 (?) of them collecting plunder with Blackbeard, drinking rum with Anne Bonny and debating the pros and cons of the lawless pirate-run settlement Nassau with Benjamin Hornigold. I may in fact have spent dozens of hours sailing to remote islands, reading treasure maps, opening messages left in bottles, sinking the odd Man o’ War with a well-timed broadside, collecting sea shanties for my crew, befriending a pet monkey, and hunting whales. I am nevertheless neither so Gullible nor so Narrow-Minded as to call the magnificent Resynced a “pirate remake.” Oh no. Forget any reviews of Assassin’s Creed Black Flag Resynced you may have read. Forget what you yourself may have played, if you’ve spent any time with the game since its launch. What Assassin’s Creed Black Flag Resynced is really about I’m here to give you the scoop (spoilers for Resynced’s Animus menu lore, which many players are probably not going to see): Assassin’s Creed Black Flag Resynced, the new game whose development was led by Ubisoft Singapore, is set in the year 2096. It’s about a societal split, about revolution, about an old Assassin’s Creed adventure repurposed in the series’ distant future as propaganda or samizdat. It’s about the overheated future of 2096, essentially conquered by the series’ well-established nefarious Templar-run company Abstergo. (In this future, Abstergo is, among other things, remaking a 2013 pirate movie called Devils of the Caribbean, but this time in VR. The VR version will be backed by a marketing plan that involves AI influencers, a 10,000-avatar “metaverse premiere event” and that manufacturing of memes aimed at “50 million VR nodes.” See what I mean about Abstergo being evil?) Resynced is about a late 21st-century population mollified by the widespread use of Abstergo’s Animus devices which let people experience the lives of historical figures culled from “genetic memories.” It’s about an insurgent faction of Assassins. And it’s about a plan to wake the population into revolutionary fervor by showing them the memories of 18th century pirate Edward Kenway, who—as depicted in the original Black Flag and again in Resynced—gradually comes to an understanding about the Assassins of his day and their centuries old fight for freedom. Resynced is also about an AI developed within the late 21st-century Animus, called Ego. It has found a way to alter genetic memories, to create and show Animus users false ones. The game is about Ego’s efforts to tell the people experiencing Edward Kenway’s memories that Kenway was wrong, that fighting against order is folly, that we should crave a world where “compliance is rewarded with power.” Who are we in this game? We’re an unnamed Animus user in 2096 who experiences Kenway’s journey virtually. At four moments during Kenway’s exploits in the Caribbean our virtual jaunt can be interrupted for 10-15 minutes, as we explore Animus “rifts” where Ego explicitly tries to tell us how wrong Kenway was. None of this is what 2013’s Assassin’s Creed IV: Black Flag was about, of course. That was a different game, even if you also spent dozens of hours pirating as Kenway in that game, across missions and a map that’s been faithfully reintroduced and rebuilt for Resynced. The 2013 Black Flag was about you playing as an unnamed researcher newly hired in 2013 by Abstergo Entertainment, the video game development wing of the Templars’ evil-corp. In that game, you were assigned to use the Animus to dive into the genetic memories of Desmond Miles, a man who died in Assassin’s Creed III and who was descended from a long line of Assassins (and at least one Templar) whose adventures were featured across the prior AC games. In 2013’s Black Flag, your mission was to plumb the Edward Kenway experience for material that Abstergo could use in productions such as the motion picture Devils of the Caribbean, though the Templars had some ulterior motives for the assignment. Resynced is therefore not a remake of 2013’s Black Flag. It’s a sequel. It is a new game about a new exploration of Edward Kenway’s pirate/assassin journey, set 83 years after the framing sequences of the original game. Resynced provides a new narrative framework that, thanks to the concept of an AI that wants to alter historical memories, arrives with creative justification to tweak a now-classic 13-year old game. That makes Resynced, already a hot seller, a tantalizing hint of where Ubisoft could go with a line of Assassin’s Creed remakes. They could remake the first game, the Ezio games, even the recent ones set in ancient Egypt and Greece. And for each, they could not just modernize the graphics and controls but expand and alter their sequences of events to use them as reference points for a conflict set in the late 21st century, as rival factions try to weaponize historical memories. Game File is a reader-supported publication. To receive new posts and support my work, even when that work consists of ravings about Assassin’s Creed’s modern day plot, please consider becoming a free or paid subscriber. Subscribe A story most players will probably miss If you didn’t know any of this, I’m not surprised. If you played the game and still didn’t catch it, I’m not a bit shocked. If Ubisoft has no plans to do more of this, I won’t fall down. Almost all of what I’ve described is optional and missable in Black Flag Resynced. I nearly missed it myself, as I planned for a breezy playthrough of an old Assassin’s Creed favorite. Instead, I found myself in a 40+ hour hunt for the “real” story, buried deeper in Resynced than any gold-filled chest. The story of 2096 is Resynced’s meta-story, told in two remote pockets of the game: 1) four optional playable “rifts” that players may find as they proceed through Resynced’s pirate fantasy , 2) in dozens of text files tucked three menus deep in the game’s barely-interactive Animus hub. Assassin’s Creed games have almost always had a meta-story about people in the 21st century (usually matching the game’s release year) and their connections to the main history portions you play. Those meta-stories have always been squeezed into the margins, though seldom as severely and as, uh, graphiaclly simple, as in recent games. Back in 2013, the modern-day exploits of you as an Abstergo Entertainment employee were prominent. They were portrayed via first-person portions that occasionally interrupted the third-person Kenway experience and could be explored for hours, complete with their own missions, side quests and puzzles. Resynced’s 2096 story—of Assassin “Watchers” vs. Abstergo/Tempar goons, of rogue AIs, of panicking scientists, of a woman wondering why her Animus-addicted husband is muttering about Mary Read (“What does he mean by Assassins?”), of a fight for the population’s hearts and minds via varying interpretations of Edward Kenway’s life choices—is mostly told through unlockable text files. The files are interesting. Offered via diary entries, intercepted chats and news reports, they present varied perspectives of a world in crisis. One set works as a narrative puzzle as it reveals the Rashomonic interpretations of a massacre, or was that a successful Assassin hit? Another favorite reveals the rising bitterness of a person who, through Edward Kenway’s journey, now shakes at the ignored evil around him. One surmises that Ubisoft is averse to putting the Assassin’s Creed’s meta-story in the way of more marketable pirate playgrounds and ninja/samurai epics. Instead, we get a better-than-nothing text-in-menus approach introduced in 2025’s Assassin’s Creed Shadows. In Shadows, players unlocked the meta-story text files largely via time-gated missions that called on the user to kill X number of enemy type Y, clear three enemy castles, re-win a three-phase fighting tournament, and other grinds. Time restrictions on accessing these missions and unlocking the files meant it could take players months to access the full story in-game. But even in the most hardcore Assassin’s Creed hangouts, the fanbase instead seemed to throw up their hands rather than grind to keep up. In Resynced, Ubisoft has shown some mercy, diminishing the amount of new text files that are tied to timed grinds. Now, most of the text-based 2096 lore are associated with “data file” collectibles that players can find in the world. That includes a batch of written entries that explain a historical link between the feudal Japan era in Shadows and the piracy adventures in Black Flag. Players who explore a lot will find dozens of data files, though the game does not appear to offer any in-game tracker for finding each one. You just need to keep looking for them. As of this writing, I have most of them, but not all. I can’t find any full guide for them online. And even Ubisoft’s optional $5 microtransaction that reveals lots of items in-game does not appear to reveal the locations of the text files (at least the official description omits them from its collectibles list). That’s not a huge bother, because tracking the data files down compelled me to re-explore the waves and islands of Black Flag. That was a thoroughly pleasant task to do for the first time in a dozen years. I expect many players, though, will be content to wait for the files to be reproduced in an online AC wiki somewhere, the easier to read on a web page. It may not seem enticing to play a video game in order to gradually unlock pages of text to read. Why not, you may ask, just read a book, where they put the pages in order? For one, they’ve not tucked this latest installment of Assassin’s Creed’s meta saga in a book. I also enjoy the unordered delivery, the dawning comprehension of a story about 2096’s desperate people and questionable tech, which I glimpsed first at its middle, then the end, then the front, then other moments in between1. I am also enamored with the idea of the Assassin’s Creed games I’ve previously played, including Black Flag, being repurposed for an information war. The ideas in Resynced’s meta-story, which builds off characters and ideas in Shadows’ chunks of text, are strong. The potential of where they could go with it is exciting. As for the pirate stuff? Looks great, controls pretty well, is fun to play and oh so speedy in terms of how much of a good time you can have with each sit-down. It never gets old to chase a new shanty page across a rooftop, bombard a fort with upgraded mortars or use a diving bell to explore sunken wrecks (hats off to the team at Ubisoft Barcelona that worked on the underwater portions in Resynced; that team is now facing layoffs, such is the misery of modern gaming and oft-troubled Ubisoft). New pirate missions in Resynced involving new ally characters are brief, dramatic and add more to Edward’s story, even if the gameplay perks they provide barely enhance the gameplay. A new denouement for high-class pirate Stede Bonnet is affecting; a new hunt for Blackbeard’s treasure is a welcome extra moment. A new epilogue to hunt down a pirate killer, on the other hand, over-complicates Kenway’s character. The ending credits remain my favorite of any game I’ve ever played. Black Flag provides great source material. The revisit is well-made and a great sign of what could be. It is offered in a different wrapper that hints at an opportunity for more interesting remakes to come, should Ubisoft choose to pursue such treasures—and as we brace to resist or comply with an Abstergo future. 1 The messages that Edward Kenway finds in bottles tell another out-of-order story, one about a man reckoning with the strange memories and voices he’s heard in his head since he was a boy. That tale was also in the 2013 game and develops into one of Black Flag’s most compelling character arcs. In Resynced, it has lost its climax, because the bottle story previously paid off in the halls of the first-person Abstergo Entertainment, which is exclusive to the older game. An altered resolution, written by the 2013 game’s lead writer is fine, doesn’t invalidate the 2013 version, but makes for an inferior final note.
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Shaky political science: using "simulated" elections over real-world elections
[Dear DSOS readers – this article is the latest in our “Shaky Political Science” series. In our 38 page report, “Shaky political ‘science’ misses mark on ranked choice voting,” released in early December, we examined over 40 studies focused on ranked choice voting. We found that many of these studies suffered from puzzling research methodologies, poorly constructed surveys, unrealistic simulated elections, cherry picked data, and faulty analyses that often were contradicted by results from real-world elections (a link to our full paper is here). Here are links to the first three articles in our series: the first one summarizing the overall results of our report, the second one analyzing a study co-authored by University of Minnesota academic Larry Jacobs, which was one of the most error-prone of all the research we reviewed in our report, and a third article showing an admirable example of two political scientists holding two other political scientists accountable for their flawed, sloppy research]. In this fourth article in our “Shaky Political Science” series, we shine a spotlight on seven studies that were web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group (the ERRG is an ad hoc committee headed by New America’s Political Reform Program and joined by the American Enterprise Institute, the Unite America Institute and Stanford University’s Center on Democracy, Development, and the Rule of Law). This research consortium has been led by Lee Drutman, senior fellow with New America’s Political Reform Program. These seven studies are simply not credible from any objective standard about how political “science” is supposed to illuminate our understanding of either ranked choice voting or politics in general. The feature that six of these seven studies have in common is that they all used surveys – artificial, simulated elections -- to attempt to say something cogent or interesting about ranked choice voting (RCV) elections. None of them used real world data from actual RCV elections – either the 1000+ elections in the US or the many thousands of elections from places like Australia, Ireland and elsewhere where RCV has been used for 100 years. While a few of these studies conclude with some mixed positives about RCV, our analysis here is content neutral. The idea that, with a political reform like RCV, you can ask respondents in a mock, artificial election to vote with that method, with only the barest of explanation about how RCV works or its likely impacts (i.e. no spoiler candidates, majority winners, voters liberated to pick their favorite candidates, coalition-building), and then ask them their thoughts/reactions about voting in that system, with fake candidates and no real campaigning, no real exposure to an actual election or actual candidates, rests on some very puzzling assumptions. The findings of these seven studies actually are contradicted by the findings from many other studies based on real-world RCV elections. These New America studies also failed to list the real-world RCV studies in their own citations, instead including those studies that reinforced their conclusions. The seven studies featured in this article were chosen because they form a cohesive cohort which precisely illustrates one of the main points of our research paper, namely that using surveys, i.e. artificial elections, or mathematical/theoretical models, instead of real-world data, is in fact “shaky political science.” Below are summaries of our analysis of five of the seven New America studies. You can read our complete analysis of all seven studies at our paper, “Shaky political ‘science’ misses mark on ranked choice voting.” Choosing to “Vote As Usual” by Andre Blais, Carolina Plescia, and Semra Sevi. New America. (Blais et al., 2021). This study, web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group, used two surveys in which respondents completed ballots for simulated elections using plurality, approval, RCV and point (Score) voting. In both cases the authors provided the respondents with only minimal explanation of each method. For example, the entire explanation for RCV was “For this vote, rank the candidates from your first to your last choice (you do not need to rank them all). This is called the ranked vote.” That’s it. The study did not provide any context or explanation to survey respondents about why she/he might want to rank multiple candidates. Participants were not even told that ballots would be tabulated using an “instant” runoff, not to mention any description of RCVs ability to eliminate the spoiler effect or liberate voters to rank their favorite candidates without fear of helping the “greater evil” candidate to win. That’s like taking an iPhone back in time to 1970 and asking someone if they like it better than their rotary phone without explaining how it works. Their first survey targeted states that held 2020 Super Tuesday Democratic primaries and used the real candidates’ names in the survey; the second survey used fictitious candidates. In other words, they surveyed respondents who had only ever participated in plurality elections, had no history or background with using RCV or any of the other methods, had no clue about its likely impacts, and did not communicate how the alternative methods would be counted, and then asked them: “How satisfied are you with using each system?” Predictably, the winner was plurality elections, the system used for president, Congress, gubernatorial and state legislative elections – in other words, the method they have been using, year after year, all their voting lives. With so little explanation of RCV and its impacts, this study is simply not credible in discovering anything useful about real-world RCV elections. It merely shows that a basic voter education campaign is needed when adopting a new election system. Additionally, the result contradicts many other post-election surveys following real RCV elections, asking opinions from voters who had just participated in a RCV election, that showed a great deal of satisfaction with RCV (see details on that in Studies 22-25 in our paper, as well as the four studies cited in the review for Study 28). Share Other studies on “satisfaction” and “understanding” make similar mistakes, in terms of basing their surveys on inadequate explanation to respondents and lack of education about context. How could any survey ever hope to measure accurately, in essence simulate a real-world election, without actual campaigning candidates, the media writing about those candidates, organizations endorsing candidates and voters being inundated with crucial information? More than anything, what these “studies” based on surveys show is that if you ask voters about something they don’t know very much about, and fail to adequately educate them, their responses will unsurprisingly reflect their confusion. Equally puzzling is that New America’s Electoral Reform Research Group, headed by political scientist Lee Drutman, found this to be a credible enough study that they not only published it but highlighted it in Drutman’s own discussion of research related to ranked choice voting. This pattern was repeated in study after study featured by New America’s Electoral Reform Research Group. For example in Ranked-Choice Voting and Political Expression: Voter Guides Narrow the Gap between Informed and Uninformed Citizens by Cheryl Boudreau, Jonathan Colner, and Scott MacKenzie, the researchers based their analysis on a survey which found that respondents who were asked to vote in a simulated RCV election, with minimal explanation of RCV or how it works, displayed less evidence of being informed about how to use RCV effectively, with the least informed voters ranking fewer candidates. As pointed out under the study above, in a real election voters are informed by a wide variety of methods, including public education by the election administration, by interested political groups, the media, and the candidates themselves who benefit from voters being aware of how to vote in the new system. In Support for Ranked-Choice Voting across Race and Partisanship by Joseph Anthony, David C. Kimball, Jack Santucci and Jamil Scott, the researchers used respondents from different parties and races voting in simulated plurality and RCV elections, who indicated their satisfaction with each voting method. Instead of using real world election results, the authors fell back on the easy, armchair and less reliable academic research methodology of making up mock elections. As with the other studies, little explanation was given of how RCV works or what its implications might be (electing majority winners or eliminating spoilers, for example). Unsurprisingly, this study found that respondents were not very satisfied with RCV. However, when the authors added an explanation that RCV has a tendency to elect more women and people of color, they found that this greater explanation increased the preference for RCV. The more voters were familiar with it, and the more they understood potential positive impacts – surprise! -- the more they were open to switching away from the status quo. Of note, the results from this study are thoroughly contradicted by a number of other studies whose data was obtained from real RCV elections with real voters. Those studies show a great deal of satisfaction with RCV. More “fake election” research An interesting wrinkle on this “research by fake elections” approach, which only served to illustrate how unreliable such “research” can become, was taken in Ranked-Choice Voting, Runoff, and Democracy: Insights from Maine and Other U.S. States by Joseph Cerrone and Cynthia McClintock_,_ also web-hosted and funded by New America’s ERRG. It gets high marks for creativity, but an eye-roll for thinking this could possibly add anything meaningful to our understanding of real world RCV elections. This study tried to determine whether RCV, plurality or two-round runoff elections provided greater voter satisfaction and acceptance of election results. To determine that, the authors conducted a survey asking if voters were satisfied with a fictional newspaper report of an election, with three different versions given to respondents – plurality, runoff and RCV, with variations of Republican/Democrat winners and variations of “come-from-behind” winners,” i.e. candidates not initially in first place but who win the “runoff.” Again, a minimal explanation of RCV or how it works was given, and the survey showed that respondents had the greatest unfamiliarity with RCV than the other methods. The unsurprising result? Respondents were much more satisfied with “come-from-behind” victories in a traditional two-round runoff election than in RCV, even though RCV is also a runoff system but with a single round of counting. Interestingly, the dissatisfaction with RCV disappeared for those who were more familiar with RCV. In fact, among those respondents who were “very familiar” with RCV, they were equally satisfied with RCV, runoff and plurality. Surprise, surprise. Again, what this study revealed, more than anything, is not only the inadequacy of the explanation for RCV given by the authors of this study, but the failure of the research format itself, thinking that such an artificial mock election could somehow simulate what actually happens in the real world in a real RCV election. Those four studies reviewed above are fitting examples of inadequate and shaky political “science.” Other studies reviewed in our paper from the New America/Electoral Reform Research Group cohort which also used mock elections included: Ranked-Choice Voting is an Acquired Taste by Joseph Anthony and David C. Kimball. New America. (Anthony et al., 2021). Ranked-Choice Voting is No Refuge for Extreme Candidates by Melissa Baker. New America. (Baker, 2021). Also included in this New America cohort is Does Ranked-Choice Voting Reduce Racial Polarization? by Yuki Atsusaka and Theodore Landsman, which actually did use real-world election results data but applied an odd and unconventional methodology to the data which relied on shaky assumptions and non-real-world scenarios that were too divorced from reality. To determine levels of “racially polarized voting,” the researchers imagined “ethnic parties,” by which they mean political parties for each ethnic group, which was especially odd since the election data they were using came from nonpartisan RCV races. But then they made an even odder assumption, namely that since race and ethnic characteristics of studied voters were not available, the authors tried to infer that information based on who voters selected and the racial make-up of voters in each district. This amounted to little more than vague and ambiguous guesswork dressed up with a bunch of mathematical equations used to give it a veneer of scientific appearance. Indeed, it seemed to assume racial polarization in order to prove racial polarization. Based on this questionable methodology, the authors concluded that RCV doesn’t reduce racial polarization. But the premise of this study missed an obvious reality: since RCV incentivizes more candidates to run and can result in more diverse fields of candidates, one would expect more racially-polarized voting in voters’ top rankings, not less, because more voters would have someone on that ballot who represents their racial or ethnic identity and more freedom to vote for their real first choice. By encouraging more diverse candidates and eliminating the spoiler effect, RCV facilitates voting for a favorite candidate of your own race and then selecting a second choice with the best likelihood of winning. The real measure is what voters do with their additional rankings – do they consider other candidates and vote “for the best of the rest”? This study didn’t tell us anything useful about that. But readily available data shows this is common in real RCV elections, and candidates act on this knowledge by engaging with voters outside their racial group. So the authors of this study failed to consider or account for what actually happens in real-world elections, and their conclusions are tainted by this failure. New America has contributed a great deal over the past 2.5 decades to our understanding of many policy areas, including politics and political reform (full disclosure: Steven Hill, one of the authors of this article and of the “Shaky Political Science” research paper and series, is a former senior fellow and former director of New America’s political reform program, 2005-2010). So it was especially disappointing that New America funded and published such a large batch of dubious studies about ranked choice voting. The stated praiseworthy goal of its Electoral Reform Research Group was to inspire new academic research about ranked choice voting that would shed light and help the public better understand the impacts of RCV. Instead, the ERRG research did just the opposite. It produced dubious research that created more confusion and misinformation. In so doing, New America’s political reform program contributed to “shaky political science.” Steven Hill and Paul Haughey Share Upgrade to $5 subscription Thanks for reading DemocracySOS, a reader-supported digital portal for the pro-democracy movement. Subscribe for only $5 per month to receive full benefits and to support our work. Subscribe
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Crucially, it aligns scheduling with the hardware’s real shape, not just with abstract CPU counts. Real‑world gains and who benefits Early tests on Intel Sapphire Rapids platforms point to gains in the 30–45% range for select workloads. Those wins appear in cache‑sensitive tasks like in‑memory analytics, high‑thread compilation, and microservices with tight working‑sets. Games and latency‑bound engines can also feel steadier frame‑times, especially when threads share hot assets. The benefits extend to AMD’s 3D V‑Cache parts, where keeping threads near enlarged cache slices prevents needless misses. Hybrid x86 designs with performance and efficiency cores further profit when cache and core roles are scheduled in concert. Even handhelds running SteamOS can squeeze more out of limited power, translating cache locality into smoother play. 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Server‑class kernels may enable or tune it sooner for targeted fleets where cache locality is money in the bank. How to think about performance impact Cache Aware Scheduling amplifies gains when your workload is both CPU‑bound and cache‑sensitive. Think tight inner loops, hot code paths, and datasets that fit snugly in shared LLC. It’s less dramatic for I/O‑bound services or memory‑hungry tasks that blow past cache capacity. Still, even modest locality improvements often translate into smoother tail‑latency, which is where user experience and SLAs typically break. Developers can further help by pinning related threads, batching work, and aligning data to reduce cross‑cluster chatter. The scheduler’s new awareness works best when applications expose good hints. The bottom line By understanding and honoring cache topology, Linux removes a subtle yet costly bottleneck. The kernel’s smarter placement keeps hot data hot and work near where it belongs. 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