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How-To Geek - Thu, 05/21/2026 - 19:00

Categories: IT General, Technology

MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models

Microsoft Research - Thu, 05/21/2026 - 19:00
At a glance
  • MagenticLite is an agentic application that works across both the browser and local file system in a single workflow. Built as the next generation of Magentic-UI, it combines a redesigned app with a harness optimized for small models.
  • MagenticBrain and Fara1.5 are small models designed for orchestration and computer-use tasks, respectively. Fara1.5 is the next iteration of Fara and delivers measurable gains on real-world browser tasks.
  • Together, these releases explore how far agentic performance can be pushed with smaller models, codesigned tools, and an optimized execution harness.

Today, Microsoft Research AI Frontiers releases MagenticLite (opens in new tab), an experimental agentic application designed for small models. As the next generation of Magentic-UI, it works across the browser and local file system in a single workflow.

MagenticLite is powered by two purpose-built models: MagenticBrain, for reasoning, delegation, and terminal use, and Fara1.5, a computer-use model family for browser-based tasks. The three components were designed to work together as a single system. The result is an agent that runs efficiently, keeps data on the user’s machine, and supports a broad range of agentic tasks. It also points toward a broader goal: capable agents that can run directly on users’ hardware.

The project is built around a key research bet: that agentic capability depends on tool orchestration and action rather than knowledge alone. That insight makes it possible to use smaller models while still enabling a broad range of agentic tasks at a fraction of the cost.

MagenticLite also reflects how we approach agentic AI end-to-end—from training data and model design to orchestration, interaction design, and human oversight throughout the experience.

Figure 1. One experience, three components: MagenticLite, MagenticBrain, and Fara1.5. Included in this release

MagenticLite (opens in new tab)

The next generation of Magentic-UI, our experimental agentic experience, is powered by an agent harness rebuilt for small models, with an updated user interface informed by community feedback. It works across users’ browsers and local file systems in a single workflow.

MagenticBrain (opens in new tab)

MagenticBrain is MagenticLite’s planner, coder, and delegator in one. It turns vague requests into concrete plans, selects the right tool or subagent for each step, writes code when needed, and recovers should something break mid-task. 

Fara1.5

The next generation of our computer-use model family, Fara1.5 comes  in three sizes, with a flagship 9-billion-parameter model for most use cases. Fara1.5 sets new state-of-the-art (SOTA) results among small computer-use models and nearly doubles Fara-7B’s performance on web navigation, with sharper handling of forms, credentialed sites, and long-running tasks.

Each component is useful on its own, but they work best together. Codesigning the app, models, and the harness enables capable and reliable agentic performance at this scale.

Our research approach: Doing more with less

We started with a simple question: what does it take to make a small model genuinely good at agentic tasks? The answer spanned the full lifecycle—data generation, training objectives, model design, and orchestration had to be redesigned together rather than in isolation.

We identified requirements from real-world use cases like filling out forms, conducting browser research, and managing files locally, and built an evaluation dataset around them. Standard benchmarks capture part of the picture, but they are not always a direct measure of real-world usefulness. Scenario-based evaluations complemented those benchmarks and became a key signal for iterative improvement across both the models and the harness, as shown in Figure 2.

Figure 2. An iterative process for building agentic systems involves defining success criteria, evaluating performance, and refining the models or system design (or both). Then repeat.

For the user experience, we retained key elements from Magentic-UI, including visibility into the agent’s reasoning and actions, the ability for users to take direct control, and explicit approval at critical points. Based on recent user studies, we also made MagenticLite easier to learn and collaborate with through updated browser and chat views, designed to make it easier for users to understand the agent’s actions and intervene when needed. This is illustrated in Figure 3.

Figure 3. MagenticLite’s interface includes updated browser and chat views designed to make it easier to understand agent actions and intervene when needed.

Spotlight: AI-POWERED EXPERIENCE

Microsoft research copilot experience

Discover more about research at Microsoft through our AI-powered experience

Start now Opens in a new tab System components Fara1.5: A computer-use model that outperforms its weight class

Fara1.5 is the next generation of our computer-use model family, which is available in three sizes, with a flagship 9B model recommended for most use cases. Fara1.5 achieves new SOTA performance among small computer-use models and nearly doubles Fara-7B’s performance on web navigation, with better handling of forms, credentialed sites, and long-running tasks.

Last November, we released Fara-7B, a small agentic model built for completing tasks in a web browser. It was trained using a novel synthetic data generation engine that enabled best-in-class performance. Fara1.5 is the next step in that bet: a family of three models (4B, 9B, 27B) based on Qwen 3.5, designed to close the gaps we saw in the prior release.

What’s new

State-of-the-art results. On the popular Online-Mind2Web benchmark, which contains 300 tasks across widely used web domains, Fara1.5 sets new SOTA results for models in its size class. Fara1.5 outperforms all similarly sized models and nearly doubles the performance of Fara-7B. The larger Fara1.5-27B variant achieves more than 90% performance on the same benchmark.

Figure 4. On the OnlineMind2Web benchmark, Fara‑1.5-9B achieves state-of-the-art performance among models in its size class and substantially outperforms prior models. 

Improved user experience. In addition to improvements on benchmarks, we improved the user experience of Fara1.5. Users should observe stronger performance on everyday tasks like filling out forms, handling logins for credentialed sites, and booking appointments. These improvements are driven by the next evolution of our FaraGen data generation pipeline. Alongside training on live websites, we also trained the model on highly realistic synthetic environments designed to simulate scenarios like logins and irreversible actions.

A native action space tuned for long-running tasks. Beyond clicks and keyboard actions, Fara1.5 has built-in tools to store key information in its context across hundreds of steps and ask the user for permission or preferences when needed, helping it stay coherent on tasks that span many minutes of real work.

Recalibrated critical points. Fara-7B was trained to detect critical points for activities like transactions, login flows, or irreversible submissions and flag them. In Fara1.5, we refined our design around critical points based on our learnings from real use, so safety triggers still occur when they should but do not block useful tasks, such as form-filling.

Figure 5. Fara1.5 pauses and requests user intervention when it detects a critical point, in this case during a sign-in to a LinkedIn account using email credentials.  MagenticBrain: The orchestrator model

MagenticBrain is a 14B-parameter orchestration model—planner, coder, and delegator in one. Fine-tuned from Qwen 3 14B, MagenticBrain was trained end-to-end within the MagenticLite harness with the same tool schemas and execution environment it will encounter at inference time. As a result, there is no gap between how it learned to orchestrate and how it runs.

In many agentic systems, orchestration (planning and coordination) is the most reasoning-intensive component, so teams have historically relied on their most capable models for this role. Our bet is that small models can handle this role without sacrificing capability. Two design choices make that possible.

The first involves combining multistep tool-calling trajectories—where the model learns to pick the right tool and call it correctly—with coding and terminal trajectories—where the right answer is sometimes five lines of Python, not a tool call. This is paired with tight coupling between the tool format used during training and inference.

The second is computer-use agent (CUA) delegation. A key part of the orchestrator’s job is knowing when not to act itself and instead handing off a task to Fara1.5. Our data pipeline includes explicit delegation trajectories: sequences where the orchestrator recognizes a browser or user interface (UI) task, issues a structured handoff to the CUA model, waits for the result, and resumes the task. The result is an orchestrator model that reasons, codes, calls tools, and delegates fluidly within a single 14B footprint. We are releasing MagenticBrain which is designed for use with MagenticLite. 

Figure 6. MagenticBrain is a small orchestration model that can break down a natural-language request into smaller steps, select the right tools, write code when needed, and delegate browser tasks to Fara1.5. The Harness: Built for small models

The harness combines the orchestrator and browser-use models into a single workflow. Three design choices matter most:

  • Step-by-step planning. The harness plans incrementally, keeping the system flexible and enabling smoother course correction and recovery throughout long-running tasks.
  • Active context management. Small models have smaller effective context windows and degrade faster as context grows. The harness actively curates what each model receives at each step, keeping prompts focused, surfacing only the necessary information, condensing earlier interactions into concise summaries, and offloading the rest, so the orchestrator and Fara1.5 remain effective across long tasks.
  • Delegation through subagents. Rather than relying on a single small model for every task, the orchestrator acts as the main agent and delegates specialized work to subagents. This means handing off browser tasks to Fara1.5. This pattern plays to the strengths of small language models by allowing each model to handle a narrower, more specialized part of the problem. It also lays the foundation for future expansion: later versions could introduce additional subagents and run them in parallel for richer, more efficient workflows.

The harness preserves the human-in-the-loop guarantees from Magentic-UI 1.0. Critical points across both browser and code actions still pause for explicit user approval, and the entire system runs inside Quicksand (opens in new tab), an open-source wrapper created for a QEMU-based sandbox, which isolates browser sessions and code execution from the host system.

Figure 7. Overview of the MagenticLite architecture. The system uses a layered architecture spanning the front end, harness, models, and sandboxed execution environment. See it in action

MagenticLite can perform a wide range of tasks across the browser and local file system, such as filling out forms, making appointments, organizing local files, and searching for and analyzing information.

MagenticLite | Fill expense forms demo MagenticLite | Find and book a restaurant demo MagenticLite | Find prices for recipe ingredients demo MagenticLite | Organize local files demo Try it, and build with us

MagenticLite, MagenticBrain, and Fara1.5 are research releases intended to support continued exploration and development. We are releasing them to encourage experimentation, evaluation, and feedback from the broader community.

Contributors Opens in a new tab

The post MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models appeared first on Microsoft Research.

Categories: Microsoft

We organized 60+ of the best Memorial Day deals: TVs, mattresses, headphones, and more on sale

Mashable - Thu, 05/21/2026 - 18:45
The best early Memorial Day 2026 deals: Best Amazon deal Ninja Slushi $259 (save $90.99) Get Deal Best TV deal Toshiba 65-inch C350 LED 4K Fire TV $264.99 (save $265) Get Deal Best tech deal Bose QuietComfort headphones $229 (save $120) Get Deal Best home deal Ruggable save up to 25% sitewide Shop Now

The unofficial start to summer is almost here, but you don't have to wait until Memorial Day itself on May 25 to find those Memorial Day deals.

There are already deals live at Amazon, where you'll find savings of up to 40%. There are also plenty of savings from other online shopping destinations, with deals on products such as mattresses, TVs, furniture, and outdoor patio items. Plenty of brands are getting in on early MDW action — you can grab the Dyson Airwrap i.d. for $150 off and the Bose QuietComfort headphones for $120 off.

We'll be updating all the best Memorial Day deals throughout the weekend, so be sure to keep checking back on this page for the biggest and best savings.

Best Memorial Day Amazon deals Ninja Slushi $259.99 at Amazon
$349.99 Save $90   Get Deal at Amazon Get Deal at Best Buy Why we like it

What says start of the summer better than slushies on demand? When Mashable's Leah Stodart reviewed the Ninja Slushi, she pointed out the merits of the Slushi over a regular blender: no ice is required, and it keeps drinks frozen while in its cooling cylinder. From cola slushies to frosé, this might just be the ultimate summer drink machine. It has some downsides (sugar-free beverages are a no-go), but if you're a frozen drink enthusiast, this deal is worth a closer look.

More Amazon dealsBest Memorial Day TV deals Opens in a new window Credit: Toshiba Toshiba 65-inch C350 LED 4K Fire TV $264.99 at Best Buy
$529.99 Save $265   Get Deal Why we like it

Best Buy and Amazon have been racing to match prices on this Fire TV. Best Buy was initially $75 cheaper than Amazon, so Amazon dropped its sale price to keep pace. But that's only a piece of the picture demonstrating just how good this deal is. Our resident TV expert, Leah Stodart, pointed out that this $264.99 price point is so good that it's less than the sale price of the 43-inch version of Amazon's most basic Ember 4K Fire TV. In other words, if you're looking to score a solid deal on a smart TV this Memorial Day, this could be the one for you.

More TV deals

43-inch to 50-inch TVs

55-inch TVs

65-inch TVs

70-inch TVs and up

Best Memorial Day mattress deals

  • Avocado: Get up to 20% off organic mattresses, bed toppers, and bedding.

  • Amerisleep: Get up to $1,000 off all mattresses and 40% off bundles

  • Bear: Get 35% off sitewide, plus $275 worth of free accessories

  • Casper: Get up to 30% off select mattresses and 35% off bundles

  • Purple: Get up to $900 off a mattress and a base

  • Helix: Get 25% off sitewide with code MEMDAY25

  • Leesa: Get 30% off select mattresses

  • Mattress Firm: Get up to 60% off select mattresses with queens starting at $189.99

  • Nectar: Get up to 50% off select mattresses and 66% off bundles

  • Saatva: Save up to $650 on mattresses, including the Saatva Classic and Memory Foam Hybrid mattresses

  • Serta: Save up to $600 on select mattress and adjustable base sets

  • Sleep Number: Save up to $1,200 on ClimateCool and ComfortNext mattresses, BOGO free Ultimate Shape Pillows, and BOGO 50% off sheets

  • Tempur-Pedic: Save 40% on the Tempur-Cloud Mattress or up to $500 on adjustable mattress sets, plus free gifts

Best Memorial Day home deals

  • Brooklinen: Refresh your bedding for summer with 25% off sitewide

  • Buffy: Save up to 25% sitewide

  • Caraway Home: Save up to 30% on cookware and bakeware

  • Cozy Earth: Save 20% sitewide or 25% when you buy three or more items

  • Crate & Barrel: Save up to 60% on rugs, 35% on kitchen brands, and 30% on furniture

  • Cuisinart: Save 15% on $99.95+, 20% on $149.95+, and 25% on $249.95+

  • Home Depot: Save up to 40% on select appliances, 20% on select patio furniture, and up to $175 off on select tools now through May 27

  • Joybird: Take up to 45% off on bestselling furniture and up to 35% off sitewide through May 25

  • Kohl's: Save up to 50% sitewide on clothes, kitchen appliances, bedding, patio furniture, and more

  • Lovesac: Save 40% sitewide through May 31

  • Lowe's: Save on appliances, grills, patio furniture, gardening supplies, and more through June 3

  • Mellow Sleep: Get $20 off $100, $50 off $200, or $100 off $300

  • Nest New York: Save 25% sitewide with code 25OFF

  • Parachute: Save 25% sitewide plus 30% on bundles

  • Ruggable: Save up to 25% sitewide

  • Rugs Direct: Save up to 80% sitewide on brands like Safavieh, Chris Loves Julia, Loloi, Rifle Paper Co., and Rugs USA

  • SharkNinja: Save up to 30% on Ninja kitchen appliances and Shark vacuums, hair tools, and fans

  • Target: Target's Hello Summer Sale brings deals on summer favorites, including up to 20% off kids' outdoor toys and up to 45% off patio furniture and garden essentials

  • Wayfair: Save up to 70% sitewide

Best Memorial Day tech deals

  • Best Buy: Save on TVs, Apple products, laptops, monitors, Sony cameras, Bluetooth speakers, and more

  • HP: Save up to 72% on OmniBook laptops, Omen gaming PCs, All-in-One desktops, and more

  • Lenovo: Save up to 30% on ThinkPad, Yoga, ThinkBook, IdeaPad, and Legion laptops

  • LG: Save up to 44% on TVs, 40% on monitors, and up to 58% on appliances

  • Tile: Save up to 40% on trackers

Best Memorial Day beauty deals

  • Dyson: Save up to $150 on the Dyson Airwrap i.d., Airstrait, and Supersonic Nural

  • FabFitFun: Save 40% on your first box, plus get a free Vacation bonus box ($250 value) with an annual membership signup

  • L'ange: Save 44% sitewide with code MEMORIAL

Best Memorial Day outdoor deals

  • Columbia: Save up to 40% on "almost everything"

  • Dick's Sporting Goods: Save up to 50% on bikes, kayaks, tents, grills, and golf gear, save up to to 40% on Nike and adidas

  • Rumpl: Save 25% sitewide

  • Solo Stove: Save 15% on select fire pits and pizza ovens

Categories: IT General, Technology

2 useful (and 1 fun) homelab projects to try this weekend (May 22 - 24)

How-To Geek - Thu, 05/21/2026 - 18:30

It's that time of the week again, so let's dive into three more fun homelab projects to try this weekend! Today, I'll be talking about setting up a home energy usage monitoring system, a private Pastebin alternative, and a retro LAN party box!

Categories: IT General, Technology

Google, Meta, TikTok face EU complaints over financial scam protections

Mashable - Thu, 05/21/2026 - 18:26

Tech giants Google, Meta, and TikTok are facing European scrutiny for their alleged role in a growing number of financial scams targeting users.

The three companies are accused of failing to proactively remove fraudulent ads from their platforms and notify users in an appropriate manner, outlined in complaints filed to regulators by the European Consumer ⁠Organisation (BEUC) and 29 of its members in 27 European countries, Reuters reported.

SEE ALSO: Child safety organizations accuse Roblox of violating FTC rules

The consumer group flagged 900 ads that they deemed violated EU laws, but said that only 27 percent of those ads were removed by platforms. More than half of the reports were rejected or ignored.

The complaints were submitted under the EU's Digital Services Act, and regulators could levy hefty fines if the companies are found in violation.

"This complaint misrepresents how we fight scams and is inherently flawed. We take extensive measures to keep scams off our platforms, blocking over 99% of policy-violating ads before they are ever seen," a Google spokesperson said in comment to the press.

"We ​invest in advanced AI, ⁠tools, and partnerships to stop them. Last year we found and removed over 159 million scam ads, 92% before anyone reported them to us," Meta responded.

Meta was recently accused of making tens of millions of dollars off of scam ads targeting older Americans and Medicare recipients. Last year, a Reuters investigation found that Meta made billions from fraudulent ads, also referred to as "high risk" advertising. AI-powered scams are proliferating across platforms, including Google-owned YouTube and TikTok.

The Digital Services Act — a broad set of laws that impose more transparent reporting and consumer protections on online service providers — went into effect in 2022. Since then, the European Union has initiated multiple inquiries against large tech companies, including a recent Google antitrust probe, an investigation into Meta's child safety policies, and a sweeping audit of TikTok's algorithm and data policies.

UPDATE: May. 21, 2026, 4:18 p.m. This story was updated with a new statement from Google.

Categories: IT General, Technology

I tested aluminum foil, metal bowls, and antenna extenders on my Wi-Fi router—only one actually worked

How-To Geek - Thu, 05/21/2026 - 18:00

A Wi-Fi router works best when it’s placed in a high, central spot in your home. Unfortunately, reality and pre-existing cabling often dictate where it ends up, leaving it stuck in corners or behind obstacles where coverage suffers.

Categories: IT General, Technology

Android's openness was always a myth—and Google just admitted it

How-To Geek - Thu, 05/21/2026 - 17:45

Many Android fans will tell you that the signature requirement for apps outside the Google Play Store, even with the 24-hour sideloading exemption, represents the latest betrayal of the platform's open-source philosophy. You're supposed to have full control over what software you install and when, unlike the more closed-off iPhone experience, where Apple usually has the final say.

Categories: IT General, Technology

Spotifys new Reserved feature could make concert ticketing less miserable

Mashable - Thu, 05/21/2026 - 17:44

These days, scoring concert tickets can feel like entering a digital Hunger Games. Fans log on the second tickets go on sale, only to watch seats disappear instantly — many of them seemingly snapped up by scalpers and resellers before actual fans ever get a chance.

Now, Spotify wants to change that by rewarding the people who stream the most.

SEE ALSO: Spotify has a new Wrapped-like experience that covers its entire history

Today, May 21, the streaming platform announced Reserved by Spotify, a new ticketing initiative aimed at helping dedicated fans access concert tickets before they go on sale to the general public. The program is launching for Premium subscribers in the U.S. who are 18 or older.

Credit: Spotify

The idea is simple: Instead of forcing fans to battle through chaotic on-sale queues or complete elaborate fan-verification games, Spotify will identify an artist's most dedicated listeners through streaming activity and reserve tickets specifically for them. Eligible fans will receive a purchase window before the public on-sale begins, with up to two tickets held in their name.

Importantly, Spotify says the reserved tickets will not include additional Spotify service fees.

The company says the number of fans selected — and the number of tickets available — will vary depending on the artist, tour, and market. But Spotify says allocations are intended to be substantial and to scale with an artist's fanbase.

Credit: Spotify

The move reflects the growing importance of superfans to the music industry, where artists and platforms alike are increasingly trying to reward the fans who engage most deeply. In recent years, fandom has become one of the most powerful forces shaping touring, chart performance, and even marketing strategies, particularly in pop and K-pop spaces where highly organized fan communities already treat streaming like participation.

Reserved by Spotify also expands the company's broader ambitions in live music. Spotify says it has already driven more than $1.5 billion in ticket sales through its platform via partnerships with more than 40 ticketing companies, alongside features like Concerts Near You and Venue Search.

SEE ALSO: Why the Spotify icon is a disco ball

The bigger question, though, is whether programs like this can meaningfully combat the frustrations fans increasingly associate with modern ticket-buying in the U.S. As ticket prices continue to climb and resale markets remain difficult to control, many fans have grown cynical about whether fair access to concerts is even possible anymore.

Spotify is betting that listening history — not luck — might be the closest thing to a solution.

Categories: IT General, Technology

Google's Googlebook is just the Pixelbook all over again—and that worries me

How-To Geek - Thu, 05/21/2026 - 17:30

Google has announced a successor to the Chromebook, introducing a class of computer that merge together Android and Chrome OS, with a thick layer of Gemini on top. The first Googlebook, titled simply the Googlebook, is an attractive showpiece of a laptop—but I wouldn't feel comfortable buying one.

Categories: IT General, Technology

I've been a Synology die-hard for years, but this brand finally won me over

How-To Geek - Thu, 05/21/2026 - 17:00

I used to be a Synology die-hard fan, but that's recently changed. While I think Synology still makes a solid NAS, they're no longer the best option around, and my favorite NAS brand might just surprise you.

Categories: IT General, Technology

New Microsoft Defender exploits discovered. How to protect yourself

Mashable - Thu, 05/21/2026 - 16:55

Microsoft has identified some nasty exploits that could affect your Windows machine if you let them.

Bleeping Computer reported on the exploits, which are specific vulnerabilities in Windows Defender, the built-in anti-malware software in Windows. The company has detailed reports on its security website for both vulnerabilities. While it can be a bit difficult for a layperson to understand what's going on from those reports, the main thing to know is that vulnerable Windows machines can be subjected to denial-of-service attacks using these exploits.

SEE ALSO: Microsoft Teams won’t put everyone in a virtual room anymore — no more 'Together'-ness

The good news is that Microsoft has already revealed these exploits, and a fix is in the pipeline. If you have automatic updates for Defender turned on, it should have installed the Malware Protection Engine versions 1.1.26040.8 and 4.18.26040.7 to address these exploits.

Bleeping Computer also included a helpful set of instructions for making sure these updates are turned on:

  1. Open Windows Security

  2. Select "Virus and threat protection"

  3. Click "Protection Updates" and then "Check for updates"

  4. Select "Settings" and then "About"

  5. Check the Anti-malware Client version number and make sure it matches the two numbers above

Hopefully, everything is properly set up, and your machine is good to go.

Categories: IT General, Technology

Memorial Day is the perfect time to buy a robot lawn mower — steep discounts on top models are live now

Mashable - Thu, 05/21/2026 - 16:54
The best Memorial Day robot lawn mower deals at a glance: Best overall deal Dreame A3 AWD Pro Robot Lawn Mower $2,946.98 (save $553.01) Get Deal Best deal for smaller yards Segway Navimow i110N Robot Lawn Mower $849 (save $250) Get Deal Best deal for fast recharging Sunseeker S4 LiDAR Robot Lawn Mower $1,399 (save $400.99) Get Deal

Some people love to mow the lawn. Others, especially those with allergies, would be thrilled to never touch a lawn mower again. If you fall into the second camp, there's a great solution. Hiring a robot lawn mower means there's an on-demand solution that's ready and willing to mow at any time.

Much like robot vacuums that we rely on indoors, a robot lawn mower maps your yard and sets off to mow according to your desired schedule. Since Memorial Day is nearly here and backyard hangs on are on the agenda, check out these robot lawn mower deals at Amazon.

Best overall deal Opens in a new window Credit: Dreame Dreame A3 AWD Pro Robot Lawn Mower + Free Mower Garage $2,946.98 at Amazon
$3,499.99 Save $553.01   Get Deal Why we like it

Dreame makes some of Mashable's favorite robot vacuums, so it only makes sense the brand is producing some of the best robot lawn mowers. The Dreame A3 AWD Pro Robot Lawn Mower is designed to tackle grass that covers up to 1.25 acres with a width that measures 15.8 inches for efficient mowing. This model uses 360-degree LiDAR binocular AI vision to help with navigation and obstacle avoidance for over 300 common items it might encounter in the yard.

In rush mode, the Dreame can cover 0.2 acres per hour and it can maneuver over curbs, roots, or stepping stones that measure up to 2.2 inches tall without getting stuck.

Today's on-page coupon brings the price of the Dreame A3 AWD Pro Robot Lawn Mower down to $2,946.98, and Amazon is throwing in a free Dreame robot lawn mower garage which helps protect the robot from harsh sun and rain. The garage ordinarily sells for $299.99, which makes this Memorial Day deal just that much sweeter.

Best deal for smaller yards Opens in a new window Credit: Segway Segway Navimow i110N Robot Lawn Mower $849 at Amazon
$1,099 Save $250   Get Deal Why we like it

Covering an area of up to 0.25 acres, the Segway Navimow i110N Robot Lawn Mower is more than happy to take over the task of keeping the lawn trimmed this summer. It can mow as quietly as 58 decibels while identifying and avoiding over 150 types of obstacles. Plus, it's designed to handle multiple zones in your yard. You'll be able to set zones like the front yard, back yard, and side areas while indicating an ideal schedule to mow each area. In addition to using the Segway app, you can also set up voice control of the robot lawn mower.

Select the desired heigh of the grass between 2 and 3.6 inches, and the Segway Navimow will take care of the rest. It'll take about 120 minutes for the Navimow i110N to get a full recharge. As a unique feature, the Segway has a new doodle feature that allows you to write messages in the lawn.

Best deal for fast recharging Opens in a new window Credit: Sunseeker Sunseeker S4 LiDAR Robot Lawn Mower $1,399 at Amazon
$1,799.99 Save $400.99   Get Deal Why we like it

Just in time for Memorial Day, the Sunseeker S4 LiDAR Robot Lawn Mower is 22% off at Amazon, shaving $400.99 off the list price. This Sunseeker model can mow yards up to 0.25 acres and navigate sloes that measure up to 42 degrees. You're able to set up to five mowing zones with the Sunseeker S4 and select mowing heights for each zone between 1.6 and 3.2 inches.

When it comes time to recharge, the Sunseeker takes just 90 minutes to get back to 100% and ready to mow again. It also has a smart rain sensor and will return to base should the weather turn soggy.

Categories: IT General, Technology

I found a 70-inch 4K Roku TV for $299.99 in Best Buys Memorial Day sale — better than Black Friday

Mashable - Thu, 05/21/2026 - 16:48

SAVE $210: As of May 21, you can score a 70-inch 4K Roku TV from Pioneer for $299.99. That's more than 40 percent off its usual $509.99.

Opens in a new window Credit: Pioneer Pioneer 70-inch 4K Roku TV $299.99 at Best Buy
$509.99 Save $210   Shop Now

Best Buy's Memorial Day sale is home to a ton of good TV deals, including a Prime Day-level doorbuster the month before Prime Day 2026. I'm talking about a Pioneer 70-inch 4K Roku TV on sale for $299.99, down $210 from its usual $509.99. And if this were Prime Day, this feels like a deal that would've sold out within hours.

This quieter deal should last longer, but it's set to expire in the wee hours of May 22.

SEE ALSO: What's new to streaming this week? (May 22, 2026)

You're unlikely to find a 70-inch TV for less than $300 elsewhere. $299.99 would even be a decent price for a smaller 65-inch model. That's exactly how much the 65-inch Insignia 4K Fire TV is currently going for at Amazon, if you want to take the classic Fire TV vs. Roku TV route — so opting for this Roku deal at Best Buy is kind of like getting five extra diagonal inches for free. For reference, the 70-inch Insignia 4K Fire TV is $20 more at $319.99.

This Pioneer Roku TV has three HDMI ports, a 60Hz refresh rate, and supports HDR 10. While it's unrealistic to expect groundbreaking brightness or contrast from a TV this budget-friendly, take comfort in the fact that this model has 4.8 out of five stars at Best Buy (from more than 300 reviews, too). It gets good marks for easy set up, a lightweight and thin build, and clear picture quality for the price.

Categories: IT General, Technology

Forget the classics: 4 movies that prove Pixar actually peaked in the 2010s

How-To Geek - Thu, 05/21/2026 - 16:46

As someone who has grown up watching Pixar and witnessed the evolution of animation, there have been many times where I think I’m watching the company's peak, as in "This is the best movie I’ve ever seen." Often, when it comes to Pixar, I’ve noticed many people believe the earliest portion of its life, in the 2000s, was when it peaked, but I’m here to say that’s false.

Categories: IT General, Technology

Almost every Sonos speaker is on sale for Memorial Day — save up to $200 on our top picks

Mashable - Thu, 05/21/2026 - 16:32
The best Sonos Memorial Day deals at a glance: Best portable speaker deal Sonos Roam 2 $134 (save $45) Get Deal Best home speaker deal Sonos Era 300 $379 (save $100) Get Deal Best soundbar deal Sonos Arc Ultra $899 (save $200) Get Deal

We're massive fans of the Sonos audio ecosystem. The brand's speakers and soundbars are some of the best in the business, but their expensive prices make them hard to recommend in this economy. When a major sale takes place, on the other hand, we want to scream about it.

Sonos doesn't offer a ton of discounts on its products throughout the year, so it's kind of a big deal that nearly every product in its lineup is on sale for Memorial Day. While the brand new Sonos Play speaker isn't on sale, the beloved Roam 2, Arc Ultra, Move 2, Era 300, and plenty more are up to $200 off.

Check out our top picks from the Amazon Memorial Day sale below.

Best Sonos portable speaker deal Opens in a new window Credit: Sonos Sonos Roam 2 $134 at Amazon
$179 Save $45   Get Deal Why we like it

The portable Bluetooth speaker market is crowded, but the Sonos Roam 2 stands out thanks to its impressive audio performance and dependable voice assistance.

We also love the Sonos Move 2, but it's not nearly portable enough and is far too expensive. "The market for waterproof speakers with voice activation is incredibly small," writes Mashable's reviewer. "If you’re looking for one, the Roam 2 answers the call with striking sound and unique features that appeal to Sonos users." You can expect sound that feels similar to a home speaker, but in a package small enough to fit in your hand. It's down to just $134 from $179, which is its best price ever. The speaker has only reached this all-time low once before.

Best Sonos home speaker deal Opens in a new window Credit: Sonos Sonos Era 300 $379 at Amazon
$479 Save $100   Get Deal Why we like it

While it's a few years old at this point, the Sonos Era 300 is still an impressive home speaker. And at $100 off its list price, adding it to your home is a bit more accessible. When Mashable's Stan Schroeder reviewed the Era 300 in 2023, he deemed it the "king of sub-$500 smart speakers." It's Sonos' first speaker to support spatial audio and it can connect seamlessly with other audio products from Sonos — not that it needs help from anything else. Its sound is absolutely booming on its own. We're not particularly captivated by its design, but its incredibly loud and precise sound makes up for it.

Best Sonos soundbar deal Opens in a new window Credit: Sonos Sonos Arc Ultra $899 at Amazon
$1,099 Save $200   Get Deal Why we like it

If you want the best and don't mind a little splurge, the Sonos Arc Ultra got a near-perfect rating from Mashable's tech editor Tim Beck Werth. Even at full price, he says the soundbar justifies its price of admission. "While a single soundbar can't compete with the booming speakers you'll hear in a movie theater," Werth writes, "This speaker gave me the closest match to that experience I've ever had in my living room." Typically $1,099, you can slash $200 off at Amazon, Sonos, and Best Buy for Memorial Day. That's just $20 away from its best-ever price.

More Sonos deals
Categories: IT General, Technology

Stop letting your Raspberry Pis collect dust—here are 3 projects to start this weekend (May 22 - 24)

How-To Geek - Thu, 05/21/2026 - 16:16

Do you still have a drawer full of Raspberry Pis? Well, get them out, because here are three fun and simple Pi projects for you to do this weekend.

Categories: IT General, Technology

5 forgotten Android apps you’ll still love

How-To Geek - Thu, 05/21/2026 - 16:00

The "Android Market" from 2008 became the Google Play Store in 2012 and now offers over 1.8 million apps for download. A lot has changed in the world of Android since then, but some things (and apps) have stayed the same. Did you know many of your favorite and long-forgotten apps are still available? More importantly, some are still worth downloading.

Categories: IT General, Technology

Vega: Zero-knowledge proofs for digital identity in the age of AI

Microsoft Research - Thu, 05/21/2026 - 15:48
At a glance
  • Vega lets users prove facts from government-issued credentials — age, personhood, professional status — without revealing the credential itself. The credential never leaves the device. 
  • Zero-knowledge proofs are generated in under 100 ms on a commodity client device with no trusted setup, making private identity verification practical at scale. 
  • Fold-and-reuse proving means repeated presentations — to different services or through AI agents — skip most of the expensive work after the first proof. 
  • Vega targets real-world formats like mobile driver’s licenses and the EU Digital Identity Wallet, is built in Rust, and will be open sourced soon.

AI is transforming how people interact with digital, from AI-powered assistants to autonomous agents that act on a user’s behalf. As these capabilities grow, so does the value of strong digital identity: users need reliable ways to establish trust, whether proving they are human or sharing a credential with an AI-mediated service. Government-issued credentials are still the strongest foundation for trust, but today’s verification methods often require people to hand them over. As AI agents begin acting on behalf of humans and interacting with decentralized systems, the need for fast, privacy-preserving ways to prove credentials will only grow.

These needs are already materializing in policy. Governments are moving quickly to formalize digital identity. The EU Digital Identity (EUDI) framework aims to make digital wallets available to all EU citizens, and efforts like the EU’s age-verification blueprint and the UK’s Online Safety Act mandate government ID-based methods for age checks. Application providers face a double bind: they must either use less accurate approaches like AI-based age estimation, or compromise user privacy by requiring ID uploads.

The credential gets uploaded, processed, sometimes stored, and eventually (hopefully) deleted. But high-profile breaches have repeatedly exposed government IDs that users shared for routine verification. These are not edge cases. They are the predictable consequence of a system that asks users to share their most sensitive documents to prove a single bit of information.

This is the question we set out to answer with Vega: Can we make it practical to prove something about a credential without ever revealing the credential itself?

The path to Vega: From idea to practice

Zero-knowledge proofs (ZKPs) are the cryptographic tool that makes this possible. The idea is simple: they allow a user to prove a claim, such as “I am over 21”, without revealing anything else.. In practice, this means a user could prove their age from their driver’s license without the verifier ever seeing the license, whether to a website, an app, or a service mediated by an AI agent.  The proof works directly on the credential as issued, so the issuer does not need to change anything.

so the issuer does not need to change anything. 

This is not a new idea. The challenge has always been practicality. Prior systems either require a trusted setup that had to be repeated whenever the logic changed, or they sacrificed performance to avoid the trusted setup, often producing large proofs in the process. For real-world use, the proof needs to be fast to generate, small enough to transmit quickly, and efficient enough to run on a mobile device.

We have spent several years working toward a practical solution. Privacy-preserving identity has been a motivating application (opens in new tab) throughout, and Vega’s proof system draws on several building blocks from that line of work:

  • Spartan (opens in new tab) showed how to efficiently prove R1CS, a standard way to express statements for a general-purpose proof system, with succinct proofs and without a trusted setup.
  • Nova (opens in new tab) introduced folding schemes, which let a prover compress many instances of a computation into one. 
  • HyperNova (opens in new tab) showed that Nova’s folding also provides a key building block for zero-knowledge: folding a real instance with a random instance hides the underlying secret data, a technique dubbed “NovaBlindFold.”
  • NeutronNova (opens in new tab) provided the most efficient folding scheme for handling a batch of instances at once.

Vega puts these building blocks together into a single proof system. A key design goal is simplicity. Spartan, Nova, and NeutronNova are composed in a direct way, and the circuit is built from a small number of standard components, with no exotic multi-field constructions and no trusted setup. On top of this simple foundation, Vega adds the ability to reuse work across multiple proofs of the same credential and a new way to achieve zero-knowledge with minimal overhead. The result is a system that is easy to audit, extend to new credential formats, and deploy.

Performance

Vega generates a zero-knowledge proof of age from a typical mobile driver’s license, about 2 kilobytes (KB), in 92 miliseconds (ms) on a commodity client device. The resulting proof is 108 KB and can be verified in 23 ms. No trusted setup is required. The prover key is 464 KB; it fits comfortably on any phone. For smaller credentials, proving drops to 62 ms, with 83 KB proofs, and 17 ms verification. In practice, a user taps a button to present a credential, and 92 ms later the proof is done. The service learns only the requested fact; the credential never leaves the phone.

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Start now Opens in a new tab Under the hood: Fold, reuse, and lookup

Vega’s speed comes from two ideas: fold-and-reuse proving and lookup-centric circuit design. The figure below shows the proving pipeline end to end.

Vega’s proving pipeline. Work is split into two phases. The once-per-credential phase splits the credential into step and core circuits and commits reusable data. The once-per-presentation phase re-randomizes cached commitments for unlinkability, folds all SHA-256 step instances into one via NeutronNova, proves the folded step and core circuits with Spartan, and applies zero-knowledge via NovaBlindFold. The final output is a 108 kB proof generated in 92 ms and can be verified in 23 ms.  The hashing problem, and how folding solves it

A credential proof must do two expensive things: hash the credential bytes with SHA-256 and verify the issuer’s digital signature. Signature verification would normally be the bottleneck, but  Vega avoids that cost by working in a field where the signature arithmetic is native. As a result, hashing becomes the dominant cost. SHA-256 works by applying the same compression function to one 64-byte block at a time. A straightforward circuit simply unrolls all of these iterations,so its size grows with the length of the credential. For a typical mobile driver’s license, that is 30 blocks of compression, all captured in a single circuit.

We take a different approach. Instead of unrolling the entire hash, we define one small “step” circuit that proves a single SHA-256 compression step, and we instantiate it once per block. Because these step instances are structurally identical, we can use NeutronNova’s folding scheme to collapse them into a single instance. The prover does work to fold the 30 step instances into one, but this folding cost is modest. Spartan then only needs to prove a single step-sized circuit alongside a separate “core” circuit that handles the rest of the checks, including signature verification and age predicates, rather than a monolithic circuit with 30 unrolled blocks. The proving key only needs to describe one step and one core, so it stays small regardless of credential length.

There is a subtle privacy issue here to arddress. Credentials vary in length, and if the circuit size varied with the credential, that would leak information. To prevent this, all step circuits share a committed table of intermediate digests. The core circuit picks the selects the appropriate digest using a private index. If the prover selects the wrong entry, the issuer’s signature check fails.

Making it zero-knowledge, cheaply

A proof system needs to be zero-knowledge: the verifier should learn nothing beyond the claim being proved. Existing approaches to achieve this are often complex to engineer and can add significant overhead to the prover. We found a simpler way.

A standard first step is to commit to every message the prover sends using hiding cryptographic commitments, so the verifier sees commitments rather than values. The harder question is to prove that those hidden values would have passed the verifier’s checks. We express those checks as a small constraint system, just a few hundred constraints, since the verifier only performs a logarithmic number of operations. We then fold this constraint system iwith a random instance via Nova’s folding scheme. This step hides the underlying data, so the zero-knowledge overhead scales with this small constraint system, not the full secret data.

Proving once, presenting many times

A user who presents their credential to one website will likely present it again to another, and another. In a world where AI agents handle many of these interactions on a user’s behalf, the same credential may need to be presented dozens of times a day. The credential itself does not change between these presentations. What changes is the session nonce, a fresh random value from the verifier, and possibly the date or the predicate threshold.

Vega takes advantage of this structure by by splitting the prover’s secret data into three parts. The shared data (SHA-256 tables) and the precommitted part, such as the issuer signature and field locationsm are computed and committed once when the credential is first loaded. The online part, such as the device signature and  today’s date, is committed fresh each time. Before each proof, the precomputed commitments are refreshed with new randomness, which is cheaper than recomputing them and ensures that two proofs about the same credential cannot be linked.

Avoiding the parser

Another important part of Vega’s efficiency comes from how it handles the credential format. A mobile driver’s license is encoded in Concise Binary Object Representation (CBOR), and building a full CBOR parser as a circuit would be both complex and expensive. But we realized we do not actually need a parser. The credential bytes are signed by a trusted issuer, so we know they are well-formed. We only need to reach in and grab specific fields.

We treat the credential as a byte-addressable lookup table. The prover says, “the device public key starts at byte 847” and supplies the bytes. The circuit checks three things: that the bytes actually match the authenticated credential, that the right CBOR prefix appears at the start of the field so the prover cannot claim the wrong field, and that the addresses are contiguous so the prover cannot splice bytes from unrelated locations. This replaces an entire parser with a handful of lookups.

The same lookup idea powers length-hiding hashing, as described above: the circuit builds a table of all intermediate SHA-256 digests and picks the correct one at the point where the real message ends.

Device binding

A zero-knowledge credential proof is only useful if it is tied to the person holding the credential. Without device binding, someone who obtains a leaked credential could generate valid proofs for any session. This matters even more in a world of AI agents: if an agent can present a proof on behalf of a user, we need cryptographic assurance that the proof originated from the user’s device, not from an attacker or an unauthorized agent.

Vega addresses this by requiring the holder’s device to sign a fresh session nonce with the device private key, which is bound to the phone’s secure element. The circuit extracts the device public key from the credential via lookup and verifies the device signature over the session nonce hash. Because the device private key never leaves the secure hardware, possession of the signed credential alone is not sufficient to produce a valid proof.

Where this leads

Vega is implemented in Rust and will be open sourced soon. The proof system powering Vega is already available as the open-source spartan2 (opens in new tab) project on GitHub. The paper, joint work with Darya Kaviani, will be presented at the upcoming IEEE Symposium on Security and Privacy in San Francisco. 

While we focused on mobile driver’s licenses as a concrete and timely application, especially given emerging frameworks like the EU Digital Identity wallet, the proof system and circuit techniques are general. They apply to any credential format with a stable byte encoding and a digital signature.

We see several directions where the same primitive becomes increasingly important.

Agents carrying identity on behalf of humans. As autonomous AI agents begin acting on behalf of people, whether booking travel, interacting with services, or entering agreements, those agents will need to prove facts about the human they represent. For example, “my principal is over 18” or “my principal is a licensed physician.” The agent should be able to carry these proofs without ever holding the underlying credential. A zero-knowledge proof generated on the human’s device, bound to the agent’s session via device binding, lets the agent present identity signals without holding secrets.

Bridging off-chain identity to on-chain systems. Decentralized systems increasingly need real-world identity signals, such as KYC compliance, accredited investor status, and jurisdiction checks. Today, this is handled by uploading documents to a centralized intermediary, who then issues an on-chain attestation. The user loses privacy twice: once to the intermediary, and again on chain, where the attestation may be linkable across interactions. A ZKP over an off-chain credential could bridge this directly: the user proves a fact from their government-issued credential, and the on-chain verifier receives only the proof. No intermediary sees the credential, and rerandomization ensures repeated proofs are unlinkable.

As digital identity mandates expand and AI reshapes how humans and agents establish trust, the need for privacy-preserving credential verification will only grow. We see Vega as one step in a broader shift: from a world where proving a fact about yourself requires giving up your identity, to one where cryptography lets you keep it.

Opens in a new tab

The post Vega: Zero-knowledge proofs for digital identity in the age of AI appeared first on Microsoft Research.

Categories: Microsoft

5 things that can ruin your summer road trip (and how to fix them now)

How-To Geek - Thu, 05/21/2026 - 15:45

A recent Hertz survey found that 64 percent of Americans are planning a road trip this summer, with nearly three-quarters planning to take at least one trip between June and September. That's tens of millions of people about to spend hours behind the wheel, many on highways they don't usually drive, in weather they aren't always prepared for, and pushing through fatigue to make the most of their vacation time.

Categories: IT General, Technology

Tesla says its Full Self-Driving package is now available in China

Mashable - Thu, 05/21/2026 - 15:30

Tesla has brought its Full Self-Driving (FSD) suite of driver assistance features to China – or it's at least close to doing so.

The company announced the news in a tweet on Thursday, listing all of the countries where FSD is currently available. Besides China, also new on that list is Lithuania, the second European country to get FSD after the Netherlands.

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The total list of countries where Tesla FSD is available is now as follows: Australia, Canada, China, Lithuania, Mexico, the Netherlands, New Zealand, Puerto Rico, South Korea, and the United States.

Tesla did not share any other details about FSD availability in China. Launching FSD in the vast, busy automotive market that is China would surely be a win for Tesla, especially given that many other local automakers, such as Xpeng and Xiaomi, have a similar suite of semi-autonomous driving features in the country already.

As CNBC pointed out, Tesla previously offered its Autopilot and Enhanced Autopilot suites of driver assistance features in China, while the FSD was only available to select users, and in limited fashion. China Daily, however, claims that the complete version of FSD isn't available in China yet, though "progress is under way," citing insider sources.

SEE ALSO: Someone drove a Tesla Cybertruck into a lake to test 'Wade Mode.' It didn't end well.

The news comes shortly after Musk, alongside several other American businessmen and President Donald Trump, visited Chinese leader Xi Jinping in Beijing.

Tesla customers in China currently have to pay a high price to access the most advanced autonomous driving package the company has to offer. As it stands on Tesla's Chinese website, the "Intelligent assisted driving" package costs a one-time fee of 64,000 yuan or $9,409. In the U.S., FSD is only available as a monthly subscription, at a price of $99 per month.

Categories: IT General, Technology
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