The most consequential line in Intel’s Computex announcement was not about a chip. It was about a ratio. As AI workloads move from training to inference, the company argued, the long-standing arrangement of four GPUs to every CPU collapses towards something closer to one to one, and the processor Intel actually sells well moves back towards the centre of the data centre.
That is the bet behind the partnership unveiled in Taipei on 2 June. Intel, SambaNova, and Foxconn said they intend to build rackscale AI infrastructure for data centre, hyperscale, and what Intel calls intelligence centre deployments, all built on Intel Xeon processors.
The companies showed production-ready racks pairing Xeon chips with SambaNova’s SN-50 Reconfigurable Dataflow Units, a combination pitched on inference performance per watt and per dollar rather than raw training horsepower.
Foxconn’s role is the integration layer. The world’s largest electronics manufacturer will provide system integration for the rackscale platform and plans to build a CPU-dense variant for workloads that do not need additional acceleration, including cost-optimised inference, data processing, and hybrid AI.
The two companies also said they would explore collaboration in design services and custom silicon development, the more open-ended part of the announcement and the one Intel will most want to convert into something concrete.
Intel chief executive Lip-Bu Tan framed the moment in generational terms, citing “the rise of inference, agentic, and physical AI” and Intel’s five decades of building foundational technology alongside partners in Taiwan.
The analyst case sat underneath the rhetoric. Creative Strategies principal Ben Bajarin, quoted by Intel, put the shift plainly: where the training era ran roughly one CPU per four GPUs, agentic inference moves that to one CPU to one GPU or fewer.
Foxconn was one name on a longer list. Intel also detailed expanded or new collaborations with Siemens, Hitachi, Echo Neurotechnologies, and Greenstone Biosciences, each aimed at industry-specific silicon.
Separately, a new enterprise inference cloud called Vector Core Compute, formed by Vista Equity Partners and Cambium Capital, demonstrated a fully disaggregated inference system running Xeon for orchestration, SambaNova RDUs for decode, and Nvidia Blackwell GPUs for prefill, with Together.ai as its first commercial customer.
Underpinning the rack story is Intel’s new Xeon 6+ processor, its first data centre CPU built on the 18A process. Intel said a single liquid-cooled rack can deliver 36,864 cores in 32U of space at roughly 100 kilowatts, a density figure aimed squarely at operators trying to host agents without redesigning their facilities.
What the announcement did not include was a dollar figure, an equity stake, or a volume commitment from Foxconn. It is a statement of intent between a chipmaker trying to reclaim relevance in AI, a contract manufacturer with the scale to build whatever the market orders, and a dataflow-chip start-up betting that inference economics will reward something other than the incumbent GPU. Whether the one-to-one ratio holds is the question the whole arrangement rests on. The racks are real. The thesis is still being tested.
The perfect robot mower for you is not nearly as fancy and feature-heavy as you may think. I’ve said it before, and I’ll say it again: it’s not the lawn mower, it’s all about the yard. A robot mower may be a market leader with top-of-the-line specs and still not be a good fit for your yard.
Here’s the great news: There’s a perfect robot mower for almost any yard. As someone who’s tested numerous types of robot lawn mowers, I’ve learned that many of the specs that brands market as groundbreaking are simply not vital for most shoppers. A mostly flat, fenced-in 0.10-acre yard doesn’t need the power that a hilly, sectioned, unfenced one-acre yard does.
A LiDAR, GPS, or wired boundary robot mower works for these yards. If you choose a wired boundary, you may have to bury wire around the flower beds, unless the borders are tall enough for the mower to avoid.
1. Don’t focus on: ‘AI-powered’ or other marketing buzzwords
Maria Diaz/ZDNET
Artificial intelligence (AI) has surpassed the popularity of acid-wash jeans in the 80s and Baby G watches in the early 2000s. And tech companies — including robot lawn mower manufacturers — are capitalizing on its appeal.
Most of these “AI-powered” or “intelligent mowing” terms are vague, geared to grab shoppers’ attention with buzzwords. That doesn’t mean that the robots don’t use AI to navigate, however.
The key is to find out how the robot uses AI to its benefit, and whether that will meet your AI expectations.
AI algorithms typically process data captured by the robot’s hardware to help it make quick decisions and adjustments. For example, a robot lawn mower may have a set of sensors and cameras to capture its surroundings. The robot’s processor then uses AI to convert that information into actionable data, so it knows whether to swerve to avoid an obstacle or slow down around a retaining wall.
Instead, look for: The navigation tech under (and on) the hood
Instead of AI and other buzzwords, you should focus on matching the robot lawn mower’s hardware and navigation system to your yard. This includes whether the robot uses RTK (Real-Time Kinematic) for positioning, and whether it features LiDAR, cameras, and sensors.
Then look at real user reviews to assess how accurately the robot mower maps and how well it performs around various types of obstacles.
There’s no blanket rule for robot mowers, but most do well with the following guidelines.
2. Don’t focus on: Premium extras
Maria Diaz/ZDNET
Skip the premium extras that don’t match your yard. You really don’t need the most advanced robot mower; you need the one that will best handle your lawn.
Most US homeowners have mostly flat lawns, simple rectangular layouts, minimal obstacles, and small yards. Yet some of the most popular mowers advertise features that don’t match this, and you don’t want to spend an extra few hundred dollars on advanced features that won’t deliver a noticeable difference in your yard.
Instead, look for: Only as much as you need
Do you have a mostly flat lawn with no fences and need a robot that can navigate to several sections separated by paths? Then you can skip AWD models and commit to superior mapping and navigation features, like multi-zone intelligence.
Similarly, if you have a yard with dense trees covering most of it, it’s safe to skip the RTK models and go for LiDAR or boundary wire options instead.
3. Don’t focus on: Flashy app features
The path lines created by the Mammotion Luba 2, as captured by our Bink Outdoor camera, is one flashy app feature I can’t quit.
Maria Diaz/ZDNET
Any dependable robot lawn mower requires an equally reliable mobile app to let you use it effectively. However, manufacturers market many flashy app features that end up being unnecessary for many users.
Don’t make app features the deciding factor unless it’s something you genuinely care about. Many users don’t rely on voice control to run their mowers and don’t mind using a separate app for their robot rather than integrating it into an existing home automation system.
A robot lawn mower with mediocre navigation and cutting performance can still have a flashy app — all while leaving behind missed patches or taking longer to finish mowing.
Instead, look for: The features you’ll actually use
Most robot mower users keep them running on a schedule to get the lawn-cutting chore off their minds. The majority of the most popular models offer basic features beyond scheduling, such as remote start and stop, basic mapping, automatic rain delay, and theft protection.
It’s easy to find robot lawn mowers with these features, but if you’re looking for anything beyond that, just be sure that the feature is worth it, especially if you’re paying extra for that model.
An example of a flashy app feature that is completely unnecessary, but I love having? The Mammotion’s pattern cutting. I can select the cutting pattern I want on the Mammotion app, whether I want lines or checkered, but I can also have the robot cut in custom patterns, like letters and numbers. I don’t care for mowed letters in my yard, but I like that it always has that freshly mowed checkered patterned with no effort from me.
4. Don’t focus on: Cutting system extras
Maria Diaz/ZDNET
The cutting width and system specs are important, as they can determine whether a robot can cover a given area in a day. However, most robot mowers use similar multiple-blade mulching systems.
Unlike traditional lawn mowers with large blades for aggressive cutting in a single pass, robot mowers typically feature a set of small blades that constantly spin. Because of this, robot mowers trim smaller amounts of grass with each pass than a traditional mower, but they also cut more frequently and leave behind smaller grass clippings that decompose naturally.
Because the robot mowers have a smaller, compounding cutting system, the real-world differences between the cutting systems from one brand to another are often smaller than you’d expect. Other issues, like poor navigation, will be glaringly obvious before small differences in blade design.
Instead, look for: Cutting width and yard size
The average US yard would benefit more from navigation quality, consistency, and connectivity than blade design. Instead, you should focus on matching the mower to your yard size.
The robot’s capacity is measured in how many acres it can cover in a day. Among other features, this is calculated based on your robot’s battery size and cutting width. Essentially, most users want a robot that can mow an entire yard in a day, so you can set it and forget it and always come home to a mowed yard. You get this by getting the appropriate robot for your yard size.
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