Tag: hardware

  • An ‘iPhone of AI’ Makes No Sense. What Is Jony Ive Really Building?

    An ‘iPhone of AI’ Makes No Sense. What Is Jony Ive Really Building?

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    At this point, phrases like ambient computing, ubiquitous computing, and even (shudder) Internet of Things may be zipping and popping around your brain. Are we back here again? If the answer is yes, it might not be a reason to despair. Béhar cites Embodied’s Moxie companion robot, ElliQ’s elder care, and the Happiest Baby robotic bassinet as examples of AI-powered devices which actually “solve specific human needs”—but it should be noted Béhar is involved in all these products. He says, “We are designing these experiences to be directly embedded into the actual physical element of these products, rather than your smartphone. This lightens the reliance to do everything on a personal device, and we find that these solutions are not socially disruptive and actually more magical in their use.”

    Just last week, Sir Jonathan Ive was handing out degrees to Royal College of Art and Imperial College graduates at the Royal Festival Hall ceremony in London, as befitting his role as an elder statesman of design. Stephen Green, head of the joint Innovation Design Engineering program between the two universities, suggests that Ive is the perfect candidate to scoop up and metabolize all the post-smartphone, post-screen experiments we’ve seen come and go over the past decade, whether that’s voice agents—which Green believes needs to be used in combination, not solo—wearables, Bluetooth beacons for greater fidelity at a location level, signal processing, olfactory sensors (OK, perhaps we’re not quite ready for that last one).

    “Historically speaking, that was the beauty of Apple with Steve Jobs,” says Green. “Ultimately a marketing person with great technological foresight, and able to, with what’s sometimes referred to as design leadership, bring an amazing team of people and investors around him to make that happen. So, obviously, Jony Ive has many of those ingredients that are needed, with the backing that can coalesce around him, to achieve amazing critical mass to do something innovative. Because a lot of the technology and possibility is out there.”

    The iPhone of AI

    The original rumors and reports referred, of course, to an “iPhone of AI,” in the sense of a super successful device that allows everyday people to access cutting-edge technology. It’s likely that the dominant component in any era-shaping system cooked up by LoveFrom and OpenAI will define itself against the iPhone. The mentions of social disruption and reliance on screens do chime with Ive’s somewhat elusive comments through the years on smartphones and social media addiction.

    Ive is on record as saying he has limited his children’s screen time. When pressed by Anna Wintour on stage at the WIRED25 Summit in 2018 as to whether we are now “too connected,” he responded: “The nature of innovation is that you cannot predict all the consequences. In my experience, there have been surprising consequences. Some fabulous, and some less so.”

    One possible kindred spirit, both in terms of breaking away from smartphone norms and San Francisco culture, is Anjan Katta, the founder of Daylight, whose DC-1 tablet goes against the grain with a 60-fps paperlike display. He says that the harmful components of our current consumer tech, including blue light, flicker, and addiction-inducing notifications, can make us sicker and more anxious. “As someone who has directly experienced the extreme downsides of modern technology, including eye strain, disrupted circadian rhythm, exacerbation of ADHD symptoms, and mental health concerns like anxiety and depression,” he says, “I wholeheartedly embrace the push to create personal computing devices that don’t consume such a large share of our time and energy.”

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  • What Are the Different Motherboard Sizes?

    What Are the Different Motherboard Sizes?

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    When you first learn how to build a PC, everything can seem super complicated, but one of the most confusing things you’ll come across is motherboard sizing. Depending on the type of case you’ve bought for your build (and what kind of hardware you want to put in your computer in general) you can have a ton of different size options. Below I’ll go through all of the main modern motherboard iterations and what they mean.

    Looking to learn more about gaming or PC gear? Be sure to have a look at our guides for the Best Gaming Keyboards, Best Gaming Mice, Best Gaming Headsets, and Best Gaming Controllers.

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    What Is ATX?

    Ever wonder why most modern computer motherboards look the same? That’s because they almost all use ATX, a standard for motherboards, power supplies, and desktop cases that defines size, position, and power delivery. This set of rules helps every component work together, regardless of manufacturer.

    For our purposes, we’re interested in the physical dimensions. Some elements, like the size and location of the ports on the back, are consistent across all of the ATX variations. Other aspects of the standard, like the width and length of the board, are indicated by their own acronyms, helping you quickly identify the size and compatibility.

    Just ATX

    Left A black packaging box for a computer component. Right A black electronic board with wires connectors and slots that...

    Photograph: Amazon

    ATX is both the name of the standard and also how we refer to the most common size. If you’ve ever cracked open the side of a computer case, this form factor will likely look familiar. Measuring in at 305 x 244 mm (12 x 9.6 inches), this size of motherboard has plenty of room for four or more RAM slots, multiple PCIe cards at several lengths, and two to four M.2 slots.

    For example: The ASUS TUF Gaming B650-Plus WiFi ($200) is a full-size ATX motherboard for the AMD AM5 platform. It boasts four RAM slots, two M.2 slots, and a PCIe 5.0 slot.

    These are a great choice for basically any PC build, from your humble living room email checker to a powerful gaming rig. They’re typically the first to release when a new generation launches, and have all the new features and options without paying a premium price. You don’t need a fancy computer to appreciate the benefits, since ATX motherboards also come in the widest variety of budgets and feature sets.

    Micro ATX

    Left A black and blue packaging box for a computer component. Right A black electronic board with wires connectors and...

    Photograph: Amazon

    A slightly smaller option, micro ATX (or mATX for short) is increasingly common, thanks to constantly improving energy and thermal efficiency. These boards are the same width as the full-size boards, but shortened on one end to be a 244 x 244 mm square. You’ll also find many of the same options and features that you can on ATX boards, without too much of a price increase, making these a popular choice for midrange gaming PCs.

    For example: The reasonably priced MSI Pro B760M-P ($99) has the CPU slot for the latest generation of Intel chips, a PCIe 4.0 slot, and only one M.2 slot.

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  • How to Build a PC (2024): Hardware Suggestions, Instructions, and More

    How to Build a PC (2024): Hardware Suggestions, Instructions, and More

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    Assembling a computer yourself is a good way to learn how they work.

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  • The Daylight Tablet Returns Computing to Its Hippie Ideals

    The Daylight Tablet Returns Computing to Its Hippie Ideals

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    “Do you mind if I hug you?” asks Anjan Katta. This is not the usual way to wrap up a product demo, but given the product and its creator, I wasn’t really surprised. Katta, a shaggy-haired, bearded fellow, he’d shown up to the WIRED office in San Francisco dressed like he was embarking on a summertime mountaintop trek. He had immediately began rhapsodizing about the idealistic early days of personal computers and the amazing figures who produced that magic, knowledge he gathered in part through my writings. And he seemed like the hugging type.

    The device Katta pulls out of his backpack—an electronic-ink-style tablet called the Daylight DC1—is very much a reflection of its creator, a spiritual object driven more by ideals than commerce. “It’s almost trying to bring back the hippie into personal computing,” he says, bemoaning the loss of that spirit. “It’s been replaced by shareholders—what’s happened to that bicycle-for-the-mind idealism?” Katta’s device wants to put us back in that saddle, pulling us out of the mire of unsatisfying empty interactions with our phones and junky apps. All he has to conquer is Apple, Amazon, Google, Meta, Microsoft, TikTok, and a public unlikely to take a monochrome gadget that costs more than $700 out for a spin. No wonder he needs a hug.

    Alan Kay, the visionary who imagined the way we’d use portable digital devices, once said that Apple’s Macintosh was the first computer worth criticizing. I think Katta wants to make the first computer worth meditating with. He hopes to join the ranks of early tech heroes by stipulating what Daylight doesn’t do—multitasking, mind-numbing eye candy, or distracting floods of notifications.

    Courtesy of Daylight Computer Co.

    Instead, the sharp “Live Paper” display quietly refreshes, a page at a time. (Katta’s team worked up its own PDF rending scheme.) The accompanying Wacom pencil lets users scrawl comments and doodles on its surface as easily as they do on their latest Field Notes memo book. Web browsing in monochrome may not have pizzazz, but it seems to lower one’s blood pressure. Daylight strives to be the Criterion Collection of computer hardware, making everything else look like The Real Housewives of Beverly Hills.

    To fully understand the Daylight device, look to Katta’s own origin story. He describes himself as “a very ADHD person who’s been a dilettante his entire life.” He was born in Ireland, where his parents had emigrated from India, and then the family moved to a small mining town in Canada. Katta couldn’t speak English well, so he learned about the world from books his father read to him. Even after the family moved to Vancouver and Katta became more socially deft—and discovered an entrepreneurial streak—he retained that wonder. He loved science, games, and books about early computer history. The only college he applied to was Stanford, because it symbolized to him the creativity of Silicon Valley people like Atari cofounder Nolan Bushnell. “It was the place where mischief makers were doing cool stuff,” he says. “Stanford was the place where I’d finally be accepted.”

    But during the years Katta attended Stanford—2012 to 2016—he became disillusioned. “I expected irreverence and innovation, but it felt like McKinsey-Goldman Sachs banker energy, because you could get rich that way,” he says. While his peers did internships at Google and Facebook, Katta spent summers climbing Kilimanjaro and trekking to Everest base camp. He loved to hang out at the Computer History Museum in nearby Mountain View, soaking up the tales of the early PC pioneers and being appalled by how the narrative of tech had shifted from charming geeks to rapacious bros.

    “What happened to everything I read in those books?” he says. “After graduation I was like, Fuck this, and went backpacking for two years.” He wound up back in his parents’ Vancouver basement, massively depressed. Katta stewed for months, reading about science—and fixating on how our devices had turned into what he saw as engines of misery. “They are dopamine slot machines and make us the worst versions of ourselves,” he says.

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  • Generative AI Doesn’t Make Hardware Less Hard

    Generative AI Doesn’t Make Hardware Less Hard

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    Things aren’t going so well for AI hardware startups.

    After years of development, startup Humane launched a $700 wearable in early April that leans heavily on artificial intelligence. The original pitch for the Ai Pin was that you no longer need to juggle different apps; its operating system can “search for the right AI at the right moment,” allowing it to play music, translate languages, and even tell you how much protein is in a palmful of almonds. And because it doesn’t have a traditional display, the Ai pin was supposed to be a tiny tincture for the disease of screentime; smartphones were on their way out.

    The pin has been panned. WIRED’s Julian Chokkattu scored the Ai Pin a 4 out of 10. Popular YouTuber Marques Brownlee complimented the device’s hardware design but still called it “The Worst Product I’ve Ever Reviewed … For Now.” The company has since massaged the message that it’s meant to replace your phone. Humane co-founder and chief executive Bethany Bongiorno has been fastidiously responding to displeased customers—and some fanboys—on Twitter, with apologies, assurances that improvements are coming, and video demos of the gadget’s UI, which replaces the smartphone in your palm by projecting lasers onto your palm.

    Humane appears to have lost the thread on its own product launch, and it’s not alone. The cheaper Rabbit R1, which was sold for $200 as a generative AI “pocket companion” and generated a lot of initial excitement, has now been labeled “underwhelming,” “half-baked,” “undercooked” and “unreliable.” WIRED’s Chokkattu gave it a 3 out of 10, while some people have questioned the way the device handles logins for outside apps such as Uber.

    These early hardware #fails aren’t unprecedented. Plenty of startups have overpromised in marketing and then built and shipped lackluster products. Competing in hardware is especially difficult in the age of Tech Giants, whose ecosystems rule over all. Developer Ben Sandofsky surmised that the Humane cofounders’ adherence to the “Apple Way,” or toiling in a secretive vacuum, is partly to blame. They spent years polishing that singular product the way a giant tech company would, he wrote in a blog post, but with $230 million in venture capital funding instead of billions in cash stores.

    But both Humane and Rabbit appear to have made another error in judgment: Both were banking on AI excitement in the ChatGPT era to capture early customers and keep themselves out of the gadget graveyard. Instead, they rode the AI hype train straight into a non-working brick wall. It turns out generative AI doesn’t make hardware any less hard.

    Expensive Flops

    “To really create a great new AI device you have to have both hardware and software figured out, and the question with some of these startups is how much of that software layer is just a skin,” says MG Siegler, a partner at GV, Alphabet’s venture capital firm.

    Sielger says that tech incumbents now have an even bigger advantage, because they can build using their own infrastructure and afford to lose money while they’re iterating on new versions of products. While startups are attempting to launch their scrappy AI products out of nothing, Meta, Google, Microsoft, and Apple can tap existing teams and services to put AI assistants into infinitely wearable sunglasses, churn out phones with built-in generative AI search, create designated keys for AI on their laptops, and pack their tablets with “outrageously powerful” AI chips.

    “Bigger tech companies are able to have five shots on a hardware product whereas a startup may only have one,” says Jacob Andreou, an investor at Greylock who spent several years growing products at Snap. “The odds of one of these smaller companies raising a future fundraising round after releasing an expensive flop are not good odds.”

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  • Roundtables: Inside the Next Era of AI and Hardware

    Roundtables: Inside the Next Era of AI and Hardware

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    Recorded on April 30, 2024

    Inside the Next Era of AI and Hardware

    Speakers: James O’Donnell, AI reporter, and Charlotte Jee, News editor

    Hear first-hand from our AI reporter, James O’Donnell, as he walks our news editor Charlotte Jee through the latest goings-on in his beat, from rapid advances in robotics to autonomous military drones, wearable devices, and tools for AI-powered surgeries.

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    • A new satellite will use Google’s AI to map methane leaks from space

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  • To Build a Better AI Supercomputer, Let There Be Light

    To Build a Better AI Supercomputer, Let There Be Light

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    GlobalFoundries, a company that makes chips for others, including AMD and General Motors, previously announced a partnership with Lightmatter. Harris says his company is “working with the largest semiconductor companies in the world as well as the hyperscalers,” referring to the largest cloud companies like Microsoft, Amazon, and Google.

    If Lightmatter or another company can reinvent the wiring of giant AI projects, a key bottleneck in the development of smarter algorithms might fall away. The use of more computation was fundamental to the advances that led to ChatGPT, and many AI researchers see the further scaling-up of hardware as being crucial to future advances in the field—and to hopes of ever reaching the vaguely-specified goal of artificial general intelligence, or AGI, meaning programs that can match or exceed biological intelligence in every way.

    Linking a million chips together with light might allow for algorithms several generations beyond today’s cutting edge, says Lightmatter’s CEO Nick Harris. “Passage is going to enable AGI algorithms,” he confidently suggests.

    The large data centers that are needed to train giant AI algorithms typically consist of racks filled with tens of thousands of computers running specialized silicon chips and a spaghetti of mostly electrical connections between them. Maintaining training runs for AI across so many systems—all connected by wires and switches—is a huge engineering undertaking. Converting between electronic and optical signals also places fundamental limits on chips’ abilities to run computations as one.

    Lightmatter’s approach is designed to simplify the tricky traffic inside AI data centers. “Normally you have a bunch of GPUs, and then a layer of switches, and a layer of switches, and a layer of switches, and you have to traverse that tree” to communicate between two GPUs, Harris says. In a data center connected by Passage, Harris says, every GPU would have a high-speed connection to every other chip.

    Lightmatter’s work on Passage is an example of how AI’s recent flourishing has inspired companies large and small to try to reinvent key hardware behind advances like OpenAI’s ChatGPT. Nvidia, the leading supplier of GPUs for AI projects, held its annual conference last month, where CEO Jensen Huang unveiled the company’s latest chip for training AI: a GPU called Blackwell. Nvidia will sell the GPU in a “superchip” consisting of two Blackwell GPUs and a conventional CPU processor, all connected using the company’s new high-speed communications technology called NVLink-C2C.

    The chip industry is famous for finding ways to wring more computing power from chips without making them larger, but Nvidia chose to buck that trend. The Blackwell GPUs inside the company’s superchip are twice as powerful as their predecessors but are made by bolting two chips together, meaning they consume much more power. That trade-off, in addition to Nvidia’s efforts to glue its chips together with high-speed links, suggests that upgrades to other key components for AI supercomputers, like that proposed by Lightmatter, could become more important.

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  • There's No AI Without Nvidia. Meet the CEO Powering the Future

    There's No AI Without Nvidia. Meet the CEO Powering the Future

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    Tech companies can’t get enough of this tech company. Earnings are off the charts. WIRED probes the mind of its CEO, Jensen Huang.

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