MarketWatch
중도 성향
IT/기술
First Google, now Meta? Big Tech may increasingly sell stock to bankroll $820 billion AI boom.
Stock investors may not love it — but bond investors already heavily engaged in funding the AI buildout are pleased.
🇺🇸 미국 · IT/기술 · "LOVE" · 총 25건
필터 보기현재 지수
50.0
0 = 부정 우세
50 = 중립
100 = 긍정 우세
최근 7일 기준 11,968건을 분석한 결과, 뉴스 심리지수는 50.0(균형)입니다. 긍정 1건(0.0%)·중립 11,966건(100.0%)·부정 1건(0.0%)이며, 중립 비중이 뚜렷하게 높습니다. 성향 지수는 종합 18.8(중도 균형)입니다.
Stock investors may not love it — but bond investors already heavily engaged in funding the AI buildout are pleased.
“I think the team has really experienced the loss of a loved one with the end of the mission.”
The state of Florida is taking off the kid gloves and slapping artificial intelligence kingpin OpenAI with a monster lawsuit. Florida Attorney General James Uthmeier filed an 83-page civil suit on Monday against OpenAI and CEO Sam Altman. Florida charges OpenAI with building an unregulated “wealth machine” that pushes a highly addictive, dangerous product directly ...
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It's early June, which means it's video game event season once again. Now that E3 has been gone for a few years, a bunch of showcases and presentations have started to fill the void, including big productions like Summer Game Fest Live and smaller affairs like Wholesome Games Direct. If you love following gaming news, […]
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My eyes have seen the PC gaming promised land, and it's a beautifully bright world without a shred of blurriness. It's warm, it looks lovely, and it's impeccably sharp. Also, it's expensive as hell. I've dipped my toe in this world by testing a pre-production version of the upcoming Asus ROG Strix Scar 18, which […]
Cecil Baldwin's résumé includes appearances on Gravity Falls, narrating the documentary Scream, Queen! My Nightmare on Elm Street, and performing as part of the New York Neo-Futurists theater company. But he is best known as the host of the podcast Welcome to Night Vale, a long-running fiction show that blends macabre Lovecraftian horror with absurdist […]
Dating apps are matching up with artificial intelligence as romance-seekers demand new ways to find love. Venture capitalist Matt Shumer joins "CBS Mornings" with more details.
Depending on who you talk to, AI is either the future, a cheap parlor trick or the death of creativity as we know it. But at this week’s “AI on the Lot” conference, up and coming filmmakers, developers and wanna-be showbiz entrepreneurs were all banking that AI will be their on-ramp into an insular business....
How Pope Leo XIV's Magnifica Humanitas encyclical reframes the AI debate around human dignity, storytelling, and building a civilization of love.
Steven Spielberg spoke out against AI in filmmaking during a recent appearance on Michelle Obama and Craig Robinson’s “IMO” podcast. While the legendary director said he thinks AI can be useful to “find solutions to medical issues,” he doesn’t want it taking over the creative process in Hollywood. “Where I don’t love AI is where […]
Ferrari fans don’t like the design of the new Luce EV, an electric four-door sedan that just doesn’t look like the Ferraris of old. It was designed with help from Jony Ive’s LoveFrom, but what worked for Ive at Apple isn’t working for Ferrari. The Luce’s launch immediately preceded a stock drop that even an […]
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Save on Lovehoney, including bestselling toys, lingerie, and popular gift sets for date nights, self-care, and couples’ play.
Floppy disks are several decades old—many of the disks are degrading and the data stored on them is at risk of being lost. In response, Leontien Talboom, a technical analyst at Cambridge University Libraries and Archives, led a roughly year-long project preserving floppy disks called “Future Nostalgia,” which concluded in January. Leontien Talboom Leontien Talboom is a technical analyst at Cambridge University Libraries and Archives, where she transfers material from a wide range of storage media to make them accessible to archivists. IEEE Spectrum spoke to Talboom about her work preserving data from Cambridge’s collection of floppy disks and collecting knowledge about the disks themselves. Why is it important to preserve floppy disks now? Leontien Talboom: Two reasons. First, the physical media is starting to degrade. Floppy disks are made from plastic, but they’ve got a magnetic layer of iron oxide, and that’s deteriorating. A lot of floppy disks are found in attics or garages, which means they also suffer from mold. Second, a lot of people who developed floppy disks and systems that use floppy disks are starting to retire or pass away, which means that a lot of tacit knowledge is disappearing. Whom did you go to for that tacit knowledge? Talboom: I went to the retro computing community. Their work is more around preserving these machines to keep them running [than] the data that lives on the floppy disk. But they know their stuff about floppy disks. For example, they know that in a lot of the older disks, the inside of the disk—the doughnut—gets stuck to the top. So if you flex the casing, the doughnut falls down again. If I hadn’t known that, I would have assumed that those disks in our collection were broken or corrupt. What is the most difficult part of working with floppy disks? Talboom: Accessing the files can be quite challenging if we don’t understand the file system. Within libraries and archives, we get a lot of material from machines that are not as well loved. Many of the personal computers that you had at home, such as the Amstrad or ZX Spectrum or BBC Micro, are very well documented. But a bunch of our material comes from business or research systems. They’re not as nostalgic for people, so there’s not as big a community preserving this type of material. Do you have a favorite type of floppy disk? Talboom: Five and a quarter. The weirder the system, the more frustrating and fun it is. I quite like doing that detective work. The Amstrad disk has also really stolen my heart. The popularity of floppy disks is very geographically dependent. Our library, for example, has these Amstrad 3-inch disks. But if you go to the U.S., they’re really uncommon. They weren’t able to manufacture enough of these drives, and [3.5-inch disks] took over at a certain point. But they’re really cute. What’s the best method for sustainably storing data? Talboom: The main thing is actively looking after it. A lot of the floppy disks we get in the library haven’t been accessed for 20 or 30 years, which means that you need certain special hardware to actually read them, and then work with emulators or other tools to make these file formats accessible. Now that we’ve done that work and transferred it, we can monitor it and make sure it’s not suffering from anything like bit rot. We can also make decisions around migrating it to other file formats or working on specific file systems or unknown file formats in more detail.
After months of teasers, Ferrari is offering the first full view of its Luce electric vehicle. The Luce is notable not just for being Ferrari's first EV, but for being designed in collaboration with Jony Ive and Mark Newson at their collective LoveFrom. It's also going to be Ferrari's second four-door car and its first […]
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We love this brand’s stylish storage lockers, and there's a big sale on eight colors through the end of the month.
This sponsored article is brought to you by Wetour Robotics. A field technician on a wind turbine, harness clipped, both hands on a wrench, needs to send a command to the diagnostic device hanging at her belt. A logistics worker on a loading dock, gloves on, eyes on the pallet, needs to redirect a connected lift. A person using an assistive mobility device on a crowded street wants to nudge it forward without taking out a phone or speaking aloud. None of these moments call for a smarter robot. They call for a smarter way to be heard by the machines that already exist. The industry has been building from one side The past three years of Physical AI have been a story of remarkable progress on the robot side of the loop. Companies like Boston Dynamics, Figure, and Unitree have advanced actuators, locomotion, and dexterity to a level that would have seemed implausible a decade ago. Google DeepMind’s Gemini Robotics has redefined what vision-language-action models can do in unstructured settings. The trajectory of the hardware and the foundation models is real, and it is accelerating. But there is another side to this loop, and it has been treated as a solved problem for too long. The interface between humans and machines has defaulted, for 40 years, to three input modalities: screens, buttons, and voice. Each of those assumes the user can stop, look down, and translate intent into structured commands. That assumption breaks the moment the work moves into a real environment. On a turbine. On a dock. On a sidewalk. In any setting where hands are occupied, eyes are committed, or speaking is impractical, the conventional interface stack quietly fails. Spatial Intent Fusion is the simultaneous processing of three streams of human-centered information, namely spatial position, visual context, and gestural intent: Your body is the interface. The bottleneck on the human side of the loop is becoming as important as the one on the machine side. And solving it requires a different question. Not how do we make the robot more capable, but how do we let the human participate in the computing system as naturally as the robot already does. Wetour Robotics’ bet: put the human back into the computing loop Wetour Robotics is betting that the next architectural leap in Physical AI is not about making the robot more capable. It is about making the human a first-class node in the computing network, with the same kind of low-latency, high-fidelity participation that connected devices already enjoy. Wetour Robotics’ engineers frame the problem this way: a wristband that recognizes a gesture is not enough. A camera that recognizes a scene is not enough. The information a human carries about what they are about to do is distributed across multiple channels, including where their body is in space, what their eyes are attending to, and what their muscles are preparing to do, and any single channel observed in isolation is ambiguous. Reconstructing intent reliably means fusing those channels at the operating system level, with latency low enough that the loop feels closed rather than mediated. This approach has a name. Wetour Robotics calls it Spatial Intent Fusion: the simultaneous processing of three streams of human-centered information, namely spatial position, visual context, and gestural intent, fused into a single real-time command for any connected physical device. It is the technical implementation behind a simpler positioning statement the company uses externally: your body is the interface. Orchestra is a portable intelligent hub running the operating system that handles sensor fusion, intent inference, command translation, and safety arbitration. The reference compute platform is NVIDIA Jetson Orin Nano Super, which provides enough on-device inference capacity to keep the entire control loop at the edge, with no cloud dependency on the critical path. Wetour Robotics The architecture: three layers, four engines, one loop Orchestra is not a single device but a layered platform, designed from the start to be sensor-flexible and actuator-agnostic. The architecture decomposes into three perception layers and four coordination engines. Orchestra itself is the local compute and orchestration core: a portable intelligent hub running the operating system that handles sensor fusion, intent inference, command translation, and safety arbitration. The reference compute platform is NVIDIA Jetson Orin Nano Super, which provides enough on-device inference capacity to keep the entire control loop at the edge, with no cloud dependency on the critical path. Edge inference is non-negotiable for this application. Full-chain latency from biosignal acquisition to actuator command is held under 100 milliseconds, the envelope inside which closed-loop control feels natural rather than laggy. VisionLink handles visual and spatial perception. Cameras feed into vision models that identify objects, estimate distances, and track environmental context. VisionLink is designed not as a passive recognition layer but as a real-time command generator: its outputs feed directly into Orchestra OS to be fused with biosignal data. Conductor is the biosignal pipeline. It ingests raw surface electromyographic (sEMG) data from a wrist-worn device, classifies temporal patterns into discrete gestures or continuous control signals, and outputs actuator commands. The technically interesting property of sEMG for this use case is that the signal precedes visible motion. Motor unit action potentials appear at the skin surface roughly 50 to 80 milliseconds before a finger completes the corresponding gesture. Wetour Robotics calls this property pre-motion intent sensing, and it is what allows Orchestra to anticipate user intent rather than react to it. On top of the three perception layers, Orchestra OS runs four coordination engines. The Perception Engine ingests and normalizes raw sensor streams. The Intent Engine performs Spatial Intent Fusion across modalities, resolving what the user is trying to do given where they are, what they are looking at, and what their hand is signaling. The Orchestration Engine translates intent into device-specific command sequences for any connected actuator. The Safety Engine arbitrates conflicting commands, enforces operational envelopes, and gates execution against runtime safety conditions. Wetour Robotics The trade-offs we’re honest about No system that bridges the human body and the digital world is finished. Three engineering challenges remain open, and the company addresses each with a deliberate trade-off rather than a claim of having fully solved it. Baseline stability of sEMG under motion. In a stationary user, continuous gesture recognition from sEMG is reliable. Once the user is walking, climbing, or otherwise moving, motion artifacts and electrode drift degrade the signal in ways that are difficult to fully compensate for. Rather than overpromise on continuous control in dynamic settings, Orchestra defaults to a smaller set of robust discrete gestures in complex operating environments, and reserves continuous control modes for contexts where the signal-to-noise ratio supports them. Miniaturization of edge AI compute. Running the Orchestra control loop entirely at the edge requires real on-device inference, which has historically meant trading off between compute capacity, battery life, and form factor. Wetour Robotics’ approach has been a compact carrier board paired with a thermal design and a battery module sized for all-day wearability. The result is a hub that travels with the user rather than tethering them to a desk, and that performs the full perception-to-actuation loop without offloading to the cloud. Heterogeneity of third-party device protocols. The actuator side of the loop is a fragmented landscape. Different manufacturers expose different command interfaces, different communication stacks, and different safety conventions, and a Physical AI operating system has to integrate with all of them. Wetour Robotics uses an AI-agent layer to negotiate connection and protocol translation adaptively, so that Orchestra OS can ingest data from a wide range of devices, run them through neural network models that infer human intent, and emit the right command on the right protocol for the device on the other end. Why this matters, and why it helps the rest of the field The history of computing is a history of interface revolutions. Command lines gave way to graphical user interfaces, which gave way to touch, which gave way to voice. Each transition expanded who could participate in the system and what they could do with it. The next transition is not about a new screen or a new microphone. It is about treating the human body itself as a participant in the computing network, capable of contributing intent at the same speed and fidelity that any other connected node can. The history of computing is a history of interface revolutions. The next transition is not about a new screen or a new microphone — it is about treating the human body itself as a participant in the computing network. This path is not a competitor to the work being done on humanoid robots, foundation models for embodied AI, and dexterous manipulation. It is the missing complement to that work. The hardest open problem for humanoid systems is the data: every natural interaction between a human and the physical world is a potential training signal, and most of those interactions are currently invisible to any computing system. As more humans become first-class nodes in the loop, those interactions become observable, structured, and ultimately useful for training the next generation of embodied AI, including the humanoid robots being developed today. In other words: putting the human back into the computing loop is not just about better interfaces for individual users. It is about generating the kind of grounded, in-the-wild human-machine interaction data that the broader Physical AI ecosystem will need to keep advancing. The robot side and the human side of the loop are not two competing futures. They are two halves of the same one. That is what Wetour Robotics means when it says: Your body is the interface. Learn more at wetourrobotics.com.