OpenAI family of devices plans are no longer limited to an experimental gadget hidden inside a design studio. OpenAI President Greg Brockman has confirmed that the company’s first consumer device will begin a broader series intended to reconsider how people interact with artificial intelligence.

The confirmation gives OpenAI’s hardware strategy a clearer shape without revealing the first product itself. Brockman said the company is not ready to discuss the device in detail, but described it as the first in a series that will rethink what devices should be when AI can understand language, observe context and complete tasks.

That ambition extends well beyond placing the ChatGPT app on another piece of hardware. OpenAI wants to reduce the menus, buttons, model selectors and separate applications that currently stand between a person and an AI assistant.

For Apple, Google and other established platform owners, the implication is significant. ChatGPT currently reaches consumers through devices and operating systems controlled by other companies. An OpenAI-designed product would give the company direct control over the microphones, cameras, sensors, interface and account experience through which its models interact with people. 56000

OpenAI Family of Devices Begins With io

OpenAI’s move into consumer hardware accelerated in 2025 when it acquired io Products in a transaction valued at approximately $6.5 billion.

The startup had been founded by former Apple design chief Jony Ive alongside Scott Cannon, Evans Hankey and Tang Tan. Its team included hardware engineers, designers, manufacturing specialists and product developers, many of whom had spent years working together at Apple.

OpenAI and Ive had already been collaborating before the acquisition. Their early ideas developed into physical designs, convincing the partners that they needed a dedicated company capable of engineering and manufacturing complete products rather than another software prototype.

The io team officially merged with OpenAI in July 2025. Ive and his design collective LoveFrom remained independent while assuming extensive design and creative responsibilities across OpenAI.

The structure combines OpenAI’s models and software research with a group experienced in turning new interface concepts into mass-produced consumer products. Ive’s previous work helped shape the iMac, iPod, iPhone, iPad, Apple Watch and other devices that established Apple’s modern design identity.

OpenAI has continued recruiting hardware expertise from Apple. Paul Meade, who led hardware development for Apple Vision Pro and worked on the company’s smart-glasses efforts, reportedly joined OpenAI’s hardware organization in 2026.

OpenAI also placed product-development veteran Peter Welinder in a leadership role connected to the io division. The resulting organization is not structured like a small accessory project. It is being assembled to develop products, create manufacturing relationships and support more than one form factor.

The First Device Remains Unannounced

OpenAI has not publicly confirmed the name, appearance, price or specifications of its first device. It has also not presented the product as a smartphone, pair of glasses, wearable pin or conventional smart speaker.

Recent reporting describes a portable, screen-free device designed primarily for use inside the home. The reported product resembles a compact speaker but includes a rechargeable battery, allowing it to move between rooms rather than remain attached to one location.

A camera and additional sensors would help the device understand its surroundings. Mechanical elements could allow parts of it to move, creating a more expressive physical presence than a stationary speaker waiting for a wake word.

The reported design would rely heavily on OpenAI’s latest voice technology. Instead of requiring a person to wait for the assistant to finish speaking, the system could listen and respond more naturally during overlapping conversation. Access to personal information, including messages or email when authorized, could give it enough context to handle requests rather than merely answer questions.

These details remain reported plans rather than announced specifications. OpenAI could change the hardware, features or release schedule before introducing the product.

The company is reportedly targeting a presentation during 2026 and a commercial release in 2027. Fortune separately reported that the initial design has been finalized, although development of the larger product family continues.

Why OpenAI Wants Hardware of Its Own

ChatGPT already operates across iPhone, iPad, Mac, Android and Windows devices. That wide distribution gives OpenAI access to an enormous audience without requiring it to manufacture screens, batteries or processors.

It also leaves crucial parts of the experience under the control of Apple, Google and Microsoft.

An operating system determines when ChatGPT can use a microphone, whether it can run continuously, how notifications appear and which applications it can control. Platform owners can limit background access, change default-assistant rules or promote their own AI systems more prominently.

Those restrictions matter more as ChatGPT develops from a chatbot into an agent. Answering a question inside an app requires relatively little control over the device. Completing a task across messages, calendars, files, cameras and connected appliances requires deeper access.

OpenAI hardware could be designed around those capabilities from the beginning. The assistant would not need to behave like one application among dozens because it could become the primary interface.

Brockman has described the current ChatGPT interface as too complicated, particularly as new models and tools add more controls. OpenAI’s objective is to make much of that interface disappear.

A successful device could allow someone to describe an outcome instead of opening several applications and completing each step manually. The user might ask the assistant to reorganize a day after a delayed flight, contact the relevant people and adjust reservations. The interface would be the request and the resulting confirmation rather than a sequence of taps.

A Family Creates More Context Than One Gadget

Calling the project a family of devices changes the strategy. One experimental product would need to prove its value independently. A coordinated group could distribute different sensors and functions across the places where people already live and work.

A home device could provide shared access in kitchens and living spaces. A personal wearable could preserve private conversations while moving outside. A future mobile product could handle visual information, navigation and communication without reproducing the application grid of a smartphone.

OpenAI is reportedly developing approximately five hardware concepts, with the screen-free home companion receiving priority. The company has also explored wearables and home robotics, although none of those later products has been announced.

The devices would become more useful if they shared the same ChatGPT identity, memory controls and task history. A request started at home could continue through another product without requiring the user to repeat the people involved, the desired result or the decisions already made.

That continuity is one of the strongest advantages Apple currently receives from controlling a complete ecosystem. An iPhone, Mac, Apple Watch, AirPods and HomePod can exchange information because Apple designs the devices, operating systems and cloud services together.

OpenAI appears to be pursuing a different center of gravity. Instead of making the operating system coordinate applications, it could make the AI assistant coordinate specialized devices.

ChatGPT Will Also Expand Through Other Companies’ Hardware

OpenAI’s hardware work does not mean the company intends to reserve ChatGPT for its own products.

Brockman has said OpenAI is interested in deeper integrations with smart glasses, wearables and other devices through its application programming interfaces. The company wants ChatGPT to become an interface available across hardware categories, including products manufactured by third parties.

That creates a two-track strategy. OpenAI can use its own devices to demonstrate the experience it considers ideal while allowing other manufacturers to connect their cameras, microphones and sensors to ChatGPT.

Third-party distribution would help OpenAI reach consumers who do not want another dedicated device. It would also reduce the risk of depending entirely on the success of one hardware launch.

The difficult part will be keeping those experiences consistent. A wearable may have limited battery capacity, a camera may require visible privacy controls, and a speaker may depend on cloud processing when a connection is available. OpenAI will need to define what its assistant can do reliably across products with very different technical limits.

Early AI Hardware Changed the Expectations

The first generation of dedicated AI gadgets established a warning for every company entering this market.

Humane’s AI Pin and the Rabbit R1 attracted attention by promising an alternative to application-based computing. Their launches also exposed problems involving response delays, battery life, incomplete features and tasks that remained easier on a smartphone.

Those products demonstrated that access to a language model does not automatically justify a new object. Consumers need to understand why they should carry, charge and maintain another device when ChatGPT, Gemini and other assistants already operate on phones.

OpenAI has several advantages those earlier companies lacked. It controls one of the most widely used AI services, operates the models behind the interface and has the resources to improve the software after launch. The io acquisition gives it experienced design and manufacturing leadership rather than requiring it to assemble a hardware organization gradually.

The standard will consequently be higher. A well-designed enclosure and natural voice will not be enough if the device cannot complete dependable tasks more efficiently than an iPhone or Android phone.

Apple’s Lawsuit Could Affect the Schedule

OpenAI’s expansion beyond Apple devices has also produced a direct legal confrontation with Apple.

Apple filed a federal lawsuit in July 2026 accusing OpenAI, io and former Apple employees of misappropriating confidential hardware information. The complaint alleges that trade secrets connected to unreleased products, engineering processes and suppliers were taken for the benefit of OpenAI’s hardware business.

OpenAI has denied having any interest in Apple’s trade secrets and said it was unaware of evidence giving the complaint merit. The allegations have not been decided by a court.

Apple is seeking restrictions on the use of its confidential information, along with the return of materials and financial damages. The case could require OpenAI to separate employees from parts of the project, replace suppliers or repeat engineering work if disputed information is found inside the development process.

It does not automatically establish that OpenAI’s reported product copies an Apple device. The first OpenAI design is described as substantially different from Apple’s current hardware, but the legal dispute could still affect when it can be manufactured or sold.

The First Product Will Define the Rules for the Rest

The most important details at OpenAI’s eventual hardware presentation may have little to do with the object’s shape.

A camera-equipped device that learns from activity inside a home will need unmistakable recording indicators, understandable data-retention controls and a simple method for temporarily disabling its sensors. Owners will need to know which information remains on the device, what reaches OpenAI’s servers and which memories can be reviewed or deleted.

OpenAI will also have to explain whether the product requires a paid ChatGPT subscription, how much it can do without an internet connection and whether multiple members of a household receive separate identities. Those choices will determine whether it behaves like a personal assistant, a shared appliance or a new subscription terminal.

Support for messages, calendars, music and connected appliances will require cooperation from outside companies. A device cannot replace frequent phone interactions if it remains unable to enter the services where those interactions occur.

The first model will therefore establish more than OpenAI’s industrial-design language. It will set the privacy, account, subscription and developer rules that every later member of the OpenAI family of devices inherits.

The post OpenAI Family of Devices Takes ChatGPT Beyond Apple appeared first on AppleMagazine.

In a groundbreaking advancement that bridges the gap between biological intelligence and artificial systems, researchers at Oregon State University have engineered a light-sensitive device that not only detects visual stimuli but also bio-mimics the brain’s ability to store and modulate memories dynamically. Drawing direct inspiration from the complex workings of human neural processes, this pioneering approach integrates sensing, memory, and signal processing into a single phototransistor, a feat poised to revolutionize the future of neuromorphic computing.

Traditional artificial intelligence hardware architectures typically bifurcate these essential functions—detection, memory retention, and processing—forcing data to shuttle between distinct components. This separation not only introduces latency but significantly amplifies energy consumption. The novel phototransistor developed by the OSU team disrupts this paradigm by embedding memory capabilities precisely where sensory inputs occur, vastly improving computational efficiency and speed.

Central to this device’s innovation is its ability to mimic the neurochemical processes governing memory strength and decay in the human brain. Rather than storing information with fixed permanence, the phototransistor utilizes trapped electrical charges generated by incident light to represent memories, which can then be pharmacologically tuned—via electrical gate voltages—to either reinforce or weaken these stored traces over time. This dynamic modulation reproduces the adaptive nature of biological synapses and opens unprecedented avenues for creating AI systems that can ‘forget’ as well as ‘remember,’ essential for real-time learning and adaptation.

Structurally, the device marries an oxide semiconductor acting as the electronic transistor channel with an organic photosensitive layer responsible for absorbing photons and generating charge carriers. The organic layer traps a subset of these carriers, creating a persistent local electric field even after illumination ceases. This trapped charge influences electron flow through the semiconductor channel, effectively encoding a memory of prior light exposure.

A key technical breakthrough lies in the device’s gate-tunable interface: by adjusting the voltage applied to the transistor’s gate terminal, researchers can manipulate the spatial positioning of trapped charges relative to the conduction channel at a nanoscopic level. This precise control modulates the strength of electrical interaction, allowing for programmable decay times of the optoelectronic memory—ranging from seconds to considerably longer durations. Such flexibility is vital for neuromorphic systems requiring adjustable time constants for processing temporal patterns.

The implications of this technology extend beyond simple visual sensing. By localizing both sensing and adaptive memory functions, the phototransistor can serve as a foundational building block for advanced vision systems capable of real-time data processing with exceptional energy efficiency. This novel hardware approach offers substantial improvements over conventional sensors, which often offload processing to centralized units, incurring latency and energy penalties.

Neuromorphic computing, a field striving to emulate the architecture and operational principles of the brain, stands to gain significantly from this development. The device’s capacity to embody synapse-like plasticity within a phototransistor embodies a leap toward systems that do not merely compute but adapt, learn, and optimize autonomously. Furthermore, the integration of these functionalities at the hardware level paves the way for compact, scalable AI platforms potentially transformative for robotics, autonomous vehicles, and sensory-rich IoT devices.

The research team acknowledges that the trapped charges’ mobility within the device’s photosensitive layer marks a fundamental departure from fixed-charge memory devices. By enabling charge repositioning in response to externally applied voltages, the phototransistor achieves an unprecedented degree of control over memory retention timescales—a property rarely realized in optoelectronic components designed for AI applications.

From an energy perspective, co-localizing sensing and computation reduces data transfer bottlenecks traditionally plaguing AI processors. This attribute directly addresses pressing challenges in AI hardware, where escalating computational demands often collide with limitations in battery life and thermal management. As a result, the novel phototransistor aligns with broader efforts to develop sustainable, high-performance AI technologies.

Conceived through a multidisciplinary collaboration spanning electrical engineering and physical sciences at Oregon State University, the device’s development also underscores the growing convergence of materials science with computational intelligence. By synergizing metal oxide semiconductors with organic tetracene compounds, the team harnessed complementary material properties—robust electron transport with efficient light absorption—to realize the device’s multifunctional capabilities.

The National Science Foundation’s support, alongside the efforts of researchers including Larry Cheng, Ahasan Ullah, Tasnim Sarker, Xueqiao Zhang, Andrew Ensinger, Lizhong Chen, Roshell Lamug, and Oksana Ostroverkhova, culminated in the publication of their findings in the esteemed journal Advanced Functional Materials. The study not only charts new territory in optoelectronics but also sets the stage for transformative innovation in neuromorphic computing hardware.

As artificial intelligence increasingly demands systems capable of real-world adaptability and resource efficiency, innovations like this gate-tunable neuro-phototransistor epitomize the direction forward. By drawing directly from the brain’s principles of memory modulation and energy-efficient computation, the OSU team’s technology heralds a new era where AI devices can perceive, process, and remember in ways that approximate human cognition more closely than ever before.

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Subject of Research: Not applicable

Article Title: Neuromodulator-Inspired Gate-Tunable Tetracene–Metal Oxide Phototransistor for Adaptive Optoelectronic Memory and Neuromorphic Computing

News Publication Date: 19-May-2026

Web References: http://dx.doi.org/10.1002/adfm.75942

References: Published in Advanced Functional Materials

Image Credits: Oregon State University

Keywords

Neuromorphic computing, phototransistor, adaptive memory, optoelectronics, brain-inspired AI, gate-tunable memory, oxide semiconductor, organic photosensitive material, energy-efficient AI, in-sensor computing, tetracene, neuromodulation