UK-based materials company IQE and Israeli chipmaker Tower Semiconductor have announced a long-term supply agreement covering indium phosphide (InP) epitaxial wafers, a key technology used to manufacture photonic components for optical networking, data centers, and artificial intelligence applications.

Under the agreement, IQE will supply Tower with InP-based epitaxial wafers used in the production of lasers, photodetectors, and other advanced optical devices. Tower plans to integrate these materials into its photonics manufacturing processes, which serve customers in optical communications and AI-related markets.

The announcement is particularly noteworthy given the companies’ contentious legal history.

In 2022, IQE filed a federal lawsuit in the United States accusing Tower of misappropriating trade secrets and proprietary know-how related to porous silicon technology, which enables advanced integration of electronic and photonic components on silicon substrates.

According to the complaint, IQE alleged that it had shared sensitive technical information with Tower during discussions about a potential collaboration under confidentiality agreements. The company claimed that Tower later filed patent applications that incorporated knowledge disclosed during those discussions. IQE sought damages and asked the court to review the inventorship of certain patents involved in the dispute.

Tower consistently denied the allegations, arguing that its patents had been developed independently and that the claims lacked merit. Legal proceedings continued for several years, but no final court ruling was issued publicly determining the validity of either side’s claims.

Against that backdrop, the new partnership suggests that both companies have moved beyond the dispute and are now focusing on the commercial opportunities emerging in the rapidly growing photonics market.

Indium phosphide has become one of the semiconductor industry’s most strategically important materials in recent years. It is widely used in high-performance lasers and optical interconnects that enable high-speed data transmission between AI processors inside modern data centers. As AI workloads continue to expand, demand for optical networking infrastructure has surged, driving increased investment across the photonics supply chain.

For IQE, the agreement secures a strategic long-term customer and a stable source of revenue in a fast-growing market. For Tower, it provides reliable access to advanced photonic materials needed to expand its position in optical communications and AI-related applications.

While neither company has presented the agreement as a formal legal settlement, the joint announcement marks a clear shift in their relationship. After four years of public litigation, IQE and Tower are now collaborating in one of the semiconductor industry’s fastest-growing sectors, turning a dispute over intellectual property into a partnership centered on the AI-driven photonics boom.

[Photo: The Intel Israel engineering team behind the development of the new capability. Photo credit: Aviv Harel]

By Yohai Schwiger

At its Build conference in Seattle, Microsoft unveiled a new capability called Confidential Live Migration, which allows encrypted virtual machines (VMs) to be moved between servers in Azure data centers without interruption. The technology was developed by a team of approximately 20 engineers from Intel Israel’s security group and is built on Intel’s TDX platform, which is integrated into the company’s Xeon server processors.

The new capability addresses one of the most significant limitations in the field of confidential computing—a rapidly growing area designed to enable organizations to run sensitive workloads in the cloud while protecting data even from the cloud provider itself. While conventional virtual machines have long supported live migration for maintenance, load balancing, and infrastructure upgrades, encrypted VMs have traditionally required downtime whenever they needed to be moved to another server.

The challenge stems from the security mechanisms that make confidential computing possible. Technologies such as Intel TDX encrypt and isolate a virtual machine’s memory at the hardware level, preventing access not only by the cloud provider’s administrators but also by the host operating system and cloud management software. This additional layer of protection is particularly valuable for financial institutions, healthcare organizations, government agencies, and other enterprises handling highly sensitive information.

“This feature is entirely an Israeli development,” said Boaz Tamir, Senior Director at Intel. “We can move an encrypted virtual machine from one server to another while it continues running, without the customer noticing anything. For customers, this means higher service availability. For cloud providers, it means greater flexibility in managing infrastructure without compromising the security model.”

According to Tamir, the architecture, development, and validation of the new capability were all carried out by Intel’s security team in Haifa. The engineering challenge involved securely transferring the VM’s execution state, encrypted memory, encryption keys, and trust mechanisms between two separate servers, while cryptographically verifying the target environment and maintaining uninterrupted service.

Bringing Secure Hardware Trust to the Cloud

At the heart of the development is Intel TDX (Trust Domain Extensions), one of Intel’s flagship security technologies for its Xeon processor family. TDX enables the creation of isolated and encrypted computing environments known as Trust Domains, where sensitive workloads can run without exposure to the host operating system, cloud management software, or even data center operators.

In essence, Intel is extending the hardware-based trust model traditionally associated with secure enclaves into the world of cloud infrastructure and hyperscale data centers.

TDX is part of the broader confidential computing movement, which has emerged as one of the fastest-growing segments of cloud infrastructure. While traditional security approaches focus on encrypting data at rest or in transit, confidential computing aims to protect data while it is actively being processed. This means that information remains protected even when loaded into server memory and being analyzed by applications or AI models.

Demand for such capabilities continues to rise as organizations move increasingly sensitive workloads to public cloud environments. Banks, insurance companies, healthcare providers, government agencies, and technology firms are seeking to leverage cloud scalability while reducing the need to place complete trust in infrastructure providers. At the same time, the rapid adoption of AI is driving new requirements for secure processing of medical, financial, industrial, and defense-related data.

Eliminating a Major Operational Barrier

For Microsoft, the new capability removes one of the primary operational constraints that have historically affected confidential computing services. Routine maintenance tasks—including server upgrades, hardware replacements, and load balancing—have often required temporary shutdowns of encrypted virtual machines.

With Confidential Live Migration, those operations can now be performed transparently, much like they are for standard virtual machines, while preserving the security guarantees of confidential computing.

The project also highlights Intel Israel’s role in developing core technologies for the global TDX platform. Unlike customer-specific software projects, TDX is a foundational element of Intel’s server security architecture. As a result, the expertise and technologies developed by the Israeli team become part of a broader platform used by cloud providers and secure applications worldwide.

As Microsoft rolls out the new capability across Azure’s DCesv6, ECesv6, DCedsv6, and ECedsv6 server families, Intel is already working on the next generation of confidential computing technologies. The company says its Israeli TDX development team is also building a new capability called TDX Connect, designed to further expand the possibilities of secure computing within data centers.

Over the past decade, competition among cloud providers has largely focused on performance, cost efficiency, and AI capabilities. In the years ahead, however, one of the industry’s most important battlegrounds may be the ability to guarantee that even the cloud provider itself cannot access customer data.

The joint Microsoft–Intel development offers a glimpse of that future: a cloud environment where security, privacy, and high availability coexist without compromise.

Defense robotics startup Shifters, which develops AI-powered autonomous ground robotic systems, has announced a $10.2 million seed funding round led by Ace Capital Partners. The round brings the company’s total funding to $15 million since its founding in 2023 by CEO Ofer Balin and CTO Asaf Tzafrak. According to the company, it has already conducted demonstrations and pilot programs with defense organizations and is working with Israel’s Ministry of Defense and the Directorate of Defense Research & Development (DDR&D). The new funding will support further AI development, commercial production readiness, and expansion into the U.S., European, and Middle Eastern markets.

Shifters emerges at a time when military robotics is gaining significant momentum. Unmanned systems have become an increasingly important component of modern warfare. In conflicts around the world—including the war in Gaza—ground robots are being deployed for reconnaissance, intelligence gathering, tunnel exploration, suspicious building inspections, and explosive ordnance disposal. The objective is straightforward: send machines into places where the risk to human life is highest.

Yet despite recent advances, ground robotics still faces major limitations. Unlike drones that operate in relatively open airspace, ground robots must navigate chaotic and unpredictable environments filled with rubble, stairs, debris, tunnels, obstacles, and structures that have never been mapped. In many cases, these systems still require close human supervision and, often, a dedicated operator for each platform.

According to Shifters’ founders, this is precisely the challenge they are addressing. While much of the robotics industry remains focused on hardware—motors, actuators, manipulators, and mobility systems—they believe the real bottleneck lies in robotic intelligence.

Four Layers of AI

At the heart of Shifters’ technology is a stack of AI models operating simultaneously. The goal is not merely to move a robot through terrain, but to enable it to understand its surroundings, interpret missions, and act autonomously in dynamic environments.

The first layer focuses on mobility and spatial understanding. Ground robots must constantly make decisions about how to move through stairs, rubble, trenches, obstacles, and narrow passages.

“One of the hardest problems in robotics is not movement itself, but determining how to move through an environment the robot has never seen before,” says Balin. “AI allows us to maximize the physical capabilities of the platform and adapt its movement to the terrain in real time.”

The company combines spatial perception, environmental understanding, and motion control. Rather than simply detecting obstacles, the robot attempts to reason about how to traverse them safely while maintaining stability and mission effectiveness.

A second layer focuses on mission understanding. Instead of executing isolated commands, the system is designed to receive a high-level objective and break it down into actionable steps.

“The technology enables the robot to receive a mission, decompose it into sub-tasks, and execute them until the objective is achieved,” says Tzafrak.

This approach draws heavily on Agentic AI, one of the fastest-growing areas in artificial intelligence. Similar to AI agents used in software environments, the system can plan, make decisions, run multiple models in parallel, and continuously adapt its actions throughout mission execution.

The same capability also simplifies operation. Rather than manually controlling every action, operators can define objectives in natural language while the AI translates intent into tactical actions in the field.

From a Single Robot to Autonomous Teams

The next layer of the technology stack focuses on coordinating multiple robots simultaneously.

“The challenge is not just building a robot that can move,” says Tzafrak. “The more complex problem is enabling multiple robots to understand the operator’s intent, coordinate with one another, and execute missions in unpredictable environments. That orchestration challenge is why Shifters was founded.”

The company’s vision is to deploy teams of autonomous platforms that function as a unified system. Rather than operating independently, robots share information, divide tasks dynamically, and respond collectively to changes in the environment.

These concepts align closely with the emerging field of Physical AI, which seeks to bridge advanced AI models and real-world physical systems. While recent AI breakthroughs have largely focused on generating digital content, the next wave is expected to move into autonomous machines operating in the physical world.

Why AI Must Run on the Robot

One of the most significant technical challenges is computing power. Unlike consumer AI applications, military robots cannot rely on cloud connectivity.

“The robot has to make decisions on its own,” says Tzafrak. “You cannot assume communications will always be available, or that computation can be offloaded to the cloud.”

According to the company, a significant portion of its intellectual property focuses on optimizing AI models to run directly on the platform itself. Shifters uses NVIDIA AI processors and develops edge AI technologies designed to operate within strict constraints involving weight, power consumption, thermal management, and physical size.

As robotic systems become more sophisticated, edge processing becomes increasingly critical. Unlike large AI models running in data centers with thousands of processors, a ground robot must make real-time decisions using limited onboard computing resources while moving through challenging terrain.

For Shifters, the ultimate goal extends beyond building another military robot. “The first entity entering a dangerous environment should be a robot, not a human,” says Balin. “If we can make that happen, we can extend operational reach while significantly reducing the exposure of soldiers to risk.”

If drones transformed how militaries observe and operate from the air over the past decade, Shifters believes that the combination of Physical AI, Agentic AI, and edge computing could drive a similar transformation on the ground. For the company, the future of military robotics will be defined not by stronger motors or more sophisticated actuators, but by the digital intelligence that enables machines to understand their world and act within it.