At CES last year, Sony teased an AR/VR headset prototype focused on "spatial content creation." And at the same time, Siemens announced it was working with Sony to use that same hardware, including the two new controllers it developed, for something it was calling the "industrial metaverse." That's a lot of buzzwords, but at CES 2025 both Siemens and Sony showed the headsets and associated software in action which helped clear up a lot of what the companies are trying to do here. During Sony's CES press conference, it announced its XYN brand of software and hardware solutions, with the headset being a key part of the equation. The XYN "spatial capture solution" uses mirrorless cameras to scan and make photorealistic 3D objects. Using the XYN headset, you can see those objects in 3D production software for animation, video games and other potential uses.

Programmable Logic Controllers (PLCs) are microcomputers essential for automating factory operations. Structured Text (ST), a high-level language adhering to the IEC 61131-3 standard, is pivotal for PLCs due to its ability to express logic succinctly and to seamlessly integrate with other languages within the same standard. However, vendors develop their own customized versions of ST, and the lack of comprehensive and standardized documentation for the full semantics of ST has contributed to inconsistencies in how the language is implemented. Consequently, the steep learning curve associated with ST, combined with ever-evolving industrial requirements, presents significant challenges for developers. In response to these issues, we present AutoPLC, an LLM-based approach designed to automate the generation of vendor-specific ST code. To facilitate effective code generation, we first built a comprehensive knowledge base, including Rq2ST Case Library (requirements and corresponding implementations) and Instruction libraries. Then we developed a retrieval module to incorporate the domain-specific knowledge by identifying pertinent cases and instructions, guiding the LLM to generate code that meets the requirements. In order to verify and improve the quality of the generated code, we designed an adaptable code checker. If errors are detected, we initiate an iterative self-improvement process to instruct the LLM to revise the generated code. We evaluate AutoPLC's performance against seven state-of-the-art baselines using three benchmarks, one for open-source basic ST and two for commercial Structured Control Language (SCL) from Siemens. The results show that our approach consistently achieves superior performance across all benchmarks. Ablation study emphasizes the significance of our modules. Further manual analysis confirm the practical utility of the ST code generated by AutoPLC.

In this technology-driven world, the uptake of artificial intelligence in business is accelerating at a faster pace. From Google and Amazon to Apple and Microsoft, every major tech company is working hard to set its dominance in the artificial intelligence field. Through business acquisitions and in-house AI development, the creation of new Artificial intelligence companies has access to a multitude of AI applications. Today, the most promising artificial intelligence companies offer unique and advanced AI algorithms at fast speed and more reliable solutions at competitive rates. Businesses across the globe are leveraging the benefits of Artificial Intelligence to optimize processes or automate workflow. These companies are taking an innovative approach to machine learning and AI; their forward-thinking approach has resulted in unique ways to utilize artificial intelligence.

They already are, but may not realize it since many tools are used by clinicians behind the scenes in radiology and imaging, explained Peter Shen, head of digital health at Siemens Healthineers North America. But increasing personalized medical care by using AI tools is something Siemens is continuing to refine and prioritize. "Our strategy for AI goes beyond imaging and pattern recognition," Shen said. "The informed diagnostics we derive from AI allow us to design better ways to take care of patients. For us, it is about more than efficiency and more than just decision-making. We want to start to drive personalized medicine toward the patients themselves and create accessibility in medical care."

Artificial intelligence applications have been growing rapidly in a variety of industrial technologies, ranging from data analytics and quality inspections to autonomous mobile robots. Now the technology is being applied to robotic grasping applications to enable accurate picking and placing of random objects in unstructured and changing environments. Siemens says it is working to "democratize artificial intelligence (AI)-enabled robotics by encapsulating systems for complex problems in easy-to-use software." To this end, the company is developing an as-yet-to-be-named software technology designed for use by system integrators and OEMs to create cost-effective, advanced AI-driven piece-picking systems that can "reliably pick and place objects that are unknown to the system at runtime." Traditional automated pick-and-place systems follow fixed, pre-programmed routines in a structured environment.

Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. This was AI race week, seemingly, and Google, Nvidia, AT&T, Siemens and your local retailer were all there. At the pole position, Google held an AI event on Wednesday. In addition to announcing the company's recent advances in AI technology, CEO Sundar Pichai made the case for responsible AI, saying, "We see so much opportunity ahead and are committed to making sure the technology is built in service of helping people, like any transformational technology." Nvidia has entered the speech AI race (currently dominated by Google and Meta) by partnering with Mozilla Common Voice.

Hannover Messe (or Hannover Fair), the #1 global industrial tradeshow, was back in action earlier this month. The event that took place from 30 May–02 June 2022, in Hannover, Germany, showcased once again the latest developments and industrial technology trends. Despite a much smaller crowd (75,000 visitors--roughly 40% of pre-pandemic levels), the fairgrounds were buzzing and filled with senior executives from many of the leading industrial hardware, software, and service providers. The conference remains one of those rare fairs where you randomly walk into senior executives, like a Head of Engineering for a major industrial conglomerate, and not only into the pre-sales representatives giving you the usual pitch. "In the face of disrupted supply chains, rising energy prices, inflation, and climate change, it was all the more important to meet face-to-face again in the exhibition halls after two years marked by a pandemic, to take in the latest technology trends and get a window to the future."

Off the Italian coast, something amazing is happening under the surface of the sea. Resembling a bloom of giant jellyfish anchored to the ocean floor, a new form of agriculture is growing in Nemo's Garden. These large clear domes, or biospheres, are a unique new type of underwater greenhouse. These biospheres harness the positive environmental factors of the ocean – temperature stability, evaporative fresh-water generation, CO2 absorption, and natural protection from pests – to create an environment ideal for growing all manner of produce. The brainchild behind Nemo's Garden is Sergio Gamberini, president of diving equipment manufacturer Ocean Reef, who in 2012 was challenged by a friend to combine his experiencing designing diving equipment with his passion for gardening – but he had no idea that it would turn into a new business with a vision of creating more food for the population.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. The basic idea behind the concept of digital twins, is to help model aspects of the physical world in software. According to a forecast from Fortune Business Insights, the market for digital twin technology and services will generate an estimated $8.9 billion in revenue in 2022, growing to $96 billion by 2029. Industrial technology giant, Siemens, has long been modeling different elements of the real world in software, and it is now looking to advance its approach to enabling an industrial metaverse. To support its efforts, today, Siemens detailed an extended partnership with Nvidia to enable artificial intelligence (AI) digital twin capabilities.

Siemens, a leader in industrial automation and software, infrastructure, building technology and transportation, and NVIDIA, a pioneer in accelerated graphics and AI, announced an expansion of their partnership to enable the industrial metaverse and increase use of AI-driven digital twin technology that will help bring industrial automation to a new level. As a first step in this collaboration, the companies plan to connect Siemens Xcelerator, the open digital business platform, and NVIDIA Omniverse, a platform for 3D design and collaboration. This will enable an industrial metaverse with physics-based digital models from Siemens and real-time AI from NVIDIA in which companies make decisions faster and with increased confidence. The addition of Omniverse to the open Siemens Xcelerator partner ecosystem will accelerate the use of digital twins that can deliver productivity and process improvements across the production and product lifecycles. Companies of all sizes will be able to employ digital twins with real-time performance data; create innovative industrial IoT solutions; leverage actionable insights from analytics at the edge or in the cloud; and tackle the engineering challenges of tomorrow by making visually rich, immersive simulations more accessible.