by Gary Mintchell | May 14, 2025 | Manufacturing IT, Sensors, Technology
Most of the interesting developments for the past several years have been in software. But not in the MES area that I began my software career working with. The companions to software have been security and artificial intelligence (AI). The AI component assumes many forms. In today’s news, we have AI assisting visual inspection (in a way a quite old application updated with new developments) integrating with MES. The companies involved are Cybord and Siemens.
Cybord, a leading provider of advanced visual-AI electronic component analytics, and Siemens Digital Industries Software have signed a new OEM agreement to integrate Cybord’s cutting-edge AI technology with Siemens’ Opcenter software for Manufacturing Execution Systems (MES). The collaboration expands a previous OEM agreement and enables Siemens to offer Cybord’s powerful AI solutions to Opcenter customers and Siemens’ factories globally.
The integration of Cybord’s visual AI platform with Siemens’ Opcenter empowers manufacturers to enhance quality control of their Surface Mount Technology (SMT) processes. The solution will provide real-time detection of defective components, help build component repositories, and integrate visually verified traceability across the supply chain. Customers will be able to streamline their operations without the need for additional dashboards as the solution is fully integrated into Opcenter MES. This integration also allows customers to take immediate action on product integrity issues, improving their ability to address problems on the fly and helping to ensure consistent product quality.
by Gary Mintchell | May 13, 2025 | Generative AI
Still more AI news. I guess you might as well buckle-up and enjoy the ride. I remember many other memes that journalists love to perpetuate. I’m not saying there is no value to AI in its many various guises, but it is far from living up to its hype, if indeed it ever will.
BitSeek introduced the first end-to-end decentralized AI infrastructure purpose-built for Web3. At the heart of the platform is the BitSeek proprietary DeLLM (Decentralized Large Language Model) protocol, designed to deliver powerful AI without the tradeoffs of being centralized and controlled by a big tech corporation. By combining distributed compute, blockchain-native model governance, and privacy-preserving architecture, BitSeek empowers users and developers to own, control, and benefit from the AI systems they use.
The BitSeek AI tech stack includes a globally distributed computing network of independent nodes, a suite of Blockchain Model-Context-Protocol (MCP), and a data DAO. These components address two core limitations of the Web3 AI ecosystem: the lack of accessible decentralized LLMs and the absence of native on-chain interactions.
BitSeek delivers high-performance decentralized LLMs and a multi-blockchain MCP suite to power the next generation of intelligent Web3 agents, accelerating the evolution of the decentralized AI industry. Furthermore, Bitseek gives users and developers full control over AI data, computation, and monetization—marking a pivotal moment for Web3 artificial intelligence.
While decentralization has transformed finance and data in the crypto space, AI has remained centralized and remains in the hands of big tech. Most AI platforms claiming to be “decentralized” still rely on centrally hosted LLMs. BitSeek changes that by introducing model atomization architecture: a novel approach that distributes open-source LLMs—such as DeepSeek R1 and Llama 3—across a decentralized, privacy-first network. This eliminates the need for centralized hosting, placing both the model and the data it processes in the hands of the community.
For users, the DeLLM infrastructure preserves the key benefits of hosting an AI model locally: full data control, enhanced privacy for sensitive topics, and freedom from corporate surveillance.
Unlike commercial AI platforms that collect and monetize user data, the BitSeek model ensures personal information remains secure and customizable to individual needs. A recent survey shows 78% of users prefer AI that doesn’t analyze their data, and 80% favor decentralized, open-source models—reinforcing ideals that BitSeek champions.
In the BitSeek ecosystem, users retain ownership of every conversation they generate, deciding whether to keep their data private, monetize it through DataDAOs, or move it to another LLM platform. This approach gives participants direct authority over how their data is used, along with a meaningful stake in AI’s growth. Meanwhile, node operators earn tokenized rewards for providing the computational power behind the AI models, strengthening the network while keeping it decentralized.
BitSeek is a foundational infrastructure for the next generation of decentralized applications. Web3 developers can integrate DeLLM models into AI dApps, social protocols, and decentralized agents, without compromising on privacy or decentralization. The system is modular, scalable, and designed to evolve with open-source AI advances, including upcoming integrations with models like Qwen and open-weight variants of GPT.
Unlike other decentralized AI efforts, BitSeek decentralizes the model itself—delivering infrastructure-level transformation for the entire crypto space.
by Gary Mintchell | May 13, 2025 | Security
Like I noted the other day, LLMs are so past tense. It’s all about Agents for marketing hype now. This release notes the release of “true” AI agents from a company called Abnormal AI. This relates to email security—which sounds like an oxymoron. These marketers do not hold back on bold claims.
Abnormal AI, the leader in AI-native human behavior security, unveiled its most ambitious product release to date—introducing autonomous AI agents that revolutionize how organizations train employees and report on risk and evolving its email security capabilities to continue to stop the world’s most advanced email attacks. In a year defined by the explosive use of malicious AI for cybercrime, Abnormal is doubling down on its mission to protect people. With its AI-native platform, Abnormal’s newest innovations bring intelligent automation to security awareness training, executive reporting, and advanced email threat detection.
In a recent survey, 53% of security leaders agreed that the effort required to run and maintain their organization’s current security awareness training program isn’t worth the impact it appears to be having. To solve this pain point, the launch of AI Phishing Coach allows organizations to replace ineffective, generic training with a personalized, autonomous AI platform. By converting real attacks blocked by Abnormal into tailored simulations for each user, it delivers instant coaching modules when users click—no more canned videos or impersonalized courses. For company-wide training, AI-generated videos are created on-demand, branded and customized to each organization’s threat landscape.
Unlike legacy training platforms that rely on static templates and outdated scenarios, AI Phishing Coach uses real-time behavioral threat data to deliver hyper-relevant training experiences. Because it’s powered by Abnormal’s behavioral AI engine, it learns from each organization’s threat environment and adapts training dynamically—providing proactive education before attacks succeed. It’s like giving every employee their own AI-powered security mentor—without adding any operational burden to security teams.
In addition to AI Phishing Coach, Abnormal is also launching AI Data Analyst to turn complex security data into instantly usable intelligence—providing admins with better reporting tools and saving teams dozens of hours in manual data aggregation. AI Data Analyst acts as an intelligent agent that proactively delivers reports directly to customers, highlighting the value Abnormal is bringing to their organization. Customers can then interact with the agent to ask follow-up questions, explore specific data points, or request customized board decks—complete with interactive slides and plain-language insights—tailored to showcase the impact of Abnormal AI on their security posture.
Earlier this month, Abnormal achieved FedRAMP Moderate Authorization in only 256 days, paving the way for federal agencies to easily adopt the platform. The company is also announcing expanded operations into Germany, with Japan and France to follow later this year. As we expand, the Abnormal Behavior Platform will be tuned for the nuances and language needs of each market.
by Gary Mintchell | May 12, 2025 | Enterprise IT, Generative AI
We have passed through the valley of the shadow of Large Language Models version of AI. Now we have moved a level to the gorge of Agentic AI. I’ve written about three posts I believe on that subject. Here is another company unveiling Agentic AI solutions.
Akka, the leader in helping enterprises deliver distributed systems that are elastic, agile, and resilient, announced new deployment options for its Akka solution, as well as new solutions to tackle the issues with deploying large-scale agentic AI systems for mission-critical applications. Already the standard for building resilient and elastic distributed systems with industry leaders like Capital One, John Deere, Tubi, Walmart, Swiggy, and many others, Akka now also gives enterprises unprecedented freedom to deploy Akka-based applications on the infrastructure of their choice. For the first time, developers now have two new options that enable them to leverage Akka to build distributed systems at scale and self-host their application or deploy their application across multiple regions automatically.
“Agentic AI has become a priority with enterprises everywhere as a new model that has the potential to replace enterprise software as we understand it today,” said Tyler Jewell, Akka’s CEO. “With today’s announcement, we’re making it easy for enterprises to build their distributed systems, including agentic AI deployments, without having to commit to Akka’s Platform. Now, enterprise teams can quickly build scalable systems locally and run them on any infrastructure they want.”
The agentic shift requires a fundamental architectural change from transaction-centered to conversation-centered systems. Traditional SaaS applications are built on stateless business logic executing CRUD operations against relational databases. In contrast, agentic services maintain state within the service itself and store each event to track how the service reached its current state.
As a result, developer teams experience very unpredictable behavior, limited planning and memory impacting agent effectiveness, hard failures at scale, opaque decision-making with zero transparency, and, perhaps most importantly, significant cost and latency concerns.
Today, Akka has introduced two new deployment capabilities:
- Self-managed Akka nodes – You can now run clusters of services that were built with Akka SDK on any cloud infrastructure. The new version of the Akka SDK includes a self-managed build option that will create services that can be executed stand-alone. Your services are binaries packaged in Docker images that can be deployed in any container PaaS, bare metal hardware, VMs, edge nodes, or Kubernetes with any Akka infrastructure or Platform dependencies. Your nodes have Akka clustering built from within.
- Self-hosted Akka Platform regions – Teams can now run your own Akka Platform region without any dependency on Akka.io control planes. Services built with the Akka SDK have always been deployable onto Akka Platform, with Akka providing managed services through the company’s Akka Serverless and Akka BYOC offerings. Akka Platform provides fully automated operations, alleviating admins from more than 30 maintenance, security, and observability duties. Both Serverless and BYOC federated multiple regions together by using an Akka control plane hosted at Akka.io.
In contrast, self-hosted regions are Akka Platform regions with no Akka control plane dependency, which teams will install, maintain, and manage on their own. Self-hosted regions can be installed in any data center with orchestration, proxy, and infrastructure dependencies specified by Akka. Since Akka Platform is updated many times each week, the installation of self-hosted regions is executed in cooperation with Akka’s SRE team to ensure stability and consistency of a customer environment.
Akka, formerly known as Lightbend, is relied upon by industry titans and disruptors to build and run distributed applications that are elastic, agile, and guaranteed resilient.
by Gary Mintchell | May 9, 2025 | Robots
Last of a series of Automate show product announcements. More technology relative to robotics. And another one working to expand the function of Cobots to moving processes.
CoboMover is a robust linear track for cobots and small industrial robots launching at Automate 2025. At the show, Güdel is also showcasing a demo on how air bearings can eliminate the need for cranes or embedded rails, moving 3,800+ lbs on a cushion of air.
Güdel will unveil the Cobomover, a 7th-axis linear track purpose-built for collaborative and lightweight robots. Designed and manufactured in Switzerland, the Cobomover extends the working range of robots up to 5 meters (16.4ft), allowing them to operate multiple workstations and perform a variety of tasks without manual repositioning.
The CoboMover is compatible with over 60 cobots and small traditional robots. It offers mounting positions at 0° and 180°. The maximum payload, including robot weight, is 78 kg (172 lbs). Its drive system utilizes a toothed belt and Güdel’s HPG045 angular gearbox. Available stroke lengths include 1000, 2000, 3000, 4000, and 5000 mm. The CoboMover has a maximum speed of 2 m/s and a maximum acceleration of 2 m/s², providing a repeatability of ± 0.05 mm.
