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 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 5, 2025 | Software
Ah, competition for Adobe. And finding good, small application for AI beyond all the hype we hear. Foxit has upgraded its AI Assistant within the Foxit PDF Editor.
The enhanced AI Assistant includes features such as chat with image, multiple document analysis, automatic bookmarking, and additional read-aloud options. A new tab in the ribbon toolbar also provides users with streamlined access to the powerful suite of AI-driven tools designed to simplify and supercharge document management workflows.
The dedicated ribbon tab refers to a specific, clearly labeled section within the top toolbar (aka the “ribbon”) of the Foxit PDF Editor interface that is solely focused on AI tools. Think of the ribbon as the strip of tabs at the top of applications like Microsoft Word or Excel – where you see tabs like “Home,” “Insert,” “Review,” etc. A dedicated ribbon tab means Foxit has created a new, standalone tab specifically for its AI Assistant, placing AI-related tools – like AI Chat, Document Translation, and AI Bookmark – in one easily accessible spot. This kind of integration signals a shift from AI being a hidden or secondary feature to becoming a core part of the user interface and user workflow.
What’s New in Foxit’s AI Assistant:
- AI Chat Enhancements
- Chat with Images – Users can now upload images to extract the text in the image, translate the text, or even describe the image.
- Analyze & Compare Multiple Documents
- Easily extract key details and compare content across multiple PDFs simultaneously.
- AI Bookmark
- Automatically generate bookmarks based on document structure or specific page ranges, making navigation and organization easier than ever.
- Intelligent Read
- Documents can now be read aloud with improved voice options, enabling hands-free review and improved accessibility.
by Gary Mintchell | Apr 25, 2025 | Generative AI, Manufacturing IT
AVEVA held its AVEVA World event a couple of weeks ago in San Francisco. I was not in attendance. I also didn’t see a bunch of news. There is this one piece I saw. Partnerships being all the major trend lately, several partnerships were announced.
- AVEVA is partnering with Databricks to revolutionize industrial operations with a secure and open approach to data and AI.
- AVEVA is also announcing a strategic partnership with Track’em, a cutting-edge material tracking and mobility solution provider, to deliver real time visibility and cost control in capital projects.
Parsing through the marketing speak, the company is using generative AI for piping design. I’ve seen a few companies finding a use for the new hot tech assisting design engineers.
by Gary Mintchell | Apr 24, 2025 | Manufacturing IT
Catching up on some older news items from earlier this month. This news from Yokogawa shows how process automation companies have had to expand their offerings and problem sets to solve in this era of process automation and control market maturity. This new product is said to deliver holistic lifecycle management and operational excellence.
Yokogawa Electric Corporation announced the launch of OpreX Plant Stewardship, the most comprehensive lifecycle service program in the company’s OpreX Sustainable Maintenance family, to support customers in achieving and sustaining operational excellence.
OpreX Plant Stewardship offers a tailored, performance-based approach that strategically addresses the ever-evolving challenges faced by customers, enabling them to mitigate risks, effectively manage operational challenges, and achieve key performance indicators across all levels of their organization. OpreX Plant Stewardship is available in all regions outside of Japan.
With the acceleration of plant complexity, IT/OT integration, cybersecurity threats, and a shortage of skilled resources, traditional product-centric maintenance methods are no longer sufficient. In response to these issues, Yokogawa has expanded its lifecycle services portfolio with a program that ensures service performance across systems, field instruments, analyzers, software, and applications.
Main Features
1. A customer-centric lifecycle approach
OpreX Plant Stewardship is a service program designed through a strategic framework to drive long-term operational excellence. By proactively and systematically addressing risks and challenges, organizations can align their operational strategies with business objectives. Through this approach, Yokogawa works closely with various stakeholders across different levels of the customer’s organization, helping customers navigate complex demands and ultimately find the economic optimum that balances performance, cost, and sustainability.
2. Comprehensive coverage of five dimensions
Leveraging decades of domain expertise, Yokogawa’s service approach is built to provide coverage on five essential dimensions that drive a well-operated, efficient, and resilient business throughout the plant lifecycle:
- Safety & security: Ensuring robust operational safety and cybersecurity measures are in place
- Reliability & availability: Eliminating plant disruptions and improving equipment reliability
- Regulatory compliance: Ensuring compliance with evolving industry regulations while supporting relevant Sustainable Development Goals
- Operational efficiency: Enhancing process efficiency and reducing waste
- Investment efficiency: Optimizing asset investments to maximize long-term value
3. Four-step process for continuous engagement
The four-step engagement model ensures effective collaboration with customers:
- Identify: Understanding customer challenges, priorities, and operational risks through an assessment model
- Assess: Evaluating which services and solutions are best tailored to address customer pain points and achieve their operational goals, and crafting a tailor-fitted, long-term collaboration proposal
- Control: Ensuring seamless and effective global delivery of the services and commitment to high-quality output
- Review: Continuously supporting customers through long-term engagement and improvements, utilizing a structured feedback loop to ensure ongoing performance alignment and adaptation to evolving operational needs
Major Target Markets
Oil and gas, petrochemicals, chemicals, renewable energy, power, pulp and paper, pharmaceuticals, food, mining, iron and steel, water distribution, and wastewater treatment.
Applications
- Risk-based performance assessment and improvement
- Lifecycle management and mitigation strategies
- Maintenance and reliability enhancement
- Compliance support and regulatory alignment
- Operational performance optimization
by Gary Mintchell | Apr 23, 2025 | Software, Standards, Sustainability
While I am on a standards reporting kick, this news reflects the growing collaboration among formerly competitive standards development organizations. I wrote recently about how OPAF is actively taking an end user view into standards collaboration and rationalization. Working together usually brings benefits to users.
From the statement of purpose: Accurate energy consumption data is essential for companies aiming to achieve climate-neutral production. To support this goal, a consortium of organizations has recently published a groundbreaking specification for interoperable and efficient energy management in industrial and process automation.
\A key goal of the mechanical and plant engineering industry is to achieve climate-neutral production in the future. This effort is supported by the European Union’s European Green Deal, which aims to make Europe climate-neutral by 2050. In order to achieve this goal and implement many other use cases, accurate data on energy consumption in production is crucial. The consortium, consisting of the organizations ODVA, OPC Foundation, PI and VDMA, has now jointly published version 1.0.0 of their groundbreaking specification for interoperable and efficient energy management in industrial automation and process automation. This group is chaired by the VDMA.
Dietmar Bohn, Managing Director of PNO, explains: “The measurement and analysis of energy consumption in machines and systems is an extremely important topic for the future. We are pleased to make an active contribution to this important initiative to optimize energy consumption and thereby reduce the harmful effects on the environment caused by waste and surplus.”
This specification defines a standardized information model based on OPC UA that enables comprehensive energy management in industrial automation. “This Power Consumption Management collaboration ensures that end users have a highly standardized and interoperable means of achieving their environmental, social and governance (ESG) goals,” explains Dr. Al Beydoun, President and CEO of ODVA.
The introduction of this standard will make energy management in industry considerably easier: companies can now record, analyze and use precise and consistent energy data even more efficiently in order to further increase their energy efficiency. This not only helps to reduce operating costs, but also to reduce the ecological footprint. Standardization makes it possible to implement innovative technologies and best practices faster and more effectively, which contributes to more sustainable and environmentally friendly production in the long term.
The specification essentially comprises two main content fields: Firstly, monitoring, i.e. the display of all types of energy consumption, including electrical energy as well as energy from air, water or coal. Secondly, standby management, which is understood to mean the control and display of various energy-saving modes on machines and components. It is based on the results of the research project “Development of energy management interfaces for IoT technologies (IoTEnRG)”. “The aim of the IoTEnRG research project was to make the results available to industry. We were able to contribute our results directly to the Joint Working Group and thus significantly accelerate the development of the OPC UA Companion Specification,” says Prof. Dr. Niemann from the Institute for Sensor Technology and Automation at the University of Applied Sciences and Arts in Hannover.
“For digitalization, we need an agreement on a common understanding and description of data, including in the energy sector. OPC UA provides exactly that. I am proud that with this joint group, we can also contribute to the energy transition and thus promote optimized energy savings through standardized and efficient monitoring,” says Stefan Hoppe, President of the OPC Foundation.
The VDMA has defined a fundamental standard for the entire mechanical and plant engineering industry, known as “OPC UA for Machinery”. Various functional building blocks are specified in this standard. A new building block for energy management is being developed based on the publication. “The four organizations have been working hard to harmonize and standardize information on energy consumption in manufacturing. This is an excellent first step towards defining an upcoming OPC UA Building Block for mechanical engineering that will bring the machine and plant manufacturing industry a big step closer to the goal of climate-neutral production,” says Andreas Faath, director of the VDMA Machine Information Interoperability department.
