Razor Labs Launches DataMind AI Version 3.1

Razor Labs, a leader in AI-driven predictive maintenance solutions, is proud to announce the release of DataMind AI™ Version 3.1. This update introduces groundbreaking features that enhance data accessibility, sensor fusion, and industry coverage, driving unprecedented operational efficiency and reliability.

The latest version of DataMind AI™ introduces several powerful features designed to provide comprehensive monitoring and actionable insights for heavy industrial operations:

  • Revolutionary AI Sensor Fusion: Enhanced integration of diverse sensor data using advanced AI algorithms for precise diagnostics, ensuring equipment health is accurately monitored and potential failures are identified early.
  • Comprehensive Data Accessibility: Streamlined access and visualization of critical data through an intuitive interface, making it easier for users to interpret data and make informed decisions quickly.
  • Advanced AI-Powered Computer Vision: Improved real-time monitoring and analysis of visual data from on-site cameras, allowing for the immediate detection of issues such as conveyor belt misalignments and material blockages.
  • Proactive Maintenance Insights: Increased accuracy in predicting and preventing equipment failures using advanced AI analytics, reducing unplanned downtime and maintenance costs.
  • Business Insights: DataMind AII™ now includes enhanced capabilities that identify and analyze macro-level trends, such as the financial impact of prevented failures, energy savings, and avoided safety incidents. Leveraging sophisticated predictive maintenance technology, this tool empowers managers to make well-informed decisions, aiding in strategic planning and the efficient allocation of resources to optimize performance and safety across the site.
  • Industry Expansion: Broader applicability across multiple industrial sectors, including mining, processing, and smelting, ensuring a wider range of operations can benefit from the platform’s advanced capabilities.

“Our latest update, Version 3.1, represents a significant step forward in delivering exceptional value to our users. We’ve carefully listened to feedback and have implemented key changes that enhance performance and usability. Our goal is to continuously innovate and provide our users with the best possible experience. This update is a testament to our commitment to excellence and customer satisfaction,” said Raz Roditti, CEO of Razor Labs.

Assaf Eden, VP of Product at Razor Labs, added, “Our team has worked tirelessly to enhance DataMind AI™’s capabilities, ensuring it meets the evolving needs of our customers. The new features, such as Sensor Studio and improved AI sensor fusion, provide unparalleled insights and make it easier for users to harness the power of their data.”

What is AI missing to completely replace us?

By Michael Zolotov, AI expert, Co-Founder and CTO of Razor Labs 

A year and a half after ChatGPT burst into our lives, artificial intelligence is now high in the awareness of everyone. Hundreds of millions of people have used an AI application at least once, and the topic is at the core of the activities of companies, giant corporations, and nations. Where is it expected to advance in the coming years? What new heights, as far as we can predict, is it set to conquer? And whether (and where) does it pose a threat to us, as those who are supposed to make a living on this planet?

Tool Limitations

First, it is important to recognize that although it may seem like artificial intelligence has seen and knows everything, this is not exactly the case. The latest versions of ChatGPT and similar models are familiar with about 70% of all written content available on the internet, challenging the ability to continue training and improving them. However, they rely only on public information—what has been published and exposed to the public. This means their database lacks enormous amounts of non-public information, such as private organizational knowledge of companies. As a result, their impact within organizations is currently limited.

ChatGPT and its counterparts have led a true revolution, making vast amounts of information easily accessible. However, it is important to remember that they are still inferior to human intelligence. Unlike ChatGPT, which primarily processes text, humans see and hear their environment, giving us a deeper understanding of the world. For example, ChatGPT can easily summarize complex scientific documents but lacks basic knowledge that we consider elementary. For instance, a person can learn to drive after 30-40 hours of learning, whereas Tesla requires millions of kilometers, and its driving is still not perfect. The structure of ChatGPT and similar models does not allow them to “think deeply” or plan the answer in advance, inherently limiting the complexity of tasks they can perform.

In my estimation, it will take at least a decade to overcome these limitations and enable tools to achieve capabilities that begin to approach human intelligence. In light of this, I predict that in the near future, we will see some awakening and a better understanding of the tools’ limitations.

The Future of AI: All-Powerful Model, Specialized Niche Expertise, and Organizational Autopilot

We expect AI to use a huge variety of sensors and capabilities.This raises a significant question: Are we heading towards a supermodel that knows “how to do everything”—doctor, lawyer, accountant, mathematician, etc.? Or are we looking at a dedicated AI model tailored for a specific task? The second approach argues that if I need a dermatologist, it’s less critical for them to also have knowledge in autonomous driving or in identifying and intercepting UAVs making their way from Iran to Israel. Especially since “knowing everything” requires an enormous amount of energy—not something that fits into a small chip on a missile (and let’s remember, that missile is not exactly connected to the internet).

It seems that both approaches, the general model and the specialized AI, will coexist depending on the application. There will be applications of general “autopilot,” like ChatGPT, which is supposed to know everything about everything and, over time, will get to know us better and better. It will not only be familiar with our writing style but also with who we are and what our dreams are.  It will be able to help us write the next email in our precise and unique style, teach us a new field, and even advise us at crucial junctures in our lives, ensuring we don’t repeat past mistakes. On the other hand, there will be models with a specific purpose that specialize only in that. Guiding an interceptor missile is a great example, but also assisting doctors in diagnosing a particular disease. In the niche of specialized expertise, each such model will be more successful than the general model that knows “everything about everything.”

Another future direction, which has already begun to materialize in some places, is the “organizational autopilot.” This AI function performs actions based on organizational data and has access to all the organization’s information—from CRM and service call contents to the code itself. Such a tool can significantly enhance the organization’s operations across all levels—optimizing sales, automating customer service, training personnel, development, and more.

Will AI Replace Us?

The short answer is “no,” at least not with current technology. But it’s a bit more complex than that. A more accurate way to examine the issue is not necessarily in replacing us in jobs but in specific tasks. Broadly speaking, there are tasks that take 3 seconds or 3 minutes (such as writing an email), and those that require 3 hours or 3 days (such as strategic planning, thinking about innovative work plans, etc.). Currently, AI can assist with the former type of tasks but not with more strategic ones. This means it can help with almost any job but specifically with low-level, repetitive tasks that require shallower thought. High-level tasks that require creativity and planning will remain with humans.

Therefore, AI allows us to work at a higher level of abstraction. It gives us the opportunity to invest our time and energy more in planning and strategy and less in the precise formulation of the next email. The more a job includes a significant component of the “strategic category,” the less reason its holder has to fear AI.

Additionally, for jobs that involve significant interpersonal physical interaction, like sales or doctors who need to give personal attention to patients, AI will assist the person but not replace them.

If You Can’t Beat Them …

The latest developments in artificial intelligence are a real revolution. They have the potential to improve our productivity and increase the GDP of nations on a global scale. My recommendation is to leverage these innovative tools—while being aware of their limitations—to focus on the complex, creative, and strategic aspects of your role. Artificial intelligence can make us smarter, like superhumans surrounded by omniscient experts. By effectively integrating these tools, we can reduce the risk of being replaced by AI. And as the saying goes: “If you can’t beat them, join them.”

Michael Zolotov, 33, is an AI expert with a master’s degree in electrical engineering. He is a Co-Founder and CTO of a group of leading AI companies, including the publicly traded Razor Labs, which develops artificial intelligence technologies for asset-intensive industries; Axon Vision, which develops AI solutions for the defense market; and more. Michael also co-founded the Future Learning school, the first Deep Learning training academy for AI engineers in Israel.  

Razor Labs secured a $31.2 million Deal

Razor Labs (TASE: RZR), a leader in the development of advanced technological solutions based on artificial intelligence for industrial equipment, has signed a significant partnership agreement with a leading multinational corporation, primarily operating in the mining sector, with mining sites around the world, especially in Australia, South Africa, and the United States.

The strategic deal includes the implementation of DataMind AI, Razor Labs’ leading product, an advanced artificial intelligence system designed to streamline mining operations, predicting, identifying, and preventing machine failures to reduce unplanned shutdowns and maintenance costs. The contract has been signed for a period of eight years, with an option to extend the service supply and add functional enhancements later on.

The client will purchase licenses for the DataMind AI™ product for five years for 14 mining sites. The total annual license cost is estimated at $3.3 million. The client has committed to purchase hardware equipment for $9.1 million, mainly sensors and associated equipment required to connect the client’s machines to the product and generate the necessary data. The company estimates the expected compensation for implementation services will be about $5.6 million.

Raz Roditi, Founder and CEO: “The signing of this strategic agreement constitutes an unequivocal expression of confidence in the necessity and great value our technology generates for the mining market. After reviewing our product, the client decided to  implement DataMind AI™ extensively at a number of its global mining sites. This agreement lays the foundation and supports our marketing efforts in the mining industry and other potential sectors.”

Michael Zolotov, Founder and CTO:The product we developed uses the widest variety of sensors on the market to monitor and prevent all failures in industrial machines. Just as a doctor diagnoses diseases using CT, MRI, EKG, blood tests, and more, we understand that using vibrations alone, the most common sensor in the industry today, is not enough.

The system we developed includes over ten different types of sensors and even cameras. The artificial intelligence cross-references all the information and provides the client with a simple bottom line of all the impending failures in the machines months in advance.

The technological challenge that the 8200 unit alumni team here managed to solve is the ability to analyze and integrate such diverse types of data and to perform diagnostics of hundreds of different machine failures.

This deal allows this unique technology to generate an impact on an international scale with the implementation of 8,400 sensors across 14 mining sites. The implementation will not only lead to a tremendous optimization of production processes but also to the prevention of catastrophic failures of machines that also cause injuries to the mining sites’ operational teams.”

Tomer Srulevich, CBO: “The international experience and work with giant global companies over the past two years have allowed us to affirm the substantial need for DataMindAI™’s solution in the mining sector. The deal was woven after deep collaboration and intensive work of the teams at the client’s sites and is based on the results and impact of the technology.”

The global mining market is valued at $2 trillion, with thousands of active mining sites worldwide. While Israel does not have a mining industry, Razor Labs was chosen as the technology supplier for an international company due to the company’s innovative technology that uses the broadest range of sensors in the market to monitor and prevent all malfunctions in industrial machines.

Following the IPO on the stock market for securities in 2021, the company underwent a reorganization. The process allowed the company to bring in team members with extensive business experience to leverage the company’s advanced technological capabilities and transform from a service company to a product company, penetrating new target markets. As a result of this, DataMind AI™ was launched, a leading AI solution that is already implemented at sites in Australia and Africa, with the current deal constituting a significant strategic move highlighting the importance and potential of the company’s innovative product.