Consciousness is not a computation, it is quantum

Consciousness is not a computation, it is quantum

A lot of the new hype arounf the Artificial Intelligence (AI) is directly related with the potentiality for imitate or overcome the capabilities of the human brain (in terms of data volume managed and process speed) using computers. The neuroscientist Henry Markram in 2009 announced a project that pretend to simulate the human brain in a super-computer with different objectives such as “understanding perception or reality and maybe even undertanding physic reality as well”.

The so-called “technological singularity” established how the AI and robotics will surpass us humans. There are different predictions about when will occur this “apocalypse”. Elon Musk figured it out this singularity in 2025, the Russian millionaire Dmitri Itskov in 2045, to cite some examples. The continuous advance of microprocessors capabilities also feeds, wrongly, the hype of the AI. If someone compares only the numebr of neurons (around 86,000 million) with the number of transistors of the last M1 chip from Apple (16,000 millions) may be tempted to ensure that the “computation capacity” of the human being is easily overcome. I know, comparisons are hateful, and in this case, very daring.

Until very recently I was already among the expectant of such predictions, but with a reasonable scepticism degree. All this changed for me in the crudest of the confinement of 2020. I was wandering around YouTube in search of interesting videos related to AI and I came to a very curious one that gives the title to this post, and that attracted my curosity: 1consciousness is not a computation. In this video, a more than kucid Sir Roger Penrose, physicist, mathematician and philosopher, is interviewed by the vlogger Lex Fridman, expert in AI and autonomous driving.

I have to say that, even the scientific level of what is exposed in the video is very high, the lucidity, detail and kindness shown by Penrose, caught me and got me to be attentive throughout the whole interview. Specially, there is a part that sticks me on the chair, and makes me rewind several times to try to understand as much details as possible. The interview starts directly with this devastating thesis: “I´ m trying to say that whatever consciousness is, it´ s not a computation…it´ s not a physical process which can be described by computation”.

During the interview, Penrose explains how his curiosity about neurophysiology led him to explore the basic principles of the physic, cosmology, mathematics and philosophy in his book in 1989 “The Emperor´ s New Mind” to propose that human thinks could never be emulated by a machine, against the “mainstream” thesis of those times about how computers using artificial intelligence could soon make everything a human can do.

Which leads him to assure so bluntly the impossibility of emulating human consciousness by using a computer? It is not supposed that joining several chips of our computers one could overcome the number of neurons of our brain and its capacity of computation (if you allow me this crude comparison)? Just like life isn´ t a set of cells grouoed in organs, the “emulation” of the brain capacities is not a question of grouping a high number of transistors and their electrical impulses. We all remember the explanations of how neurons transport information throughout electrical impulses. In his analysis of the brain physiology, Penrose, even at the final of his book could not get to explain completely how it was possible that the nervous signals could transmit by electrical impulses consistently across the brain. Something did not fit or was missing in his theory. But it seems that, to a reader of his book, the anaesthesiologist Stuart Hameroff, was to the only one that figured it out. “I think you have missed something, don´ t you know what microtubules are?”- said to Penrose. “Is what you need to amke your theory work”. Microtubules could be the answer to the Penrose search about a no computable source in the human consciousness, from a physiological point of view.

But what the hell are microtubules? May molecular biologists forgives me, but it seems that they are molecular structures of tubular shape that we can found in different cells of our body, from red blood cells to neurons. These structures that “inhbait” the interconnections of our grey cells, have the property of conserving their state in a very effective way (quantum type state, but we will leave this for another post) and allow us to somehow return to being the same as we were after a loss of consciousness, for example, after and anaesthesia. We could say that microtubules are the basic storage unit (quantum) of our brain. Some scientifics call them “the neuron brain“.

Another reason for being able to aspire to emulate the brain has been to be able to replicate the number of connections that exist in our neurons. It´´ s a pretty big number actually. It is estimated that each neuron has an average of 1,000 connections. With 86,000 million of neurons this would give us about 86 trillion of connections or so. Even though the numbers give vertigo, for some experts they seems achievable with the current calculation capacity in operations per second (FLOP) of the processors. Going back to Apple´ s M1, this processor declares to be able to carry out 2.6 TFLOP, 2.6 billion operations per second (10 to the 12th). Again, a number apparently “near” to our connections if we join a lot of chips working at the same time. But it seems that consciousness is something more than connections, right?

If we focus only on the quantitative question and we return to microtubules that inhbait our neurons, how much of them can we have? Neurobiology said that inhabit our neurones, how much of them can we have? Neurobiology said that more than 1,000 microtubules per each one of our 86,000 million of neurons, that is, 86,000,000,000,000 micortubules (86 billion, similar to the neural connections) that “stores quantum information” in which some scientifics affirm, our consciousness live. We can say that actually our brain is a quantum computer, don´ t you think? Wow, sorry to fall back into a computational analogy. Let´´ s go back to the technology to conclude this post. IBM, promises a quantum computer of 1,000 qubits for 2023. Quite inferior to the 86 billion microtubules of our head. In my humble opinion, and comparing only quantitative aspects of actual and future computation capacities, the so called “technological singularity” as a promise of overcoming our human capacities only with actual computer technology and artificial intelligence i still very far away or seems almost unattainable. I don´ t know about you, but I still see a little bit far away the technological singularity, don´ t you think?

1 Human beings’ ability to recognize and relate to the surrounding reality

Industry 5.0, seriously?

Industry 5.0, seriously?

It seems unbelievable, but 5 years have passed since CARTIF inaugurated the blog with the post on Industry 4.0 in which I analysed some of the keys to the so-called “fourth industrial revolution” and how it could affect the industry in our country. It has always seemed risky to me to try to define this revolution from within itself. I suppose that time and the historical perspective will make it clearer if it really has been a revolution or simply a technological mantra. Fasten your seat belts because if we have not yet assimilated this revolution now they “threaten” us with the next one, Industry 5.0, they call it. Original, isn’t it?

If the fourth promised to interconnect the productive means of the entire value chain to make a transition to the intelligent industry or Smart Industry (everything has to be Smart as when many years ago any self-respecting appliance needed to carry “fuzzy logic” on-board). The fifth industrial revolution tries to humanize the concept beyond just producing goods and services for economic profit. The challenge of this revolution is to include social and environmental considerations in its purpose. Keywords if this revolution, as defined by the European Commission, should include human-centric approach, sustainability and resilience.

By developing innovative technologies with a human-centric approach, Industry 5.0 can support and empower workers, rather than replace them. Likewise, other approaches complement this vision from the consumer’s point of view in such a way that they can have access to products that are as personalized as possible or adapted to their possibilities. Thus, concepts such as personalized food or tailor-made clothing could be virtually applied to any consumer product.

The sustainability in the development of the industry needs to reconcile the economic and environmental progress objectives. To achieve such common environmental objectives, it is necessary to incorporate new technologies and integrate existing ones by rethinking the manufacturing processes by introducing environmental impacts in their design and operation. Industry must be a leading example in the green transition.

Industry resilience means developing a greater degree of robustness in its production, preparing it against disruptions and ensuring that it can respond in times of crisis such as the COVID-19 pandemic. The current approach to globalized production has shown great fragility during the pandemic that devastates us. Supply chains must also be sufficiently resilient, with adaptable and flexible production capacity, especially in those aspects of products that satisfy basic human needs, such as healthcare or security.

Just as the fourth needed digital enablers, this new revolution needs technological aspects to make it happen. From a practical point of view, we can say that the enablers we reviewed a while ago are fully up-ot-date for Industry 5.0. We could include some additional ones such as quantum computing or block-chain, incipient ones 4 or 5 years ago. If the enablers are similar, why are we talking about a new revolution? It is a matter of priorities. If the fourth spoke abou hyper-connection of processes to the digital world through cyber-physical systems or the IoT, in the fifth, a cooperation between human and digital technology is sought, either in the form of collaborative industrial robots, social robots or artificial intelligence systems that complement or assist in any task related to production, from installing a door in a car to deciding how to organize the next work shift to meet the productivity goal of the manufacturing plant.

IoT technology to improve the efficiency of industrial companies

IoT technology to improve the efficiency of industrial companies

With the promise of 75 billion devices connected to the Internet around the world in 2025, the ‘Internet of Things’ (IoT) opens the door to a future of opportunities for companies to optimize their processes, whether in the form of manufacturing their products, supervising their quality or monitoring the critical machines in the factories: ovens, manufacturing lines or refrigerated warehouses.

In our daily experience as consumers, we can find a multitude of technological offers in IoT devices that we integrate into our lives in a fast and, sometimes, impulsive manner, either because of fashions or real benefits. However, the incorporation of these technologies in companies is not done in such an impulsive way, since it involves a careful study of feasibility and profitability, often complex to demonstrate, as usually happens with new technologies.

In addition, IoT possesses  a significant flexibility to integrate itself into the IT infrastructures of the factories. The ‘i’ of IoT means “internet”, which seems to be automatically associated with a direct connection to the Internet of “things” in the factories, and this generates panic because of possible cybersecurity threats for almost any company. To fight against these barriers, information and training are key aspects.

Within this framework, the IOTEC Spain-Portugal cross-border cooperation project is being developed. This initiative aims to create a collaborative network of different actors (researchers, public bodies, ICT solutions providers and industrial companies) of both countries to facilitate the IoT integration in companies. Participants in IOTEC have analyzed different industrial and ICT companies to look for gaps and strengths and to be able to relate supply and demand of IoT. From CARTIF, we coordinate the activities around the industrial companies in order to know their IoT needs through a detailed analysis of their organizational and productive processes that include management, product design, manufacturing process and logistics.

This analysis included a series of technological audits to different agroindustrial companies, analyzing the potential of application of IoT in different parts of its productive process. 40 different organizational parameters were evaluated according to the methodology defined within the IOTEC project. For example, in the section on manufacturing processes, four aspects of great relevance were analyzed meticulously:

  • The type of process or productive transformation, which is fundamentally defined by aspects such as the raw materials used or the manufacturing steps.
  • The traceability requirements of raw materials, intermediate products and final products. This traceability has special relevance in agrifood companies.
  • The control of the production process that is triggered by different mechanisms according to the company: production orders, on demand, availability of raw materials (e.g. vintage).
  • The need to capture data in the plant as the first phase of complete digitalization of a productive process.

Once all the parameters were analyzed, it was carried out an exhaustive classification of different IoT technologies that could be applied in the industry and have a direct impact on the improvement of efficiency. Next, you can see these technologies:

All identified technologies were prioritized by those attending the “Forum of business opportunities through IoT and Blockchain” that took place on November 14, 2018 in Valladolid. The attendees to the event had the opportunity to reflect and vote on this set of technologies to assess their need and the importance of its dissemination by the IOTEC project. Once these priorities are established, it is now necessary to make them known so that IoT solution providers can adapt their offers to real needs.

Likewise, work is being carried out on dissemination and training activities to bring IoT technologies closer and concrete examples of their application to the set of industrial companies in the regions of Castilla y León and the Centre of Portugal participating in the IOTEC network. Any company supplying or demanding IoT technologies can participate in the project forum and benefit directly through collaboration and training opportunities in this exciting set of technological solutions such as the IoT.

Augmented reality (AR) will transform the way you work

Augmented reality (AR) will transform the way you work

The Augmented Reality (AR) after some fairly lukewarm beginnings is being seen as a technology with a promising future. Much of this change of image comes from the Pokémon Go phenomenon that about two years ago showed the augmented reality to the general public in a natural way through the characters of the famous video game. This bombshell has served for many programmers that have realized the many possibilities offered by this technology lunging to develop simple applications like in this game, that allow you to use the picture taken with the camera phone and / or GPS position to incorporate 2D and 3D scenes and models to the physical world through mobile screen.

This has meant that we can now find numerous animations using augmented reality in commercial catalogs, advertising panels, tourist applications or educational games for children, among other applications.

Large companies such as Google, Apple, Microsoft or Facebook do not want to miss the boat and are taking positions to make the most of the great possibilities provided by the use of augmented reality. At the end of 2017 all of them have been showing platforms and software tools for incorporate augmented reality to their devices.

  • Google: ARCore is the Google platform that allows you to create augmented reality experiences. In the Google I / O held in May, new applications have been presented, especially for collaborative environments. ARCore is currently available for devices with the latest versions of Android.
  • Apple: ARKit, included in devices with the iOS11 operating system, allows developers to easily create augmented reality adventures that integrate virtual objects in the real world by combining data from cameras and motion sensor information.
  • Microsoft: Windows Mixed Reality development kit is a mixed reality platform that allows you to create virtual and mixed reality presenting virtual holograms together with real elements. It is fundamentally developed for the Microsoft Hololens smart glasses.
  • Facebook has launched AR Studio to create augmented reality effects on the captured images and that people can place 3D objects in their environment and interact with them in real time. The last thing presented is the AR Target Tracking that lets you start the experiences of AR pointing to an image, creating persistent experiences.

Beyond games and entertainment, a very interesting future for AR from the point of view of CARTIF as a research center is the development of applications for professionals in their work environment. Access to information anywhere and on-the-go assistance can make a big difference in speed and efficiency when performing certain tasks. All these tools are intended to reach users through the devices they already have: Smartphones, Tablets or PC. The incorporation of this technology to the work environment (industry, health, logistics…) often comes up against the requirement that workers have their hands free to carry out their work, which they cannot do with the aforementioned devices. In this sense, the Smart Glasses are presented as the most suitable device for this type of environment although after the disappointment of Google glasses launched in 2013, the supply of physical devices of this type on which to develop the applications is scarce.

Despite this, according to a study by Forrester Research, it is estimated that 14.4 million American workers will wear smart glasses to develop their work in the year 2025. CARTIF bet that the incorporation of these devices to industrial processes occurs gradually and workers become accustomed to use these devices as a working tool. Through the use of smart glasses, employees can access detailed instructions and content about the task in question without interrupting their work.

In the industrial environment there are many processes that can provide information in the form of augmented reality quickly and non-invasively. CARTIF, within the HABITAT-RA project, is working to bring this technology to SMEs, using augmented reality for three different aspects:

  • Monitoring: visualization of information about the state of a machine or process.
  • Industrial Maintenance: Obtain information and alerts about the periodic tasks of preventive maintenance in machines.
  • Occupational Risks Prevention: Obtain information and alerts about risk areas and safety perimeters in industrial environments.

In MARCA project, integrated in the water treatment and distribution sector, CARTIF has worked on the development of tools that allow the access of a maintenance operator to advanced support resources based on AR, and advanced intermodal communication using smart glasses.

Finally, in the PUMAN project, an Augmented Reality interface is developed for manual assembly positions in the industry through the guidance and presentation of information on assembly steps in an immersive way. It also informs about the safety risks of the operator.

Although it is still in an incipient phase, the incorporation of augmented reality in the performance of many tasks in the industrial environment can make a big difference in speed and efficiency. There are many factors to improve: the technology is still not mature enough, the high cost of producing augmented reality content or technical limitations of the devices to provide fully immersive experiences. In any case, this technology is in continuous growth. The large companies are betting on it little by little and users are becoming used to having content in the form of AR. The future is to have a device that combines a high optical capacity with communication technologies and the characteristics of a wearable, and whose price allows a massive distribution.

Reduction of costs and emissions in factories: real cases

Reduction of costs and emissions in factories: real cases

Industry is one of the sectors with a highest energy demand, being the fossil fuels the main energy source used in the most of the industrial processes. The utilization of this type of fuels in the manufacture process of the industries generates a waste heat that is not usually used, hence these processes are considered as inefficient. Nevertheless, this waste heat can be recovered (and in many cases reincorporated into the same process) by using new strategies and equipment. Therefore, the optimization of the industrial processes and the implementation of renewable energies in them can contribute to reduce the harmful impacts of the energy systems to the environment, while reducing energy consumption.

In addition, it has to mention that the energy recovery contributes to the reduction of production costs of the industries and consequently these gain in competitiveness. However, energy recovering is not easy since it requires of high performance technology and best practices of operation. Furthermore, many factories have complex and autonomous processes that are unlinked to each other or integrated into their environment. On the other hand, each product and manufacture process are specific to each industry so that it is difficult to find a global solution that encompasses energy reduction, renewables integration and energy recovery through a more efficient use of resources, cleaner manufacturing technologies or the recovery of resources.

Traditionally, factors that were taken into account in manufacturing processes were economic, management, production, etc. However, this situation has changed in recent years. Energy efficiency and sustainable management are fundamental aspects that many companies have incorporated in their processes. Aware of that reality, CARTIF is accompanying the companies to incorporate in them the “Factories of Future” concept. An example of work done is the REEMAIN project.

CARTIF moves toward zero carbon manufacturing and Energy Efficiency 2.0 through the intelligent employment of renewable energy technologies and resource saving strategies that consider energy purchase, generation, conversion, distribution, utilization, control, storage, re-use in a holistic and integrated way.

From the REEMAIN project experience, we have prepared a brief brochure, in which we have highlighted 13 efficiency measures implemented and tested in three factories, one from agrofood sector, another from textile and one more from iron foundry. These measures were classified into renewable energy integration, energy recovery, recycling and ecological materials use and production, process and product optimization.

Each measure is presented in a short and visual way and is composed of title, summary, savings achieved and key factors for a success implementation. Last input is a recommendation from our side to encourage the industries to replicate the measures already applied in the manufacture process of the democases in order to achieve similar results that in REEMAIN project.

Finally, under the section “Extrapolation to other factories” the replication potential of the measures has been quantified taking into account the next four main factors:

  • Process of implementation: This item is associated to the investment required for the implementation of the efficient measures, corresponding a high score with a low investment requirement.
  • Process criticality: This item has in consideration the increase in the complexity of the manufacture process as well as a reduction of the reliability due to the installation of new equipment in the industries. An efficiency measure with high score indicates few or null operation changes, e.g., being easily by-passing in case of breakdown or during the maintenance works.
  • Expected savings: This item is related to the savings quantification based on different factors
  • Investment return: This item considers the cost savings and feasibility of the installation in economic terms.

Brochure ends with a visual summary of the total savings achieved in the three factories that were part of the project.

Brochure is online and available for download free here.

New challenges on smart manufacturing industry

New challenges on smart manufacturing industry

Big Data as one of the so called “digital enablers” of Industry 4.0 sits at the core of promising technologies to contribute to the revolution at factories where vast amounts of data (whether they are big or small) hides enormous amount of knowledge and potential improvements for the manufacturing processes.

The Strategic Research and Innovation Agenda (SRIA) of Big Data Value Association (BDVA) defines the overall goals, main technical and non-technical priorities, and a research and innovation roadmap for the European Public Private Partnership (PPP) on big data. Within the current expectations of the future Data Market in Europe (around 60 B€), Manufacturing was at the first place in 2016 (12.8 B€) and in the 2020 projections (17.3 B€), revealing a leading role played by this sector in the overall Data Economy.

With the aim to find an agreed synthesis, the BDVA adopted the “Smart Manufacturing Industry” concept definition (SMI), including the whole value chain gravitating around goods production, secondly identified three main Grand Scenarios aiming at representing all the different features of a SMI in Europe: Smart Factory, Smart Supply Chain and Smart Product Lifecycle.

Given the relevance of both Data Market and Manufacturing industry in Europe and in accordance with European initiative of Digitation of Industry, CARTIF, together with rest of experts from BDVA association engaged in a collective effort to define a position paper that proposes future research challenges for the manufacturing industry in the context of Big Data.

To contextualize these research challenges, the BDVA association has defined five technical areas for research and innovation within the BDVA community:

  • Data Management and lifecycle motivated by the data explosion, where traditional means for data storage and data management are no longer able to cope with the size and speed of data delivered.
  • Data Processing Architectures originated by fast development and adoption of Internet of Things (IoT) and the need to process immense amounts of sensor data streams.
  • Data Analytics that aims to progress technologies and develop capabilities to turn Big Data into value, but also to make those approaches accessible to wider public.
  • Data Protection addressing the need to ensure the correct use of the information whilst guarantying user privacy. It includes advanced data protection, privacy and anonymization technologies.
  • Data Visualisation and User Interaction addressing the need for advanced means of visualization and user interaction capable to handle continuously increasing complexity and size of data and support the user exploring and understanding Big Data effectively.

During a series of workshops activities, started from the 2016 EBDVF Valencia Summit till the 2017 EBDVF Versailles Summit, BDVA experts distilled a set of research challenges for the three grand scenarios of smart manufacturing. These research challenges where mapped in the five technical priority areas of the big data reference model previously introduced.

To exemplify the outcomes of this mapping, the following figure gathers the headings of the set of challenges identified and discussed by the BDVA members into the Smart Factory Scenario. The interested readers are encouraged to analyze the full set of challenges in the SMI white paper.

Challenges set initially in this first version of SMI position paper set the tone for the upcoming research needs in different Big Data areas related with manufacturing. In the Smart Factory scenario the focus is on integration of multiples sources of data coming not only from the shop floor but also from the offices, traditionally separated in Industry 3.0. Interoperability of existing information systems and the challenge of integrating disruptive IoT technologies are major trials in the area of data management. Closer to the needs of a Smart Factory, the analytics challenges are focused on prescriptive analytics as tools for an optimal decision making process at the manufacturing operations management site including the optimization trough the evolved concept of digital twin.