Dalith Steiger-Gablinger, Co-Founder SwissCognitive – “AI Takes Center Stage at Davos 2025: A SwissCognitive Perspective”

As the snow-capped peaks of Davos played host to the World Economic Forum 2025, the air was thick with excitement and a palpable sense of urgency. This year’s theme, “Collaboration for the Intelligent Age,” set the stage for intense discussions on artificial intelligence (AI) and its potential to reshape our world. As co-founders of SwissCognitive, Andy Fitze and I, Dalith Steiger, had the privilege of being flies on the wall at various public side events, soaking in the insights and debates that unfolded.

The buzz around AI was impossible to ignore, with sessions ranging from “Harnessing AI for Social Innovation” to “The Pulse of AI Innovation”. Clearly, the technology has moved beyond mere hype and into the realm of transformative force. As James Ong, one of the panellists, aptly put it, “We need to rethink the philosophy and the relationship between AI and human beings.” AI is not just a tool; it’s a paradigm shift that will redefine how we work, live, and interact with the world around us.”

“We need to rethink the philosophy and the relationship between AI and human beings.” James Ong, Founder and Director of Artificial Intelligence International Institute [AIII]

One of the most striking aspects of the discussions was the emphasis on collaboration. Gone are the days of siloed AI development. The consensus at Davos was clear: to harness the full potential of AI and ensure its benefits are widely distributed, we need unprecedented levels of cooperation between governments, businesses, and civil society.

Another discussion that deeply resonates with our vision at SwissCognitive is the AI discussion in avoiding the pitfalls of the digital divide, emphasising the need for AI to “lift all boats” rather than exacerbate existing inequalities. We strongly advocated for inclusive AI development.

The ethical implications of AI were another hot topic. The sentiment that we are not just building algorithms; we are shaping the future of humanity was echoed across multiple panels, with discussions ranging from AI’s impact on privacy to its potential to either mitigate or exacerbate climate change.

As we navigated the bustling streets of Davos, Andy and I found ourselves in impromptu discussions with fellow attendees. One of the enlightening discussions was while waiting for the Meta hot chocolate or queuing for the entrance of the Dome. One thing that was present through all our exchanges. People engaged openly, with respect and humour.

The energy was infectious, with everyone from startup founders to policymakers eager to share their perspectives on AI’s future. One conversation that stuck with us was with a young entrepreneur who’s using AI to tackle food waste in developing countries. It was a powerful reminder of AI’s potential to address some of our most pressing global challenges and SDGs.

The governance of AI emerged as a critical theme throughout the forum. With the rapid pace of AI development, there’s a growing recognition that our regulatory frameworks need to evolve just as quickly. The call for adaptive, agile governance structures was loud and clear. We shouldn’t govern 21st-century technology with 20th-century laws!

“We shouldn’t govern 21st-century technology with 20th-century laws!” during a Chatham rules debate

Perhaps the most stimulating discussions, however, centred around the potential of AI to complement human capabilities rather than replace them. AI should be seen as a co-pilot, not an autopilot. As advocates of collaboration between humans and AI, Andy and I were heartened to hear leaders from different sectors emphasise the importance of involving humans in development.

“AI should be seen as a co-pilot, not an autopilot.” during a Chatham rules debate

The Open Source Revolution: A Game-Changer in the Global AI Race

Another topic that consistently emerged in our conversations was the growing importance of open source in AI development. This trend is not just reshaping the technological landscape; it’s also challenging the traditional narrative of national AI supremacy.

The United States’ commitment to investing a staggering $500 billion in AI over the next three years is undoubtedly headline-grabbing. However, as Yann LeCun, VP & Chief AI Scientist at Meta, astutely pointed out during several discussions in Davos, the real story might be the rise of open-source models rather than any single nation’s dominance.

LeCun’s perspective is particularly illuminating: “To people who see the performance of DeepSeek and think: ‘China is surpassing the US in AI.’ You are reading this wrong. The correct reading is: ‘Open source models are surpassing proprietary ones.'”

“Open source LLM models are surpassing proprietary ones.” Yann LeCun, VP & Chief AI Scientist at Meta

This shift towards open source is democratising AI development on a global scale. LeCun explained that “DeepSeek has profited from open research and open source (e.g. PyTorch and Llama from Meta). They came up with new ideas and built them on top of other people’s work. Because their work is published and open source, everyone can profit from it. That is the power of open research and open source.”

Indeed, the open-source movement in AI is gaining momentum rapidly. Models like Llama 2, Mistral, and DeepSeek are not just matching but, in some cases, surpassing the capabilities of proprietary giants like GPT-4 and Google Gemini. This trend is reshaping the AI ecosystem, offering adaptability, cost-efficiency, and privacy compliance that many enterprises find increasingly attractive.

The implications of this shift are profound. While national investments like the U.S.’s $500 billion commitment are crucial, the collaborative nature of open-source development means that innovations can come from anywhere. This global pool of talent and ideas could potentially accelerate AI development far beyond what any single nation or company could achieve alone.

Moreover, the open source movement aligns with the growing calls for AI transparency and accountability. One tech executive at Davos noted, “We’re not just building algorithms; we’re shaping the future of humanity.” Open source development allows for greater scrutiny and collective problem-solving, potentially leading to safer and more ethical AI systems.

“We’re not just building algorithms; we’re shaping the future of humanity.” CEO during a Panel in Davos

As we reflect on the discussions at Davos, it’s clear that the future of AI is not just about who can invest the most money. It’s about fostering a global ecosystem of innovation, collaboration, and shared progress. The rise of open source in AI is not just a technological trend; it’s a paradigm shift that could redefine how we approach some of the world’s most pressing challenges.

In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets but those who can best harness the collective intelligence of the global AI community. As we move forward, it will be fascinating to see how this open-source revolution continues to shape the future of AI and, by extension, our world.

“In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets, but those who can best harness the collective intelligence of the global AI community.” Andy Fitze, Co-Founder SwissCognitive

As the forum drew to a close, we left Davos with a sense of cautious optimism. The challenges ahead are significant, but so too is the collective will to address them. The conversations made it clear that we are at a pivotal moment in the development of AI, and the decisions we make now will shape its trajectory for years to come. This future belongs to the young generations. We, the older generation, must be aware that every decision we make won’t affect us, as it will affect the younger generations! This responsibility is imperative!

As we return to our work at SwissCognitive, we’re more energised than ever to continue fostering dialogue and collaboration in AI. The insights gained at Davos will undoubtedly inform our efforts to build a future where AI truly lifts all boats, creating a rising tide of innovation and prosperity for all.

“We are the change we wanna see”, Yip Thy Diep Ta, Founder & CEO @ J3D.AI, House of Collaboration

In reflecting on our experience, Andy remarked, “The technical possibilities of AI are astounding, but it’s the human ingenuity in applying these technologies that will truly change the world.” I couldn’t agree more, adding, “AI has the power to amplify our human potential, but only if we approach its development with empathy, wisdom, and a commitment to inclusivity.“

Der Beitrag AI Takes Center Stage at Davos 2025: A SwissCognitive Perspective erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: ucsf.edu – “4 Ways Artificial Intelligence (AI) is Poised to Transform Medicine”

AI can compare thousands of images to uncover dangerous patterns, create ultra-high resolution scans from low-res images and see what the human eye misses.

The radiologist was dead.

Or at least that’s what artificial intelligence (AI) experts prophesized in 2016 when they said AI would outperform radiologists within the decade.

Today, AI isn’t replacing imaging specialists, but its use is leading health care providers to reimagine the field. That’s why UC San Francisco was among the first U.S. universities to combine AI and machine learning with medical imaging in research and education by opening its Center for Intelligent Imaging.

Take a look at how UCSF researchers are pioneering human-centered AI solutions to some of medicine’s biggest challenges.

Spot illnesses earlier

Tens of thousands of Americans suffer pneumothoraces, a type of collapsed lung, annually. The condition is caused by trauma or lung disease – and serious cases can be deadly if diagnosed late or left untreated.

The problem:

This type of collapsed lung is difficult to identify: The illness can mimic others both in symptoms and in x-rays, in which only subtle clues may indicate its presence. Meanwhile, radiologists must interpret hundreds of images daily, and some hospitals do not have around-the-clock radiologists.

The solution:

UCSF researchers created the first AI bedside program to help flag potential cases to radiologists. In 2019, the tool was the first AI innovation of its kind to be licensed by the U.S. Food and Drug Administration. Today, it’s used in thousands of GE Healthcare machines around the world.

How did they do it?

Researchers from the Department of Radiology and Biomedical Imaging created a database of thousands of anonymous chest X-rays. Some of these images showed cases of collapsed lungs and others not.[…]

Read more: www.ucsf.edu

Der Beitrag 4 Ways Artificial Intelligence (AI) is Poised to Transform Medicine erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: informationweek.com – “AI and the War Against Plastic Waste”

Plastic pollution is easy to visualize given that many rivers are choked with such waste and the oceans are littered with it. The Great Pacific Garbage Patch, a massive collection of plastic and other debris, is an infamous result of plastics proliferation. Even if you don’t live near a body of water to see the problem firsthand, you’re unlikely to walk far without seeing some piece of plastic crushed underfoot. But untangling this problem is anything but easy.  

Enter artificial intelligence, which is being applied to many complex problems that include plastics pollution. InformationWeek spoke to research scientists and startup founders about why plastics waste is such a complicated challenge and how they use AI in their work.

The Plastics Problem

Plastic is ubiquitous today as food packaging, clothing, medical devices, cars, and so much more rely on this material. “Since 1950, nearly 10 billion metric tons of plastic has been produced, and over half of that was just in the last 20 years. So, it’s been this extremely prolific growth in production and use. It’s partially due to just the absolute versatility of plastic,” Chase Brewster, project scientist at Benioff Ocean Science Laboratory, a center for marine conservation at the University of California, Santa Barbara, says.

Plastic isn’t biodegradable and recycling is imperfect. As more plastic is produced and more of it is wasted, much of that waste ends up back in the environment, polluting land and water as it breaks down into microplastics and nanoplastics.

Even when plastic products end up at waste management facilities, processing them is not simple. “A lot of people think of plastic as just plastic,” Bradley Sutliff, a former National Institute of Standards and Technology (NIST) researcher, says.[…]

Read more: www.informationweek.com

Der Beitrag AI and the War Against Plastic Waste erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Vishal Kumar Sharma – “Analysing the Importance of Artificial Intelligence and Robotics in Agriculture”

Introduction

As the foundation of human civilization, agriculture is undergoing a revolution right now. The agriculture sector faces hitherto unheard-of challenges given the rising world population and growing effects of climate change. Though throughout has proven successful, conventional agricultural methods are failing to meet the demands of modern society. Two innovative technologies poised to transform our farming, monitoring, and collecting of crops are artificial intelligence (AI) and robotics. The article investigates the reasons behind the necessity of artificial intelligence (AI) and robotics into agriculture rather than just a passing trend.

The challenge is supplying food for a population growing

By year 2050, the world’s population is expected to reach 10 billion. Feeding this many people calls for a 70% increase in food output, claims the Food and Agriculture Organization (FAO). Still, the resources needed for agriculture land, water, labor are few and in many cases declining. Conventional methods usually damage the environment and demand a lot of human effort. Thus, it is quite necessary to improve farming’s efficiency, sustainability, and output.

The Significance of Artificial Intelligence (AI) in Agriculture

In agriculture, artificial intelligence is the use of data-based, more intelligent decisions making. Large amounts of data in real-time analysis made possible by AI-driven systems gives farmers insightful information that may be utilized to monitor soil condition and project crop harvests. Using satellite images and weather data, artificial intelligence systems can predict ideal planting times, spot disease outbreaks, and suggest effective pest control tactics. Such a great degree of accuracy can lead to notable increases in waste reduction, crop output, and the limitation of the usage of harmful pesticides.

Furthermore, artificial intelligence powered instruments have the capacity to improve resource use efficiency. Precision agriculture driven by artificial intelligence helps farmers to precisely apply pesticides, fertilizers, and water in ideal amounts and targeted areas. This method solves the entwined problems of sustainability and financial viability by lowering costs and mitigating the negative effects of agriculture.

The Significance of Robotics in Agriculture

By automating tasks requiring a lot of manual work, robotics improves artificial intelligence and hence increases farming’s productivity and scalability. Robots are used gradually for harvesting, weeding, and planting jobs. While robotic harvesters can pick fruits and vegetables with no damage, a task difficultly accomplished with human workers, autonomous tractors can plow fields with perfect accuracy. In fields without personnel or where agricultural chores demand great physical effort, this technique is very important.

Precision farming depends much on robotic tools. With sensors and cameras, unmanned aerial vehicles can monitor crop conditions from above and provide current data that lets farmers make wise decisions. Terrestrial robots can do complex tasks including weed removal, therefore reducing the need for herbicides. These technologies not only increase output but also reduce the boring character of manual farming, so appealing agriculture is to younger generations.

Sustainability and environmental impact

Using robotics and artificial intelligence in agriculture has a clear advantage since it helps farming methods to be more sustainable. Often requiring resources, traditional agricultural techniques can lead to soil degradation, water shortage, and a decline in biodiversity. Artificial intelligence (AI) driven analytics can give farmers direction on using sustainable practices such crop rotation, minimum soil disturbance, and irrigation optimization. By enabling precise farming techniques that cut waste and environmental effect, robotics can help to forward this goal.

Artificial intelligence might, for instance, look at soil moisture data and project irrigation needs, therefore ensuring the effective use of water. By selectively distributing fertilizers and pesticides, robots can help to lower the overall consumption and thereby minimize the flow into nearby ecosystems. By maintaining soil health and biodiversity, these technologies not only protect the surroundings but also raise agricultural output.

Advantages in the field of economics

In the context of agriculture, artificial intelligence (AI) and robotics provide clear financial benefits. For farmers, these technologies could help to lower costs, increase crop output, and raise the quality of agricultural goods. By means of predictive capabilities of artificial intelligence, farmers may efficiently reduce risks related to market volatility, pests, and weather conditions, so promoting more stable income. By automating chores requiring a lot of physical labor, robotics can significantly cut labor costs. In places where agricultural labor is either scarce or highly expensive, this is particularly helpful.

Moreover, the information generated by robotics and artificial intelligence can provide farmers with other revenue streams. For example, precise information on crop quality could be used to negotiate better prices or enter special markets. Furthermore, the application of these technologies can improve farming output, therefore raising its competitiveness and maintaining the livelihoods of farmers in both developed and underdeveloped countries.

Challenges and the road forward

Though robots and artificial intelligence (AI) have great potential in agriculture, several factors prevent their general application. Mostly because of high startup costs, lack of technology knowledge, and concerns about data privacy, smallholder farmers in underdeveloped areas have great difficulties. Governments, research labs, and businesses must cooperate to provide training, subsidies, and support systems that make this technology available to all farmers thereby overcoming these challenges.

Moreover, the development of robotics and artificial intelligence in agriculture has to be guided by ideas of durability and fairness. It is imperative to ensure that these technologies benefit smallholder farmers, the basis of world food supply, as well as big-scale commercial farms as they develop.

Conclusion

Rather than only a technical development, artificial intelligence and robots are essential tools for the direction of agriculture. These technologies offer a way to reach a more efficient, ecologically friendly, and flexible agricultural system within the worldwide fight to solve the problems of feeding an increasing population and preserving the environment. Including robotics and artificial intelligence (AI) into agricultural practices has moved from a luxury to a necessary need. These technologies will help us to ensure that agriculture meets the needs of the present generation without endangering the capacity of next generations to support themselves.

References:

1. Food and Agriculture Organization (FAO). (2017). The future of food and agriculture: Trends and challenges.
2. Aravind, K. R., Raja, P., & McKee, G. (2017). A review of agriculture robotics: Current trends and future directions. Computers and Electronics in Agriculture, 142, 379-394. doi:10.1016/j.compag.2017.09.030
3. Shamshiri, R. R., Kalantari, F., Ting, K. C., et al. (2018). Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. International Journal of Agricultural and Biological Engineering, 11(1), 1-22. doi:10.25165/j.ijabe.20181101.3790
4. Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming – A review. Agricultural Systems, 153, 69-80. doi:10.1016/j.agsy.2017.01.023
5. Balafoutis, A., Fountas, S., Cavalaris, C., et al. (2017). Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. Sustainability, 9(8), 1339. doi:10.3390/su9081339
6. Zhang, C., & Kovacs, J. M. (2012). The application of small unmanned aerial systems for precision agriculture: A review. Precision Agriculture, 13(6), 693-712. doi:10.1007/s11119-012-9274-5

About the Author:

Vishal Kumar Sharma, Senior Project Engineer of AI Research Centre, Woxsen University, India, with over 8 years of experience in team management, PCB design, programming, robotics manufacturing, and project management. He has contributed to multiple patents and is passionate about merging smart work with hard work to drive innovation in AI and robotics.

Der Beitrag Analysing the Importance of Artificial Intelligence (AI) and Robotics in Agriculture erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Artem Pochechuev, Head of Data and AI at Sigli – “Future Of AI-Powered Solutions For Disabilities: On The Verge Of Fantasy”

Today, while discussing Artificial Intelligence, we often talk about Generative AI tools, virtual assistants, or recommendations assistance. Such tools are already widely adopted and that’s why it is not surprising that they come to our mind in the first turn.

However, the potential of AI is much higher than that. This technology can be used in some mind-blowing solutions that seem to be absolutely fantastic.

Nevertheless, their introduction can be much closer than we may think.

In this article, we offer you to take a look at the most cutting-edge AI-powered projects that can greatly change the lives of people with disabilities (and not only).

Multimodal LLMs

Let’s start with something that sounds the most realistic – multimodal LLMs. Probably, all of you are already well-familiar with models that can work only with text inputs and provide text outputs.

Multimodal models are able to work with data in different formats. It means that they can deal with text, images, and sounds simultaneously and provide a relevant output. That is exactly what GPT-4o is expected to offer.

Of course, such models can be highly helpful for everyone. But their value will be significantly higher for people with different kinds of disabilities, including those with vision impairment, physiological disorders, and mental diseases.

Multimodal LMS can act as full-scale virtual assistants. Their functionality can offer much more possibilities in comparison to well-known solutions like Siri.

What can multimodal LLMs offer to people who can’t interact with their surroundings in a traditional way? We can say “practically everything” and from some point of view, we even won’t exaggerate.

For example, they will be able to explain everything that is written on the screen or describe what is shown in the picture. Their functionality will allow them to instantly translate and read aloud a text from the PDF file. They will help people to interact with their computers and smartphones. Based on the voice command made by users, they will open different menus, choose the necessary options, or move a pointer to the required line, while for a person with low vision or hand tremors, it can be very challenging to do this.

In the future, such models are expected to process video content as well. This will allow them to recognize films and describe their plots for users. Or they will be able to understand what sports game you will show to them and explain the rules.

Of course, these are just a couple of examples that demonstrate how multimodal LLMs can be used by people with disabilities. The range of their applications can be really wide.

AI-powered prosthetics

For people who were born without some parts of their bodies or who lost them under different circumstances, prostheses can become the best solution. These artificial body parts can restore some of the function and appearance of the lost anatomy. However, everything is not as seamless as we may think. The use of traditional prostheses can be associated with huge discomfort and various limitations, like limitations in dexterity or sensory feedback.

Nevertheless, such issues can be at least partially addressed by AI-powered prosthetics. Yes, AI arms today are not just something from a science fiction book. That’s a reality.

Artificial intelligence can significantly enhance the functionality, adaptability, and user experience of prostheses. In such solutions, ML is applied to teach bionic limbs how to understand movement patterns and how to make predictions based on the behaviours demonstrated previously. Thanks to this, limbs become more dexterous and more “natural”.

Such prostheses, both arms and legs, are non-invasive. But they have sensors that can measure electrical signals to identify the user’s intended movement.

Photo: University of Michigan

Of course, the use of AI-powered limbs is much more convenient in comparison to traditional prostheses. AI can automatically adjust artificial limbs for a better fit and can even make real-time changes based on user movements and activity levels.

The most advanced models can provide feedback on pressure and texture, which allows them to simulate the sense of touch for users.

Nevertheless, the cost of such devices is very high at the moment. This is one of the main factors that prevent them from being widely adopted today.

Bionic eye

Bionic limbs are a cutting-edge technology but what do you think about bionic eyes?

These experimental devices can restore functional vision for people who have partial or even total blindness.

The implantation of the earliest version of the bionic eye took place in 2012. The patient who got this artificial eye suffered from profound vision loss. After the surgery, he was able to see light. However, he couldn’t make distinctions within the environment. Since then, this first eye model has been greatly improved. Some other versions helped people start seeing abstract images. Nevertheless, none of the patients has regained vision.

One of the most widely discussed projects from this category is the Prima system by Pixium Vision. Their bionic vision solutions are being developed to help patients with profound vision loss and improve their independence and mobility.

Photo: https://www.pixium-vision.com

The core of their idea is the use of a 2-by-2-millimeter square implant that should be surgically placed under the retina. This implant should receive infrared data from camera-equipped glasses and further turn it into pulses of electricity which will replace signals generated by photoreceptor rods and cones.

Some early feasibility studies conducted in the US and European Union demonstrated that this system could be potentially effective and safe for people. Nevertheless, the project faced some financial difficulties which resulted in the delay in further research and development.

Rehabilitation robots and exoskeleton

Rehabilitation is a very important process for people with disabilities and patients after injuries. AI-powered robots can greatly help in the process of physical therapy through repetitive and controlled movements. They can offer personalized exercises and continuously monitor the progress to optimize recovery outcomes.

Such robots are often used in targeted therapy for patients with neurological or musculoskeletal impairments, such as stroke, spinal cord injury, or orthopedic injuries.

One of the most well-known robots of this kind is Lokomat which helps individuals relearn walking patterns. It ensures the most physiological movement which can be guaranteed by the individually adjustable patient interface.

Photo: https://www.hocoma.com/us/solutions/lokomat

Another type of solution used in rehabilitation is the exoskeleton. Exoskeletons can be defined as wearable devices that work in conjunction with the user’s movements to enhance or assist physical capabilities.

They can help individuals with mobility impairments to stand, walk, or perform other movements. Moreover, they can be used to enhance the physical abilities of healthy individuals, such as in industrial or military applications.

Over the last several years, we could observe the growing interest in designing innovative tools of this kind that incorporate AI. The obvious benefits of such exoskeletons are their capabilities to analyze data and adjust to the individual user’s needs in real-time.

One such groundbreaking AI-powered exoskeletons was developed by a group of researchers at North Carolina State University and the University of North Carolina at Chapel Hill. This wearable device can ensure great energy savings during human movement, which could lead to great improvements in athletic performance and significantly help individuals with mobility issues.

This exoskeleton is powered by data-driven and physics-informed reinforcement learning. With this approach, wearable robots can become intuitive and predict user’s movements.  This technology can also generate synergistic assistance across different activities, such as walking or stair-climbing. The controller can automatically adapt to various kinematic patterns. It means that the transition between activities can take place without any handcrafted control.

Photo: https://www.foxnews.com/tech/ai-driven-exoskeleton-lightens-your-load-elevates-performance

Though the actual prices of exoskeletons can vary from $50,000 to $120,000, Hao Su, Ph.D., associate professor at North Carolina State University and the University of North Carolina at Chapel Hill, noted that their efficient learning-in-simulation framework allows for rapid design and testing in computer simulations.

This can help to reduce the cost of research and development.

“Looking forward, we plan to make our robots truly affordable and accessible through innovative hardware design, namely low-ratio gears and cost-effective but high-torque electric motors. In about one year, we aim to make our exoskeletons for sale at a price range of $1,500 to $4,000, depending on specific features and manufacturing scale,” he explained.

Elderly care robots/ assistive robots for people with disabilities

While talking about robots, we can’t but mention robots that could fully or at least partially replace nurses, tutors, and caregivers.

In August 2023, the first commercial general-purpose humanoid robot Apollo by Apptronik was presented to the public. At the initial stages of its development, it was planned that it would be used in the manufacturing and warehousing industries. Nevertheless, later the range of its use cases was expanded. It can be also helpful in construction, retail, and elderly care. In the latest case, such robots can handle dozens of household chores and become good companions for people who spend a lot of time in isolation due to their disease or disabilities.

Photo: https://apptronik.com/apollo

However, this project is far not the only one in this group.

For example, there are a lot of reports from Japan revealing that the country is actively investing in the automation of elder care by employing various robots.

Though probably the majority of us start thinking about humanoid devices when asked about care robots, it’s far from being true. They can come in different sizes and shapes. Some of them are intended for physical care. In this case, we are talking about those ones that can help lift patients who can’t get on their own. There are robots that assist people in exercising and moving. Some others can track the physical activity of patients, detect falls, and help them use the toilet or take a bath.

There are also robots that are intended to communicate with elderly people, they can entertain them and even conduct cognitive training.

Robot guide dogs

Guide dogs are known to have been helping people with visual impairments for centuries. They can be great assistants and companions but the use of their services is associated with a row of challenges. The training of a guide dog usually requires significant time and expense. Moreover, let’s not forget about an average dog’s lifespan. This explains why a lot of countries face a shortage of trained guide dogs.

For example, according to the data published by the China Association for the Blind, currently, there are only around 400 trained dogs in the country, while the number of people who may need their help is over 17 million.

Dogs require particular care. They all have their personalities. This also can cause some difficulties for people.

But with the application of modern technologies, such issues can be successfully solved. Especially for those who do not feel like having a furry friend, as they can have a robot friend instead.

Robot guide dogs can efficiently provide real-time navigation services for people with visual disabilities and let them travel independently and safely. Such robots can identify road conditions, obstacles, and surrounding facilities. Moreover, they can work with voice prompts and provide vibration feedback, which makes interaction with them quite simple.

It is known that a group of Chinese researchers have been already conducting field tests of a six-legged guide dog that relies on cameras and sensors for navigation. This robot can successfully recognize traffic light signals, while in the case of real dogs, this “feature” is not available.

Photo: https://edition.cnn.com/2024/07/08/china/chinese-robot-guide-dog-intl-hnk/index.html

Of course, robot dogs require some maintenance but at least users do not need to feed them on a daily basis.

Brain-computer interface

Another technology that we should mention is a brain-computer interface. It can establish a direct communication pathway between the brain and an external device. It is possible thanks to its capability to decode the neural signals associated with attempted but unarticulated speech. In other words, it can translate neuronal information into commands capable of controlling external software or hardware systems.

In a very simplified way, we can explain its work as follows:

1. Collection of brain signals using electrodes or sensors;
2. Signal processing, filtering, and amplifying;
3. Extraction of relevant patterns or features within the signals;
4. Translation of these patterns into commands that can be understood by external devices.

Some BCIs are being developed for entertainment purposes. With their help, players can enjoy more immersive experiences. However, the majority of such projects have healthcare-related goals. For example, they can be used to assist in the in the recovery of motor functions.

In this context, it’s worth recollecting Neuralink. That’s definitely one of the most widely-known projects of this kind. This BCI is fully implantable. It’s invisible. And it can help users to seamlessly control their smartphones and computers. This technology can greatly help people with disabilities who are looking for ways to become more independent. Its efficiency in this aspect has been already proven in the first human trial.

Photo: https://neuralink.com/blog/prime-study-progress-update

In January 2024, Noland Arbaugh, a 30-year-old man paralyzed from the neck down, became the first patient who received the Neuralink device. Though there were some technical challenges during the trial, the general results look quite promising.

Thanks to the Neuralink device, the young man got practically full control of a computer. With the power of his mind, he can play games and browse the web at any moment. Moreover, according to Neuralink, Noland has managed to set the human record for cursor control with a brain-computer interface.

In an interview with journalists, Noland explained that the biggest advantage of using a BCI is the possibility of being independent.

“It’s just made me more independent, and that helps not only me but everyone around me. It makes me feel less helpless and like less of a burden. I love the fact that the people around me don’t have to wait for me so much. Outside of being completely healed, I believe what most quadriplegics want is independence,” he said.

Conclusion

Though today the majority of solutions mentioned in this article haven’t been widely adopted, that’s obvious that they have great potential given their incredible social value.

Moreover, we can say for sure that the real power of technologies, and AI in particular, hasn’t been even fully explored yet.

We still have a lot of things to learn and to do. But one thing is clear: today we are close to the future as never before. And we definitely shouldn’t stop in making life easier and better for everyone with the power of AI.

About the Author:

In his current position, Artem Pochechuev leads a team of talented engineers. Oversees the development and implementation of data-driven solutions for Sigli’s customers. He is passionate about using the latest technologies and techniques in data science to deliver innovative solutions that drive business value. Outside of work, Artem enjoys cooking, ice-skating, playing piano, and spending time with his family.

Der Beitrag Future Of AI-Powered Solutions For Disabilities: On The Verge Of Fantasy erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: cio.com – “Hyperscalers Place Big Bets On AI As Cloud Spending Rolls On”

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SwissCognitive Guest Blogger: Zachary Amos – “How AI Is Transforming Drone Delivery”

E-commerce has grown exponentially since the COVID-19 pandemic drove people out of stores and into their homes. Old habits die hard as consumers continue relying on their trusty devices to make purchases.

Although business has gone well for online retailers, meeting customer expectations with timely deliveries poses considerable challenges. Fortunately, artificial intelligence (AI) advancements have paved the way for leveraging drone delivery. However, some issues must be addressed before widespread adoption.

The Rise of Drone Delivery

The convenience of e-commerce has evolved shopping, whether for food, clothing, electronics or last-minute gifts. The consumer landscape has set its sights on drones for fast, reliable delivery to fulfill these orders.

Though still in its infancy, drone delivery has the potential to reduce distribution times, improve accuracy, and lower standard shipping costs for businesses and buyers. From 2019 to 2022, customers received over 660,000 drone delivery flights, with even more tests conducted to develop and improve this method.

However, despite drones’ efficiencies, the demand outweighs current capabilities. For instance, 10 years after announcing 30-minute drone deliveries for items under 5 pounds, Amazon only fulfilled 100 shipments using the technology in the United States.

If Amazon can overcome the regulatory and logistics hurdles, its promise of 30-minute deliveries will significantly appeal to consumers. The market value for same-day delivery was $5,795.64 million in 2021, while experts predicted the demand to rise by 12.65% by 2027. Drones can play a critical role in achieving customer satisfaction.

Drone Delivery: An AI Revolution

AI has rapidly infiltrated every industry, with more companies integrating the technology into their business models. The use of AI in drone delivery fleets is a game-changer for e-commerce and has already proven its effectiveness. Here are three ways AI-powered drones have changed how orders get distributed.

1. Improved Navigation

Conventional drones use GPS to navigate, which may be unreliable in some areas. However, AI-backed drones rely on real-time sensors and computer vision to take in their surroundings.

High-resolution cameras and light detection sense various landscapes, synthesizing the information in real time via an AI algorithm. Image and object recognition allows the drone to pinpoint potential obstacles and track different objects to avoid crashing.

LiDAR sensors also use ranging lasers to map the terrain and measure distances — drone features commonly found in the surveying sector.

2. Optimized Routes

AI can process large quantities of traffic information, such as routes, congestion, rerouting, weather conditions and buildings. Drones aren’t restricted to roadways, so the algorithm can plan the appropriate path for optimized delivery of goods with reduced flight duration.

The drone delivery fleet is also more eco-friendly than traditional methods, producing nearly 47 times fewer greenhouse gases and less energy.

3. Enhanced Security

AI’s ability to detect and avoid obstacles protects the drone and its packages. The system can also circumvent unauthorized areas during flight. As a result, in-flight safety is guaranteed and orders are delivered securely.

Companies can also use AI to detect maintenance issues with drones, allowing them to ensure their fleet is up to date and prevent malfunctions.

AI Drones in the Future

Although AI-powered drones are a feat in technological advancements, the method isn’t perfect — a reason widespread adoption has been slow. For instance, AI may have a 74-day shorter breach time frame, saving companies around $3 million more than those who don’t use it. However, drone privacy is still a hotly debated topic.

The Federal Aviation Administration (FAA) requires drones to publicize their locations, meaning anyone can view the destinations and track their flight routes. A privacy breach could lead to unsolicited advertisements and the release of personal information.

Drones are also vulnerable to state and city regulations. Phoenix would be an ideal location to set up drone delivery. However, much of the city has restricted airspace, with several small airports and an Air Force base. The FAA would hesitate to allow drones to fly without a pilot for safety reasons.

Additionally, although rural areas could greatly benefit from drone delivery fleets, densely populated suburban and metropolitan regions might pose more of a problem. AI-powered drones can navigate obstacles, but trees, swimming pools, animals, cars and people may challenge the most advanced software. Inclement weather may also be an issue, as not every area has dry, sunny weather conditions year-round.

AI-Powered Drone Delivery Has Potential

AI-backed drones can improve e-commerce and ensure consumer satisfaction in package delivery. However, industries must overcome regulatory and logistics issues before the world relies on them to do the job correctly.

About the Author:

Zachary Amos is the Features Editor at ReHack, where he writes about artificial intelligence, cybersecurity and other technology-related topics.

Der Beitrag How AI Is Transforming Drone Delivery erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: informationweek.com – “The 3 Things You Need to Modernize Ahead of AI Investment”

Repatriation. It’s a word that, just a few years ago, gave rise to amusement and dismissive smiles. Today, it’s a word that makes headlines and is the subject of a growing number of articles explaining why companies are, in fact, repatriating workloads.  

I’m not going to postulate as to why organizations decide to repatriate. But I will point out that only those who have invested in modernizing their applications and operations on-premises are really doing so.  

I’ve pointed out the link between SRE practices and cloud repatriation before. Our tenth annual State of Application Strategy research will again demonstrate that link remains strong. Organizations that have already or plan to repatriate workloads have two things in common: a mostly modern application portfolio and established SRE practices for operations. In other words, they’ve modernized apps and ops and therefore can repatriate.

What’s really interesting about repatriation is that organizations are not dumping the cloud. Far from it. They are maintaining a healthy presence in the cloud; they are simply being more deliberate about which applications live in their increasingly multi-cloud estate. Either way, the data is clear: Organizations are settling on hybrid as the norm.

Do you know what else is linked to SRE operations? Yes, operating hybrid applications.

The link is startlingly obvious. Of those running hybrid applications — that is, applications whose components are distributed across multiple cloud properties — 41% have already adopted SRE practices. A mere 7% operating hybrid applications have not done so. The rest are planning to, and soon. […]

Read more: www.informationweek.com

Der Beitrag The 3 Things You Need to Modernize Ahead of AI Investment erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger:  HennyGe Wichers, PhD – “You Can’t Fetch The Coffee If You’re Dead: An AI & Intelligent Machine Dilemma”

In his book Human Compatible: AI and the Problem of Control, Stuart Russell explains why programming an intelligent machine is tricky – even if its only job is to get the coffee.

You see, an intelligent machine understands that it can’t complete its objective if switched off for some reason. So, the goal of serving coffee has an implicit subgoal: avoid being switched off. And the surest way to avoid being switched off is, of course, to disable the off-switch. If a machine is intelligent, it can figure out how.

But at that point, the machine isn’t under human control anymore – which is a problem. The scenario isn’t unique to coffee robots either but applies to any intelligent system with a specific objective. Self-preservation is critical because, well, there’s not much you can do once you’re dead.

There are other issues, too. An intelligent machine might go about things differently than its human programmers. For example, an AI instructed to cure cancer might induce different kinds of tumours in every living person, allowing it to conduct a range of medical trials all at the same time. That would be the fastest way to find a solution – but it would also be wrong.

Think long enough about any single objective, and you’ll notice problems. It’s like the genie in a bottle granting three wishes. More often than not, the third wish is to undo the first two because unintended side effects happened when the wisher forgot to mention something they cared about. In Greek mythology, King Midas wished that whatever he touched turned into gold. That backfired when he discovered food and water weren’t excluded. He died of starvation.

Single Purpose

In all these examples, we optimise for a single objective and measure success only as achieving that goal. Current AI systems work like that, too. It hasn’t caused significant problems because, so far, we’ve only built ‘narrow AI’. That is, AI that does precisely one job. For example, a chess robot that follows the rules of chess to win a game it is told to play.

On the other hand, when instructed to ‘win a game of chess, following the rules of chess, ‘ an intelligent machine might already cause trouble trying to interfere with others playing the game. And forgetting to add ‘following the rules of chess’ might send it looking for that off-switch first.

These examples seem a little dramatic, and, in reality, the unintended consequences of AI are less easy to spot. That’s not the same as irrelevant. We’ve already seen operational AI systems recommend hiring men instead of women and deny black people probation. These problems are real and affect real people in the real world.

In this article, however, we want to focus on the intelligent machines of the future. The ones that don’t yet exist, but ChatGPT, Gemini, and Sora inspire us to think about. What objective would we give such a machine? And how would we stop it acting out?

Should we explicitly tell it not to touch the off-switch? And to only be good? In that case, who decides what ‘good’ is? And if the machine is more intelligent than us, surely it would find a way around any instructions. So we need better ideas.

Stuart Russel’s Three Principles

In Human Compatible, Russell suggests an alternative approach summarised in three principles. These principles are not rigid laws to hardcode into AI but a guide to researchers and developers building a future where AI serves and benefits humanity.

Let’s look at all three before taking each in turn:

1. The machine’s only objective is to maximise the realisation of human preferences.
2. The machine is initially uncertain about what those preferences are.
3. The ultimate source of information about human preferences is human behaviour.

Notice that preferences are central to every principle. Here, preference means you can order what you prefer, like in game theory. Say you like apples better than bananas and bananas more than clementines. Then you will also like apples more than clementines. Or perhaps you are indifferent between apples and bananas. In that case, you’ll choose either over a clementine.

Preferences can be over simple things, like fruit, or complex matters, like an entire life. In his three principles, Russell means the latter: if you could virtually experience two entirely different versions of your life, you know which one you prefer. Or that you don’t mind either way.

***

The first principle, then, means that the intelligent machine is purely altruistic: it does not attach any value to its own existence. It cares only about maximising the benefits it brings to humans. The system would still avoid getting damaged if its owner is unhappy about paying for repairs but may disable the off-switch to continue doing valuable things for people.

The second principle deals with that problem. It says that the machine initially doesn’t know if its owner would be okay with removing the off-switch. A machine that knows what’s best will single-mindedly pursue its objective, not caring about any collateral damage it causes. But a humble machine doesn’t assume and checks.

It looks to its owner and their behaviour to understand the best action. Over time, the machine gets better at predicting what you want and becomes more beneficial. That’s captured in the third and final principle.

Beyond You

There is an important point to note. The intelligent machine does not try to identify or adopt one ideal set of preferences but satisfies the preferences of each person. So, how should the machine trade off the desires of multiple humans? The simplest solution is to treat everyone equally, striving for the greatest happiness for the greatest numbers.

That idea is similar to how many Western economies operate: people live their individual lives and make decisions that are best for themselves, often within family or organisational settings. And, somehow, those decisions add up to a functioning system.

Economic theory says that’s because people make efficient choices based on full information. But for most decisions, full information is too much to handle. Just think of choosing something to watch on Netflix. If you listed everything you’ve not yet seen and ranked the list, you’d know the best choice. By then, however, the evening is long over.

Netflix’s algorithm makes suggestions to help cut through the weeds. When you sign up for the service, it makes no assumptions about you. Its algorithm observes and learns from your choices. The platform makes sure to have content for you – as well as for others with different tastes. And if you change what you like, the algorithm adapts. Come to think of it, Netflix follows Russell’s three principles quite well.

Now imagine that kind of assistance with everyday life. An intelligent machine that knows and understands you and shows options you otherwise might have missed. And by combining the information about you and everyone else, the machine can find an equilibrium better than the one we occupy today.

The ideas we need for an intelligent machine exist. To turn it into reality, AI researchers and developers should focus not just on STEM but also on philosophy, psychology, and social sciences.

About the Author:

HennyGe Wichers is a technology science writer and reporter. For her PhD, she researched misinformation in social networks. She now writes more broadly about artificial intelligence and its social impacts.

Der Beitrag You Can’t Fetch The Coffee If You’re Dead: An Intelligent Machine Dilemma erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Artem Pochechuev, Head of Data Science at Sigli – “Bridging the Gap: How AI Can Facilitate Social Inclusion Of People With Disabilities”

A recent study conducted by the UK national disability charity revealed that around 60%, which is almost two-thirds, of people with disabilities are chronically lonely. Even a bigger percentage of respondents (70%) admitted that they feel that social isolation has an impact on their mental health, which can also lead to an increase in mental health conditions in combination with the disabilities that they already have.

And here, we can observe a very important dissonance. On the one hand, a lot of people with disabilities can’t feel that they are a part of society due to the restrictions that they have to face every day. So, they do not have the possibility to communicate with other individuals a lot.

On the other hand, many of them can’t live fully independently. Due to their disorders, they can’t handle even routine tasks. As a result, they need to rely on the support of their family members, nurses, or tutors. Consequently, they are obliged to interact with others to deal even with the simplest everyday processes.

Amid all these issues, questions related to social isolation and lack of independence shouldn’t be ignored by organizations that work with people with disabilities.

Given all the new opportunities that emerging technologies like AI open, they can make a huge contribution to such projects. And it is great to see the growing interest of the world’s community and international institutions in the adoption of AI to help all groups of society.

According to the European Network of National Human Rights Institutions), “AI holds significant potential to positively impact the lives of persons with disabilities by addressing various challenges and providing innovative solutions. From speech-to-text applications to vision-enhancing tools, AI can break down barriers and provide new avenues for communication and interaction.”

In this article, we offer you to take a closer look at AI-powered projects and initiatives aimed at breaking social barriers for people with disorders of various types.

AI and communication

Speech-to-text and text-to-speech tools are widely applied to help people with hearing and speech impairments communicate with others. In one of our previously written articles, we’ve already described the power of Artificial Intelligence in enhancing the way people with such disorders interact with the world around them.

Thanks to virtual assistants enriched by such features, people can communicate with others in the traditional way. And this approach presupposes a real-time dialogue with practically no delays. As a result, they can solve a lot of tasks (like making calls to book a table at a restaurant, setting an appointment with a doctor, or ordering a delivery) without waiting for help from others. You may say that such tasks can be performed via sending a message. But let’s be honest. Quite often, a phone call is the fastest way to get what you want. And in this case, they can rely on AI-powered virtual assistants like Siri.

But this functionality is not the only one that can be ensured thanks to Artificial Intelligence. AI can fully change the way society can communicate with those who use sign language. With modern solutions, you do not need to know all the signs and their meaning to communicate with those who can’t express thoughts with the help of verbal means. AI algorithms can recognize signs and transform them into natural languages and vice versa.

The AI-powered era in marketing

And that’s cool that there are projects like Signapse AI, which helps businesses adapt their marketing strategies to the needs of everyone. What does it mean? The offered solution can translate written text into a Sign Language video which businesses can place on their websites, social media accounts, and blogs.

It will be sensible to note that all the information can be delivered to people with hearing disorders via written texts. Yes, it is possible. But such projects allow companies to make their communication with everyone vivid and engaging enough. Moreover, that’s a good way to demonstrate that you respect all your existing and potential and appreciate them regardless of any disabilities that they may have.

Autism and social skills

However, while discussing barriers in communication, we should mention not only speaking or hearing disabilities. In this context, it is also crucial to talk about people with autism spectrum disorder.

For individuals with autism, it can be extremely challenging to participate in various formats of social interactions. And AI-powered tools for social skill training can bring huge value. Such tools can simulate different role-playing real-life scenarios, analyse people’s behaviour in offered situations, and provide real-time feedback. It means that, in this case, AI is applied to create a supportive, controlled, and fully safe environment where users can practice and enhance their social skills.

One of the projects that are working on delivering such solutions is SocialMind. It is a member of the Microsoft for Startups Founders Hub. This platform relies on AI and NLP to improve the social skills of children with autism. Thanks to AI, the social skills training can be personalized for each child based on his/her specific needs and learning style.

But that’s not the only possible AI use case in this domain. AI can let people with autism communicate via alternative means. How is it possible? AI technology can recognize non-verbal or limited verbal means. Then language processing algorithms, predictive text, and voice recognition tools can transform them into natural language. As a result, individuals with autism get more freedom in expressing their thoughts. They can engage in various activities and take part in conversations.

AI and consumption of content of different formats

Books, movies, and art are among those things that, in this or that form, are present in our social life and affect it.

Let us mention a very simple example. When you move to a new country and try to integrate into a new community, sooner or later you may feel that you are a stranger. It can happen even if you perfectly know the local language and have already learned the names of local supermarkets. You may start feeling that you do not know the cultural context. For example, you do not know what songs were popular when people from your generation went to school and what cartoons they liked. As a result, you simply can’t understand the majority of memes and jokes.

But, of course, it is not a problem in comparison to what people with hearing or vision disorders experience when it comes to the cultural context.

However, thanks to AI, we can introduce alternative forms of consuming and producing different content. And it’s not only about social and cultural aspects. Such tools can be also of great use for educational and professional purposes.

Live captioning and screen readers are expected to greatly change the game for people with disabilities. Real-time captioning solutions make the participation of individuals with hearing disorders in various online events possible.  At the same time, image and text readers can be used by those with visual impairments and people with dyslexia.

AI and accessibility of public spaces

It’s amazing to observe that today, public spaces are gradually becoming more accessible thanks to AI. Smart city solutions can rely on systems powered by Artificial Intelligence for sharing real-time data on accessible transportation options (like wheelchair-accessible ramps or buses that can be easily used by people with limited mobility).

Architects and designers can benefit from AI-powered tools for creating so-called disability-friendly urban planning and buildings.

And already today there are apps that use the power of AI to provide accessibility information about various public spaces.

For people with visual disorders, the market can offer smart glasses and AI-powered apps that use smartphone cameras. Special cameras can be placed on a person’s eyeglass frames. They utilize optical character recognition technology. With it, they can transform digital or printed text into real-time auditive feedback. Some other solutions of this kind can also be powered by stereo sound sensors and GPS technology. They can recognize colours, read signs, and provide spoken directions.

Moreover, there are applications like Seeing AI by Microsoft that can safely navigate people with visual impairment. AI algorithms can identify objects and people caught by the device camera and then audibly describe what is happening around them.

While Seeing AI is a universal app that can be used in many situations, similar technologies can be more industry-specific. For example, cameras powered by computer vision can be installed in gyms and can notify people about any threats caused by irregular use of equipment. Such a solution can be of great use for a very wide audience. But it will have the highest importance for people with visual impairments.

AI and independent living

Let’s be honest, the modern world is built in such a way that even a lot of healthy people can stay at home, work from home, order deliveries, communicate with others only via chats, and still feel completely okay about it. Total digitalization (in which AI also takes an important position) makes it possible for everyone. However, even when all these opportunities are available, people still feel that they are a part of society. They can easily leave their homes if they want to do it and go wherever they want. They do not depend on others.

But we can’t say just the same about people with disabilities. Many of them can’t live fully independently due to many reasons which causes a lot of discomfort to them. Nevertheless, AI is here to address such issues.

For example, smart controllers used in smart home systems can greatly increase the safety of people with vision and cognitive disabilities. They can track whether all home appliances are turned off when they are not used, monitor possible water leaks, etc. Assistants with voice control can be used to manage a lot of tasks. Meanwhile, cameras with computer vision can recognize who is standing at the door and inform a person.

Special smart controllers can also be responsible for detecting various threats and dangerous situations related to people’s health. Already today, there are projects that offer to install sensors that will detect falls and the absence of movements during a particular period. Such solutions are highly relevant for families with elderly people living alone. If a dangerous pattern is identified, the system will send notifications to nurses or other authorized individuals who can take the required measures.

For people with limited mobility, there are quite a lot of voice-controlled devices and smart robotic products. But some solutions that are available today are ground-breaking. For example, what about walking simply by thinking about it? Thanks to electronic brain implants, it can be possible. The system is still not widely available and is at an experimental stage. Nevertheless, a 40-year-old Dutch man who was paralyzed after an accident got the possibility to walk again. The electronic implants wirelessly transmit his thoughts to his legs and feet via an implant on his spine.

Neurosurgeon Prof Jocelyne Bloch at Lausanne University, who carried out the surgery and inserted the implants, explained the project’s goal in the following way:

“The important thing for us is not just to have a scientific trial, but eventually to give more access to more people with spinal cord injuries who are used to hearing from doctors that they have to get used to the fact that they will never move again.”

And that’s exactly how we at Sigli (Cortlex) view the mission of introducing tech innovations – to make impossible things possible for everyone.

But even such cutting-edge projects are not at the highest level of what we can expect to see in this field in the near future. Research and experiments are going on.

Conclusion

Have we mentioned all the existing AI-powered projects aimed at facilitating everyday tasks for people with disabilities? Definitely no. This list could be practically endless.

Without any doubt, it is extremely exciting to explore the potential of AI in this aspect. And it is even more exciting to make our contribution to this huge common initiative – ensuring that our world is comfortable for everyone. If you need any technical assistance in the realization of such projects, we would be happy to hear from you.

About the Author:

In his current position, Artem Pochechuev leads a team of talented engineers. Oversees the development and implementation of data-driven solutions for Sigli’s customers. He is passionate about using the latest technologies and techniques in data science to deliver innovative solutions that drive business value. Outside of work, Artem enjoys cooking, ice-skating, playing piano, and spending time with his family.

Der Beitrag How AI Can Facilitate Social Inclusion Of People With Disabilities erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.