Have you subscribed to any company newsletters? If yes, you should have noticed how they address every person by their names and even emphasize the content as if they know you.
The secret is AI technology. With the use of AI, companies send personalized content to every prospect hence increasing conversions.
Many firms have embraced this technology while sending emails to prospects.
Email marketing is the best way to reach clients and candidates in real-time. It has also proved to be the best tool for converting prospects into long-term clients. All the company needs is to send regular emails with insights that try to solve client needs. In turn, candidates will seek favor and more solutions, which is how they become warm prospects or even long-term clients. Use email marketing to send industry-specific news, company updates, or just to check in with clients.
This regular communication with your consumer base will go a long way to converting sales.
Using AI Chatbots Services
It is part of the ancient past when representatives answered every customer’s queries.
Many companies have invested in AI chatbots that solve many customer problems in real-time.
The chatbots engage prospects immediately when they click the link to your website. Clients trust such sites when they get help on the go.
AI allows the chatbot to gather helpful information from different sources of data. That enables other brands and businesses to communicate with consumers on a personal basis. That is what Under Armour and IBM did when they collaborated. The record learns more about one’s different activities and suggests the best way to perform better. The Under Armour App provides users with advice about nutrition, health, and exercise.
If you invest in chatbot technology, you will save a lot as everything happens, even without your customer care representative. You can start your own drip campaign, marketing automation, and chat service to boost your customer service ROI. Search for quality services online to help you implement this technology.
Doing this will also reduce the number of customer care representatives, as the bots will do a more significant percentage of the customer care services.
Have you ever asked who decides on the ads you see when you open your browser?
There is a lot of work in the background to arrive at every ad you see on your social media platform when you open eCommerce apps like Amazon.
Many companies have significantly invested in AI technology to the extent of knowing your region, your search history, and likes and preferences.
From stats, customers who receive ads that match their interests are likely to purchase them, increasing the conversion rate.
AI has dramatically enhanced customer experience and an increasingly more significant customer base with little effort. AI technology is able to collect a wide range of user insights that can influence your marketing campaigns and messages. AI can save your company money by collecting this data for you about your customers.
This data will not only enhance the consumer experience through personalization, but it can help your company create data-driven solutions and tactics to grow your business.
The technology extracts and analyzes insights from an extensive database. It matches the data with the other leads hence derives a probable conversion rate for every lead. With the technology, you can first target prospects with a higher conversion rate before going for the others with less conversion.
Moreover, when you use the correct data and AI technology, you can easily predict customer experience hence adjust accordingly.
Image Recognition Technology
You will agree that you found your photo target or friend target to a particular image at some point.
Many platforms invest in image recognition technology to target the right audience, mainly when they use images similar to what the niche leaders post.
For instance, you can decide to make an image similar to your most significant competitor’s bit with minor adjustments. Clients will efficiently prospect for your products. They, too, might remain your prospects if they get what they need. However, please don’t use the technology to dupe customers to your company and fail to get what they want.
The technology has helped the firms curate the best content customized to every prospect which in turn generates higher leads and a more personalized experience for the consumer. It has also helped the companies attract many clients with minimum effort. AI is also fundamental customer care assistance as they support candidates to get what they need in real-time. Technology is essential for any business with the vision of remaining at the brim of operations.
In addition, AI serves a crucial role during the pandemic. It is used for proper screening and predicting the current and future patients, early detection and diagnosis of the infection, developing drugs and vaccines, and reducing healthcare workers’ workload.
Many facets of eCommerce are affected by AI today as it quickly detects trends and clusters in consumer behavior, purchase patterns, and other commonly occurring data. In fact, AI now makes it possible to detect millions of such purchases per day, generating a customized experience for a single user.
With the sales processes moving beyond time-consuming methods, consumers are now influenced by different media types. Using artificial intelligence integrated into CRM systems enables businesses to personalize solutions and communications that target the right consumers at the right time for the proper purpose.
AI-Powered Email Marketing
AI has been playing a significant role in email marketing for years. Email marketing generates steep revenues at $38 for every dollar spent.
Since most businesses have moved online, the competition for the market’s attention has become more cutthroat. However, intelligent strategies powered by AI solutions can level the playing field.
Those who could retain their brick-and-mortar stores start collecting customer email addresses using a POS (Point-of-Sale) system. Just make sure you do all your lead generation in keeping with privacy laws to avoid issues for your company. If you’re exclusively an eCommerce retailer, you can collect email addresses as visitors land or leave your site.
Modern POS systems and retail platforms can be linked to email marketing apps such as MailChimp. This way, you can create and manage a subscriber list, automate email campaigns, and generate detailed reporting.
Cashless Payment Solutions
A more straightforward way to go touchless amid the global crisis is to use cashless payment solutions. More and more consumers now use E-wallet payment platforms and apps.
A Mobile E-wallet helps you keep money and move funds to your bank account by scanning a QR code. It may be linked to a customer’s debit or credit account, depending on the business’s preference. To be vigilant, you can top up or fill just the cash you need on your E-wallet.
Any aspect of the transaction, including billing to receipts, is digital, regardless of customers’ devices. Cashless payment is also possible for microbusinesses in small communities through online payment apps.
Contactless Sales and Shipping
Contactless delivery is the new normal.
Drop-off delivery options are now a standard among logistics companies like DoorDash, Postmates, Instacart while eCommerce sites like Amazon, Shopify have long offered this feature.
We will see more companies comply with human touch preservation via artificial intelligence-based applications.
The rise of AI technology has led to work automation marking the new-age business revolution. The theme remains constant, from robots working in factories to automated hotel bookings and property technology – incorporating AI systems for business automation. The only difference is the AI applications employed.
Streamlining operations through AI solutions is a smart move for businesses to cope with the demands of a new normal economy. Artificial intelligence statistics from a recent survey show that more than nine in ten top businesses surveyed are already investing in AI technology.
Companies’ growing use of AI shows plenty of benefits, at the top of which is business productivity. 54 percent of business executives claim that AI adoption within their work led to an increase in productivity. Such effective use of AI also helps with better and more accurate decision-making within organizations.
Distributed Teams and Remote Operations
Remote working has been around even before the pandemic. However, the crisis pushed remote working and distributed it into the forefront in 2020. From government offices to private companies, everyone had to adjust and find ways to keep operations ongoing.
The reason for this is because the pandemic remains to be controlled.
Another reason is the dramatic decrease in revenues for most companies affected by the lockdowns.
A third reason is that distributed teams cost less than a full-on, on-site staff. As the economy begins to recover, more and more businesses discovered a remote work setup’s glories mention they will keep these newly-adopted work setup.
Video conferencing has thus become a norm – Zoom rose rapidly as a videoconferencing platform, outranking Skype, Google Meet, and other messaging apps because of its features that were quickly able to accommodate the exodus of professionals and students coming its way. Although it experienced security and technical issues with the sudden jump of its users, it bounced back real quick and made the app more secure, able to accommodate even large-scale webinars from around the world.
Many new ventures are emerging in the remote working sector. Startups Bluescape, Eloops, Figma, Slab, and Tandem have all provided
Visual collaboration platforms are also on the rise, enabling teams to interact, create and share content, monitor projects efficiently, conduct online employee training and run virtual team-building activities. Such examples include startups Bluescape, Slab, Figma, Eloops, and Tandem.
Micro-SaaS companies in the new normal economy are also increasing, most of which integrate Artificial Intelligence and machine learning solutions to improve modern businesses.
The growing use of AI isn’t just widespread in businesses. As the technology goes mainstream, consumers worldwide have become more receptive and accepting of it.
Businesses need to work on communicating how they’re using AI within their organizations – despite the growing acceptance of AI, many consumers remain wary of how businesses are using the technology. Only 54 percent of consumers claim they trust companies to use the data collected from AI in a way that’s beneficial to consumers.
To boost small businesses, owners must be open to AI adoption and integration – the increasingly widespread use of AI is boding well for SMEs (small to medium enterprises) because it is becoming more accessible and affordable in many ways.
If customers are willing to use AI-powered solutions for a better experience, then all the more the businesses should.
Keep up with consumer demands and maintain their edge amongst their competitors.
Artificial Intelligence (AI) is a technology that fuels machines with human intelligence – machines that have AI capabilities can automate manual tasks and learn on the go just like humans.
Such automation gets repetitive and time-consuming tasks under the AI-powered systems that learn with time and can eventually carry out critical tasks and make decisions on their own.
Such unique potential drove the transportation businesses to start investing into AI technology to improve revenue and stay ahead of their competitors.
Transportation industry has just begun to apply AI in critical tasks however the reliability and safety in transport are still under question. Major challenges in transport like safety, capacity issues, environmental pollution, reliability etc. provide a huge opportunity for AI innovation.
Transportation industry faces problems when a system functionality cannot form per predictable patterns which are affected by external elements like traffic, human errors or accidents.
A.I. uses data to predict decisions appropriately and it has been implemented in a variety of ways where some of examples include
public safety (e.g. tracking crime data in real time),
autonomous vehicles (e.g. self-driven vehicles),
pedestrian safety (e.g. tracking pedestrians/cyclists paths to minimize accidents),
traffic patterns (e.g. causes of delays, reduction of traffic congestion) and
corporate decision making (e.g. accurate prediction methods and forecasts).
Benefits of AI in transport:
The best fit of AI and transport somehow came naturally as adoption of these technologies can have a massive impact on the entire industry although the application of AI still varies across geographies.
Increased use of A.I. will ensure reduced labour costs while providing higher profits – fully automated fleets will be there to resolve an issue of long driving hours and breaks.
AI can also have a huge impact on safety and traffic accidents. Driving at night is a great issue and smart unmanned vehicles can significantly improve the problem. Auto-pilots or unmanned vehicles that can operate without a human can help the drivers to snooze without causing any traffic accidents.
Traffic management can also be more effective – AI methods enable us to forecast traffic by using traffic data and details about urban ongoing events as well as suggest alternative routes by automation.
Complex infrastructures and various elements within cooperation chains can be improved with the help of AI through e.g. optimal route schedule, minimal waiting time, traffic detection in real time for adjusting the routes etc.
Data analytics in logisticscan also help upgrade transportation planning and increase safety in general.
There are many more benefits to list yet AI is still growing and the benefits will too.
Drawbacks of AI in transport:
Although AI can bring a plethora of benefits to any industry, there are also some drawbacks to pay attention to like creating transparency in AI decision making or safety issues within autonomous vehicles.
One of drawbacks include job flow as it became a major issue for truck or taxi drivers and other industry members. Although social experts tried to explain that job skills can be shifted to other sectors, tensions remain.
AI implementation can also represent drawbacks as undeveloped countries will face massive challenges in utilizing such solutions as their infrastructure is not capable of providing maintenance.
Transport companies also face potential AI drawbacks as transportation costs contribute to the company revenue by up to 10%. All existing businesses will need to develop and implement AI technologies to remain competitive within their industry and the high cost of developing, repairing and maintaining the complex machines can be extremely high.
Ethic issues are also under revision – companies bringing AI to transportation will have to take the ethics of AI seriously if they want to win consumers’ trust.
AI technology still needs significant improvement as it’s still far from a human level of intelligence.
AI in Transportation
We can already find the examples of AI being used within transportation. As Artificial Intelligence evolves and becomes more mature, it is certain that the number of roles where AI plays a major role will increase.
Some of the examples where AI is common in transport are:
Autonomous vehicles are already a reality within transportation. They represent the first step into a new future of autonomous transportation although it seemed quite a futuristic idea in the past.
A.I. uses its processing, control and optimization capabilities to power these driverless vehicles. With autonomous vehicles, real-time data transmission and processing is crucial and any confusion within these processes can cause fatal outcome.
These types of projects are still in pilot versions while trying to make autonomous vehicles safe for passengers but as the technology evolves, autonomous vehicles will gain more reliability and become much more widespread.
The safety of passengers, pedestrians and drivers has always been a number one issue for the transportation industry.
The use case of AI was the autopilot system which is used in almost every commercial airplane today and it is a vital part of any air travel nowadays.
New York Times reported that only 7 minutes of an average Boeing flight is controlled by humans (takeoffs and landings) while the rest is being handled by an autopilot.
Public transportation will also be hugely affected by A.I. since there have been driverless buses recently transporting passengers with the help of sensors, cameras and GPS.
A.I. technology can do so much for us – it can reduce the human errors within traffic, monitor the safety regulations compliance, review vehicle maintenance reports and manage transportation in such manner to decrease effects of driving risks in urban areas.
Today, ‘there is an app for everything‘ – it includes AI powered real-time traffic updates through services like Google Maps or Waze.
These applications use location data collected from smartphones to be able to analyze traffic conditions within your local area and inform the users better about the traffic.
These apps may soon face competition in the form of autonomous vehicles as why would you need an app if the car itself already does the same work?
AI can be used to manage traffic systems due to its processing, control and optimization capabilities. In order to make the roads smarter, AI can be applied to traffic management to streamline the traffic. AI prediction ability to recognize the physical or environmental issues that may lead to heavy traffic or congestions is another great benefit.
Sensors and cameras implemented on the roads collect large amounts of data related to traffic details. Such data is analyzed by big data and AI systems to reveal traffic patterns.
The relevant insights assist commuters with details on traffic predictions, accidents or road blockages and provide suggestions on the shortest routes to their destinations.
The example is Siemens Mobility which has tested a prototype A.I. monitoring system through traffic cameras – it alters the traffic lights based on real-time road congestions hence minimizing road congestion.
This way, AI can reduce redundant traffic, improve road safety and reduce wait times.
Law enforcement is another area where A.I. is not being used to help law officers to identify people drinking or texting while driving, for example. Earlier, this represented an issue for human officers since vehicles move at high speed but A.I. has resolved this issue.
Now, A.I. can detect quite accurately if a person drinks or texts while driving and sends an alert to any nearby officers to intercept them.
One of those examples is Motorola Solution which brings AI voice assistants to law enforcement vehicles where police can just state a license plate and the system will look up the information and respond within a few seconds.
In order to overcome flight delays costs as well as passengers’ negative experience, AI comes to the air transport for rescue.
Data analysis and computer vision come to assist and shorten passengers’ waiting time as AI can use its capabilities to predict anything from bad weather to a certain number of technical glitches which may cause flight delays. Computer vision systems can intermittently monitor the aircrafts while AI along with Machine Learning (ML) use and process real time aircraft data, records and weather information.
Computation can reveal some hidden patterns helping the industry to gain valuable insights on possibilities that may cause delays or cancellations.
Drones have already been used in delivery service systems but soon they could be used as taxis as well. Unmanned aerial vehicles represent a one-of-the-kind solution in fight against carbon emissions, traffic congestion or expensive infrastructure.
Drones as taxis will allow people to arrive at their destinations much faster while reducing their commuting time to a minimum at the same time. Regarding urban areas, drone taxis can be a real deal for solving the issues like urban planning and urban infrastructure development.
Some recent examples of drone taxis was a display of an autonomous aerial vehicle in China, where 17 passengers had a chance to experience smart air mobility for the first time.
These use cases indicate that similar future applications are about to be developed.
Artificial Intelligence (AI) has become more than just a visionary idea – it is a part of our daily lives and we use it each day without even noticing. AI can be found in our mobile apps, in social media feeds or in the way how Grammarly checks our grammar mistakes.
Transportation industry has already used some AI solutions for a while but it won’t be long until the increase of AI within transportation and logistics.
As A.I. is getting more subtle with time, it is a matter of time when we will get to see the exciting future driven by AI!
A wide array of digital innovations have been revolutionizing healthcare and there’s no doubt: technology will stay in the medical industry.
Medical technology has evolved to connect patients and doctors thousands of miles away through telecommunications and it is not uncommon in today’s world for patients to hold video conferences with physicians to save time and money.
As per Statista, the total global medical technology growth per year is expected to be at 5% in the 2022 and although the medical tech industry had unstable growth in the recent years, the healthcare industry persists as strong with different products and companies involved.
Technological development has transformed medicine through its innovative and challenging solutions.
Electronic Medical Records (EMR/EHR)
In the last few decades, medical recording and billing advanced from a paper-based system to a digital format.
Doctors hugely benefit from these digital records – with a tap of the button, they can access all the care a patient has ever received and figure out possible illnesses. Doctor offices and hospitals can easily access the patient’s records by any connected device.
Another benefit is enablement of statistical documentation of the entire population as well as supporting the transparency of the healthcare system and possibility to integrate it with reimbursement data.
As the healthcare system changes, these types of electronic records minimize errors.
Although it is not a perfect system (sometimes difficult to access and don’t provide network-wide connectivity due to security issues etc.) it can allow doctors to access patient’s records without having to get copies or to rely on outdated fax machines.
In a nutshell, EMR enables medical staff to access patients’ records easily and provide more personalized treatment as per the medical history.
Although 3D printing started back in the 1980s by Charles Hull, its wide usage started later.
Its ‘adolescence’ stage from 1999 to 2010 was a great decade for 3D printing not only due to its popularization but when 3D printing met an open-source movement. The open-source initiative for a self-sustainable 3D printer that could build itself or some of its parts started in 2005 by Dr Adrian Bowyer in a RepRap Project.
The ability to print anything quickly became something to improve the medical industry. MRI and CT scan images can be converted into 3D image files and printed, allowing surgeons to explore the area prior to any surgery taking place.
The pharmaceutical industry also witnessed benefits – FDA approved the first 3D printed drug back in 2015 and nowadays scientists are working on 3D-printing ‘polypills’.
3D printing has revolutionized prosthetics as well – getting a customized prosthetic limb is significantly cheaper and affordable to more people as massive developments have been made within the 3D printing industry.
NGOs also helps patients and refugees from war-torn-areas with 3D printing technology providing them with printed prosthetics.
ICD-10 or International Statistical Classification of Diseases is the most recent revision of the diagnostic tool.
The classification allows illnesses, unusual findings and symptoms to be recorded and it covers more than 14000 different codes as well as additional sub-classification. This tool is able to trace diagnoses and allows a country to track its morbidity rate as well as to retrieve and store diagnostic information.
If a clinic or a hospital wants to start using ICD-10, they usually need to install the new software.
Afterwards, the staff members must be educated on how to follow set guidelines. There are many online training programs and many association websites offer instructions.
The new technology streamlines the system and enables tracking of the population statistics which can help with future diagnoses. New billing methods and tracking procedures make it easier to identify patients’ past treatments.
ICD technology reduces the amount of paperwork, increases the rate of successful treatments and allows practitioners to monitor the entire population when treating an epidemic.
In every industry, DATA is everything – in healthcare, the analysis of a huge amount of data can provide valuable insights into the state of the industry.
Some examples are that doctors can now offer more accurate diagnoses and suggest better treatment.
Data ranges from analyzing diagnostic reports to filing patient treatment histories. IBM research teams say that the same supercomputer that won a game of Jeopardy in 2011 is now used to help physicians make more accurate diagnoses and recommend the treatment accordingly.
Today, it is possible to generate and collect huge amounts of data from a number of different sources in healthcare – this data is used for analytics, making predictions about potential epidemics and preventing fatal results.
Cloud storage of data helps to improve efficiency and accessibility to the information as well as in R&D of new treatment protocols or pharmaceutical formulations since they provide vast amounts of analysis facilitating efficient health information exchange.
With cloud services and big data, there is no more hassle or high costs of maintaining additional server hardware – it is a secure and cost-effective storage solution.
Artificial Intelligence can redesign healthcare entirely – a computer can be programmed to analyze the data and come to conclusions much faster than a human can.
AI algorithms are able to extract medical records, outline treatment plans or develop drugs quicker than any medical professional.
One of the examples is Google’s DeepMind which created an AI for breast cancer analysis – it proved to outperform all human radiologists on average by 11.5%!
Another benefit of AI is personalized medicine and more effective treatment based on individual health data paired with predictive analytics – it is currently ruled by supervised learning allowing doctors to select from more limited sets of diagnoses or estimate patient risk based on genetic info and more.
Pharmaceutical industry also reaps benefits from AI – experimentation data can help drug manufacturers to reduce the time needed for developing drugs resulting in lower costs and improved replication.
There are many more applications of AI in medicine for clinical trials or radiology and it is still being tested and implemented.
Robotics and drones
Robotics is the fastest growing field in medicine – surgical robots, pharmabotics, disinfectant robots etc. are just some of the developments that robotics covers.
The global shortage of health professionals during the recent outbreak is something that could eventually be facilitated in the future by robots providing assistance to people that need help where human capacities lack.
Due to COVID-19 being highly infectious, minimizing human to human contact has become a pivotal issue.
The challenge was to get more robots in medicine to perform activities like delivery service etc. and the company JD have accepted the challenge – its autonomous robots helped in minimizing human-to-human contact while providing basic goods to people.
Another great usage of robots in medicine is having robots disinfectants which can clean and sterilize the patients’ rooms without exposing anyone to infection.
A great example is a Danish company UVD – they constructed the robots which emit ultraviolet light to kill bacteria without exposing humans to infection and the best is that they can be controlled remotely. These UVD robots have been a great help during the Covid epidemic.
Drones are another way of helping healthcare – they can broadcast information, spray disinfectants in public places or deliver smaller items. Lately, some drones have been equipped with thermal imaging and resulted in identification of people of elevated body temperature or not wearing masks but also for many other usages.
Existing examples of robot companions include Jibo, Paro or Buddy – some of them have touch sensors, cameras and microphones for their owners to be able to interact with them.
In outbreak or not, the robots and drones can become an increasingly essential support for humans in many ways.
Virtual (VR) and Augmented Reality (AR)
Virtual reality is changing healthcare and both the lives of patients and doctors – it is being used to train future surgeons for actual surgeries which showed that surgeons had 230% of boost in their overall performance due to such a tech assistant as opposed to their traditionally-trained peers.
The technology is also benefiting patients within pain management – patients suffering from cardiac, neurological or post-surgical pain have shown a significant decline in their pain levels when using VR to distract them from painful stimuli.
On the other side, we have Augmented Reality AR which is different from VR as users do not lose touch with reality and it only puts information into the eyesight quickly.
In medicine, AR can help medical students to prepare better for real-life operations in the same way as it prepares surgeons to enhance their capabilities.
For example, medical students can use Microsoft HoloLens to study anatomy via their app. By using this method, they can learn a detailed and accurate anatomy of humans without the need of real bodies.
Wearables and sensors
The biggest benefit in healthcare definitely comes from wearable technology.
Wearables have already found their path to gaining popularity nowadays – those are great devices to get to know more about ourselves and retake control of our own lives.
There are many types of wearables e.g to manage your weight or stress level, to manage your cognitive capabilities better or just to reach an overall fit state.
The tracking industry has infiltrated into the lives of all of us, old or young, with smart bracelets, smart beds and smart chest straps, smart rings, fitness trackers, smartwatches, smart hearing aids etc.
With healthcare, patients who wear these smart devices can measure data ranging from body temperature to blood pressure which can further be sent to their medical team in real-time.
In case anything looks odd or even dangerous, doctors can diagnose and treat the patient much quicker.
The entire process is quick thanks to the data collected by a wearable device as doctors do not have to run a myriad of tests to determine an illness or disease. Instead, they can refer to the data collected by a wearable to quickly figure out the cause of the medical problem.
Wearables also enable remote monitoring where a person can stay at home and share the results remotely with their physicians leading to people having more control of their own health and making more informed decisions.
Remote monitoring is especially beneficial for disabled people who cannot move and visit their doctors or hospitals – remote technology allows them to consult the doctor from the comfort of their homes.
This way of communication reduces the time and financial cost of recurring visits to the doctor.
Mobile health apps or MHealth offer a huge flexibility to all participants – the apps are one of the most inexpensive ways to facilitate communication and to provide services to the patients.
There are different apps according to their primary functions – some serve to raise health awareness while others facilitate patient-doctor communication.
Today, there is ‘an app for everything’ as Apple says and that is genuinely true – besides the apps which can help to track your sleep patterns or monitor your heart rate there are also social media apps for doctors to interact and link with patients.
Mhealth supports multiple areas in healthcare such as medication management, personal health records, diagnostics, fitness and weight loss, mental health and many more.
Due to technological innovations, it is possible to explore and research other ways of treatments today.
Healthcare industry is heading towards improved effectiveness every day.
Medical Research and Technology
Technology has disrupted the way how medical research and experiments are conducted – the same procedures now take months instead of years or longer.
Scientists were able to examine various diseases on a cellular level and produce antibodies against those with the help of technology. Such vaccines against serious or fatal diseases (polio, MMR etc.) help to prevent disease spread and save thousands of lives.
The researches and tests are still being conducted with help of technology to support prevention, diagnosis and treatment of diseases as well as development of new medicines and drugs.
Nanotechnology is an exciting new area in science with endless applications in medicine. Nanomedicine seeks to apply nanotechnology – manipulation and manufacture of materials and devices smaller than 1 nanometre (0.0000001 cm) in size – to prevent diseases and to diagnose, monitor, treat, repair and regenerate the biological systems.
Some applications of nanotechnology in medicine can be within cancer therapy, protein detection, tissue engineering, cell manipulation, heart diseases, antibacterial treatment and more.
For example, small smart pills like PillCam are already in use for colon exams in a non-invasive way. The first approved smart pill was back in 2001 and in 2018 MIT researchers created an electronic pill that can be controlled wirelessly and can help sending diagnostic information or release medicine per smartphone commands.
Besides smart pills, there are also vibrant capsules, dose tracking pills, nanobots, nanopatch vaccines, smartphone microscopes, smart bandages and more but we are still to see the future of nanotechnology in medicine.
Smart patches are also a form of nanotech and this year, France-based company Grapheal developed a smart patch for continuous monitoring of wounds – the patch measures and stores bio parameters which graphene core can even stimulate wound healing.
These examples of technologies show how new ideas can completely change the experience for patients and the treatment process for the care providers. These technologies offer amazing opportunities to provide better healthcare to people as well as supporting healthcare to cope better with the increasing demands.
As technology continues to develop, we will see even more innovation and development within healthcare.
How can Technology and AI help fight Coronavirus better?
The spread of coronavirus shows no sign of ending soon.
Many countries have been affected by the virus but at the moment, there is no vaccine to treat it. As Coronavirus continues to spread, the most important task is to contain the outbreak as much as possible.
Amidst the global pandemic, technology can be used to help and save lives.
A Canadian health monitoring company BlueDot uses AI to scrap foreign news reports, forums and announcements from public health officials to protect people around the world from infectious diseases. BlueDot’s early-warn system uses AI (ML or Machine Learning and NLP or Natural Language Processing) to track and analyze data which helps them to understand when to notify about the spread.
Speed matters the most in a pandemic situation and AI can spot the outbreaks quickly and intervene to keep them to a minimum. AI surveillance uses tons of posts about Coronavirus to get more accurate data and predict how fast the outbreaks may be.
More and more countries have started deploying AI surveillance to monitor and track citizens to achieve a wide range of purposes. Although it raises serious questions about the future of privacy, AI surveillance has proven a useful tool to monitor and respond to the global outbreak such as Coronavirus.
AI and Wearables to Track People
Some countries, like China, use AI and ML based tools to detect Coronavirus cases – not only detect but also to track people that have been put to quarantine or self-isolation.
Face recognition can help with detecting people’s faces, especially with people who have been diagnosed with the virus and if, in any case, cannot be located.
Many applications have also been developed to help people track if they’ve been in places as the confirmed virus patients.
Wearable technology is another great way that may help to fight the virus – it enables healthcare professionals to monitor vital signs with patients without physical contact.
Some hospitals in China have used a continuous temperature sensor to help reduce the spread of the virus – the sensor is applied to the patient and sends real-time information to the health institution.
Wearables have proven beneficial and can be used to monitor heart and respiratory rates among patients.
Drones’ assistance have become essential in minimizing the spread – people use drones to carry out tasks like spraying disinfectant, dispersing public gatherings or tracking people in quarantine.
Usually lighter drones are used for detection and monitoring while some types of drones can also be used for food and face masks delivery which helps prevent the virus spread.
Drones can be upgraded for Aerial Thermography – usage of drones equipped with thermal camera scanners to detect temperatures of people in a crowd where they can identify persons with the highest body temperature.
Robots and Tech Tools for Contactless Communication
Robots have become more important than ever during the pandemic outbreak as it’s extremely difficult for medical staff to remain safe while providing treatment to patients.
Shortage of medical workers has become a top problem as they are in direct contact with the patients and can get infected by the virus.
Using robots can minimize the exposure of medical staff to the infected patients – the fewer people in contact with infected patients, the better.
Robots can help perform tasks such as delivering food and medicines and cleaning the patients’ rooms enabling contactless assistance and preventing further spread.
Healthcare applications can provide real-time consultations – patients that suffer from symptoms similar to Coronavirus can consult a doctor via a video call instead of coming into close contact with patients.
Virtual consultations can provide doctors with a person’s current state along with healthcare data like blood pressure, heart rate, etc.
In China, Ecommerce giants have gone further and deployed robots to deliver food to prevent the spread of the virus. Contactless delivery systems try to minimize the human contact resulting in decreased spread of the virus itself. Autonomous vehicles can carry up to 100kg of goods and deliver 3-4 rounds per trip.
Self-driving robots can be used for disinfection of hospitals, for example, UVD robots release concentrated UV-C light which has a germicidal effect and can kill bacteria and airborne viruses on the surface.
One of the most popular robotic ‘disinfectants’ is developed by Blue Ocean Robotics that uses ultraviolet light to kill viruses and germs.
Thermal Imaging Cameras to Detect Temperature
Although Coronavirus is a current danger, people still need to work and travel if necessary.
Many thermal screening cameras have been installed at airports across many countries – they use thermal imaging equipment to detect a person’s body temperature if above normal range and react accordingly without spreading panic.
Thermal cameras create images using infrared radiation – the heat sensors record the heat of people’s bodies and display 2D images with temperature levels.
Thermal sensors can scan the large crowd of people and instantly pinpoint the ones with high temperatures or fever as opposed to checking everyone’s temperature and creating massive delays.
As already mentioned, another great usage of thermal cameras is called Aerial Thermography which includes an unmanned aerial device (drone) and an infrared camera scanning.
Drones show higher safety levels as they can complete the task with less or no contact and they can be obtained at affordable costs.
Such data can be sent to health institutions so that the treatments can start immediately and have the biggest effect.
AI to Help Develop Medicine
Coronavirus is similar to EBola and SARS as they’re RNA viruses which means they are responsive to mutation and more complex to develop vaccines.
Many companies have already deployed their resources in attempts to develop medicines – Google’s DeepMind has used its AlphaFold system to release structure predictions associated with the virus. Although these haven’t been experimentally proven, they hope it will lead to better understanding how the virus functions.
Baidu Research has opened its LinearFold algorithm for free to the scientific community and epidemic prevention centres so that all research on Covid19 structure can be continuously expedited – the algorithm takes only 27 seconds to recognize and solve the RNA structure of Covid19 which is over 100 times faster than classic algorithms.
The most important thing for these algorithms is access to data so it’s vital to release all details crucial for any algorithm searching for a cure.
Tech Tools Provide Online Education Programs
Due to the Coronavirus outbreak, many schools and universities are closed while schooling is organized via online education programs.
Simple technology tools and apps enable many educational institutions to organize pre-recorded classes or live streaming where teachers can hold their classes with help of a whiteboard or PowerPoint presentation thus continuing the school year.
In Serbia, school and university programs have been adopted via national TV channels or digital channels so that it is accessible to everyone.
A great number of online teaching and educational platforms also provide their services for free during the outbreak helping students not to be so much affected by Coronavirus.
The crisis evoked by Coronavirus triggered an increased demand for online education, courses and content.
AI to Fight Fake Information
Global pandemic affected the world population and it’s been noticed that some social media networks started posting misleading content related to Coronavirus and its prevention – from the origin of the virus to various claims about miracle cures.
Spreading panic in a pandemic situation is extremely dangerous and an increased number of fake news can just make the situation worse.
AI can be used to analyze words or word patterns to try to spotlight fake stories.
For example, Facebook uses AI to address the issue by quickly learning behaviour through pattern recognition – power of AI can detect false stories on the Internet with great accuracy.
As the Coronavirus outbreak rapidly spread in some countries, lack of medical equipment has become a common issue within many health institutions worldwide.
Lack of masks, gloves, protective scrubs etc. is a huge problem and we need to address it if we intend to keep our medical workers healthy and minimize the spread of virus with those who are the first in the frontline.
One of the companies that contribute to the issue of shortage of medical products is Sonovia, an Israeli startup that works on producing fabrics that will be immune to the virus until we develop vaccines. The most important thing is that they use technology that can cover fabrics with antivirus without using any chemicals.
In Serbia, a Facebook group ‘Vizionari Srbije’ was established on 20 March 2020 by a group of enthusiasts with a goal to help their citizens at risk of getting infected by Coronavirus. The first project was to create 3D printed safety face visors to protect healthcare professionals and medical staff from direct transmission of the virus. The project achieved a huge response – the group created visors for more than 22.000 people and still counting.
As the Coronavirus crisis is growing, we can see how some of the technologies can be helpful in the fight against infectious diseases in the future.
Technology can be our ally and help save lives, but let us not forget that humanity and solidarity among people enable the same technology to show its full potential and keep us together during the outbreak.
I believe technology still needs time before being able to stop such disease outbreaks so we need to invest in it proactively. The human experts and technology are the best combination for the future times.
We’ve all heard about Artificial Intelligence (AI) but only few of us know exactly what it means and how does it impact our everyday life.
When thinking about AI, many Baby Boomers and X Gens think of the old sci-fi films and scenes where machines come alive and take over the world. But that’s just a funny representation how humans used to perceive the unknown.
If you remember the old TV show ‘Beyond 2000’, you may recall that their ideas and inventions were outstanding at the time, which only shows the potential of the technology.
What is in fact AI and what are the examples we can see on mobile?
Artificial Intelligence (AI) is present in mobile phones for some time now, but in the prior generation of phones, it was cloud-based and required Internet to be accessed. The new generation of smartphones integrate the cloud-based AI with built-in AI on hardware – this innovation was announced by tech giants such as Google, Apple and Huawei.
Built-in AI hardware
AI’s been dominant in app development for several years already and has a potential to grow much more in the coming years.
Devices are now offering a number of features to build up AI performance – combining AI with these built-in elements makes apps more relevant and personalized.
Some of the examples are Apple’s iPhone XS (pronounced Ten-s), XR and iPhone XS Max (S-Max) which power various advanced features including Face ID, Animoji and augmented reality apps.
Immediate follower is Google’s Pixel 3 XL which is said to have the best camera phone according to TechRadar. You can blur the background with a single camera called dense dual-pixel autofocus – using the depth map, the Portrait Mode software replaces each pixel in the image with enticing blurry background known as bokeh. The result is a high quality image that matches the professional quality with just a quick tap.
The third big player Huawei released Huawei Mate 20, Huawei Mate 20 Pro and Mate 20 X. Mate 20 and Mate 20 Pro are both powered by Huawei’s newest in-house processor the Kirin 980 chipset and have triple rear cameras – the phones’ AI chip offers a number of features, including ‘4D predictive focus’ (tracking the main object in the photo so to keep in focus) and more.
Apart from those two, Huawei Mate 20 X is intended mostly for gaming audience. Its large screen can display more information thus reducing amount of scrolling.
All three brands also paid attention to a better battery performance on the new generation phones which is partly due to the in-device AI.
Use of AI in Mobile Software
Tensor Flow Services
TensorFlow was created to be a reliable deep learning (DL) solution for mobile platforms.There are two solutions for deploying machine learning (ML) applications on mobile and embedded devices: TensorFlow for Mobile and TensorFlow Lite.
TensorFlow for Mobile has a fuller set of supported functionalities and you should use it to cover production cases while TensorFlow Lite allows targeting accelerators through the Neural Networks API.
Some common use cases for on-device deep learning:
Image Recognition (helps the camera to apply appropriate filters, label photos to be easily findable, uses image sensors to detect all sorts of interesting conditions);
Object Localization (augmented reality use cases, TensorFlow offers pre-trained model along with tracking code – the tracking is important for apps where you’re trying to count how many objects are present over time – it gives you a good idea when a new object enters or leaves the scene);
Gesture Recognition (effective way of deploying apps with hand or other gestures, either recognized from images or through analyzing accelerometer sensor data);
Optical Character Recognition OCR (Google Translate’s live camera view is a great example – the simplest way is to segment the line of text into individual letters, and then apply a simple neural network to the bounding box of each);
Translation (these are often sequence-to-sequence recurrent models where you’re able to run a single graph to do the whole translation, without needing to run separate parsing stages);
Text classification (if you want to suggest relevant prompts to users based on their previous readings, you need to understand the meaning of the text and this is where text classification comes in. Text classification is an umbrella term that covers everything from sentiment analysis to topic discovery, example likeSkip-Thoughts)
Voice Synthesis (a synthesized voice can be a great way of giving users feedback or helping accessibility, and recent advances such asWaveNetshow that deep learning can offer very natural-sounding speech).
Image Recognition Features
The technology of facial recognition is nothing new but it’s expected to witness new growth opportunities in coming years.
Mobile app creators try out new ways to apply the technology in an unconventional way since camera phones became a focal point for communication. Set of techniques that serves as a groundwork for such applications are ego-motion estimation, enhancement, feature extraction, perspective correction, object detection and document retrieval.
Since retail giants such as Amazon, Target and Macy offer image recognition with their mobile apps, the technology will likely become a must-have. Scan-to-buy options enable customers to shop directly from a retailer’s catalogue and in-store signage increased in demand and became a standard offer today.
Some retailers are employing image recognition that allows consumers to point their phone at any object and receive suggestions for the similar products. Direct example of this is IKEA Place app which they developed for iOS – the users can place the IKEA furniture into their homes with the help of AR and rotate around as if in realistic world.
Visual Search on Mobile
Mobile visual search is a great potential to create the new profit opportunities – brands are trying to utilize the smartphone camera’s increasing sophistication so to activate consumers and drive sales. In some cases, visual search is faster and more accurate than text or voice and smartphone is the perfect device for the visual search technology.
Leading Internet search companies such as Google and Baidu are racing to capture mobile visual search market as it begins to replace traditional forms of search.
Let’s say you saw something you really liked but you don’t know how to find it or how it’s called – visual search lets you find all those things you don’t have the words to describe. Google Lens is a perfect example – in 2017 Google Lens was introduced in Google Photos and the Assistant. As of 2018, Google announced three major updates: first, smart text selection that connects the words you see with the answers and actions you need.
Second update is a style match, e.g. if you like a specific outfit you can open Lens and see things in a similar style that fit the look you like.
Third update is that Lens now works in real time – it allows you to browse the world around you just by pointing your camera.
With a snap of camera, companies can use technology as a tool to determine the elements of their inventory, publishers can use it to source quality visual content from their photo libraries and Digital Asset Management (DAM) software can include visual search to organize and curate their customers’ content – visually.
Visual Search can help businesses in E-commerce to increase catalogue discovery, customer engagement and conversion rates.
Image Recognition API
Image recognition APIs train computers to analyze, classify and alter different types of pictures.
Let’s list some of them:
Clarifai independent team built system that accurately recognize most entities. Unlike any other APIs on the list, it’s offered scene recognition with a bonus of video analysis. For images, Clarifai can perform sentiment analysis, text recognition, logo and face detection, as well as more robust version of Resemble’s image attribute detection: brightness, colour and a dominant colour.
Cloud Vision by Google enables developers to understand the content of an image by covering ML models – it includes many of Clarifai’s key features and some add ons like: landmark detection and a simple REST API. You can’t make your own models to test against but you have the access to an API backed by Google which is constantly improved. Furthermore, you can build metadata on your image catalog, easily detect broad sets of objects in your images and moderate offensive content from your crowd-sourced images which is powered by Google SafeSearch. Optical Character Recognition (OCR) allows you to detect text within your images as well as automatic language identification.
On the other hand, Amazon Rekognitionprides itself with a more robust suite of facial analysis tools, including facial recognition (not offered by Google or Clarifai) across images, and detailed information like beard recognition (yes/no), and facial comparison (how likely is it that two faces are the same person?). It also pledges integration with AWS services (S3 and Lamba).
We still have The IBM Watson™ Visual Recognition service which uses DL algorithms to analyze images for scenes, objects, faces and other content. You can make and train your custom image classifiers using your own image collections – use cases include manufacturing, visual auditing, insurance, social listening, social commerce, retail and e-commerce. As visual recognition understands visual data, it can turn piles of images into organized information. With the IBM Watson Visual Recognition service, building mobile apps that can accurately detect and analyze objects in images is easier than ever.
Natural Language Processing
Your first contact withNatural Language Processing (NLP) might involved a GPS navigation app which allows you to verbally request directions to a destination – they are far more sophisticated than they used to be.
The best-known mobile app with NLP is SIRI, a virtual assistant (VA) technology followed by other VAs including Alexa, Cortana and Google Assistant.
NLP became more common in the medical and healthcare sector as the use here is wide. This is especially true when it comes to the apps for wearable health apps that allow you to use verbal input as this field has an increased need for hands-free communication.
Another usage is within detecting spam messages where NLP can be extremely useful. Spam filtering algorithms ‘read’ the content of blog comments, social media or email messages etc. Then, they compare it to the known spam messages and text patterns to identify the spam.
Also, there’s a huge potential in creating and pulling the data from the information stores – a user can give verbal input to search plethora of ebooks, websites, videos, footages etc.
There will be improvements within language translation apps and mobile apps that include talk-to-type functionalities.
It converts text pieces into more formal illustrations such as first-order logic structures that are easier for a computer program to manipulate.
NLU identifies the intended semantic from the multiple possible semantics which can be extracted from a NL expression and which usually takes the form of organized notations of NL concepts.
Regardless of the approach used, most NLU systems share certain common elements – the system needs lexicon of the language, a parser and the grammar rules to break sentences into an internal representation. The umbrella term ‘NLU’ can be applied to a different set of computer applications – from simple tasks like short commands issued to robots to highly complex ones such as full comprehension of the newspaper articles.
Text-To-Speech (TTS) Systems
TTS is a high fidelity speech synthesis which gives better user experience for some specific groups like people with learning disabilities, literacy difficulties, people who speak language but cannot read it, people with visual impairment and different learning styles, people who multitask or that access content from mobile phones.
Making your digital content audible helps online population to understand the text better and as people are increasingly going mobile, TTS can turn any digital content into a multimedia experience that people can listen to the content.
Some of the best text-to-speech software are:
Amazon Polly – Besides Alexa, Amazon created an intelligent TTS system called Polly. Polly turns text into lifelike speech. It supports an API that lets you easily incorporate speech synthesis capabilities into ebooks, articles and other media. It is easy to use – you just need to send the text through the API and it’ll send an audio stream straight back to your app.
Voice Reader Home 15 – Linguatec created Voice Reader that can quickly convert text (Word docs, emails, EPUBs and PDFs) into audio files. You can listen to those files on a PC or a mobile device.
Capti Voice – Speech synthesis apps are popular in education world as they improve comprehension among other things. Capti Voice lets you to listen to anything you want to read. You can customize learning or teaching as well as overcome language barriers.
The new cutting-edge TTS service launched by Google is Cloud Text-to-Speech powered by WaveNet, a software created by DeepMind AI. It analyzes the waveforms from a vast database of human speech and re-creates them at a rate of 24,000 samples per second. The final result includes voice with subtleties like a lip smack or accents. Google advises the new service provides 32 different voices capable of speaking 12 languages and users are able to customize factors like pitch and speed.
Speech-To-Text (STT) Systems
If you’re at the conference or a lecture, it can be quite hard to write down every word the speaker says and this is where speech recognition comes in to solve the problem.
As it is dependant on computational linguistics, it identifies spoken language and turns it into text.
These systems can differ in capabilities where simple ones can recognize only a selection of words while the most advanced ones can understand the natural speech.
Some of the best STT apps are:
Evernote for Android – Evernote allows you to record audio notes and turn those into the text. Unlike Dragon Dictation (see below), Evernote saves both the audio and the text file together so you can record what’s on your mind and sort the data later. The app is free, but since it uses Google Android text transcription service, it requires Internet connection.
Dragon Dictation – this app has only one button – just tap it and start talking and Dragon Dictation will take care of the rest. The text shows after you’re done with dictating and once the app finished transcribing your speech, you can send it out via email, or copy and paste to another app. You can also post directly to Facebook or Twitter or just save your text and use it later on. The app is for free for iPhone and iPad but it requires Internet connection.
Voice Assistant – this redesigned app has a fast access feature that makes it easy to post on Twitter, Facebook or email. With Voice Assistant, you can utilize auto copy feature to send your recordings to other apps such as Google Search, YouTube etc or straight to a wireless printer. It also has grammar correction and on-screen editing with suggestion for corrections.
Transcribe – this is a popular dictation app that’s powered by AI where you can import files from Dropbox. Transcribe any video or voice memo automatically, supporting 80 languages from across the world. Once the file is transcribed, you can export raw text to a word processor to edit. The app is free to download yet you’ll have to make an in-app purchase if you want most of these features.
Speechnotes – Speechnotes doesn’t require to create an account – just open the app and press on the microphone icon and you’re ready to go. When recording a note, you can easily dictate punctuation marks through voice commands. You can quickly add names, signatures, greetings, etc. by using custom keys on the built-in keyboard. Speechnotes app allows you to access plenty of fonts and text sizes – the app is free to download from Google Play Store but you have to make in-app purchase to access all features.
Chat Bots for mobile apps are classified as ‘recent’ sensation. But their beginning and development started in 1966 with Eliza – a medical chatbot which can be considered as the mother of all chatbots.
Chatbots are great for specific tasks – from simple ones, like answering basic customer questions to complex ones like helping with customer service questions. Chatbots won’t replace websites or apps but they work great when integrated with the same apps and websites to boost interaction with customers.
For companies, it’s essential to engage with their customers on a regular basis – mobile apps are the best platform for this engagement. Today, almost everybody would rather communicate with a company through their app than through email.
Chatbots can assist with privacy issues – that is the reason why many banks are building their own Chatbot platform like Erica from Bank of America. Using native chatbot helps to avoid privacy issues.
Some great examples of chatbots are: Duolingo, Erika by Bank of America (still in beta stage), Lemonade Maya (replacing brokers and bureaucracy), Operator by Intercom (customer service chatbot that handles simple tasks). I would also like to mention Messenger platform for chatbots (Facebook) which currently dominates the Web.
Benefits of bots in mobile are massive – customer interaction will be more lively and engaging, you won’t need to download an app for a task, chatbots will be your calculator, booking agent etc., they will recommend new things to you, help you with repetitive tasks and will save you a lot of space on your phone as they will be a number of apps in one.
Developers will see the benefits through seamless deployment of the chatbots for messaging or other instances, integration of chatbot with other apps – with an intelligent chatbot you can have easy-to-see features and additional functionality added to your mobile app.
Chatbots are adding quality to your mobile app esp with the intelligence support it gets from AI since it will help you increase conversions.
How Will Mobile AI Impact Businesses?
The major tech companies are incorporating AI algorithms into various devices to strategically retain users – it helps business to deeply engage users and provide more incentives to use their services.
Many devices and apps will be written with algorithms that adapt based on the learned behavior – the algorithms will be able to filter the data, find trends and adjust the apps themselves to create more meaningful opportunities for engaging the users. Forward-thinking enterprises will prosper on the advantages AI provides, as it continues to connect users to brands.
What Will Happen
The most obvious changes AI will bring are processing speed and efficiency — doing things faster and without multiple charges of your phone. The whole point of AI is to create more personalized and user-friendly relationship with our smartphone.
Google’s $400 million acquisition of DeepMind is a prime example of mainstream AI application. A study conducted by the Mckinsey Global Institute revealed that tech giants such as Baidu and Google spent between $20 billion to $30 billion on AI in 2017, with 90% of this spent on R&D and deployment, and only 10% on AI acquisitions.
Based on the progress in technology and the growing demand for smart applications, AI and mobile are the PERFECT match.