WorkFusion offers intelligent automation solutions that combine AI, RPA, and machine learning capabilities. With WorkFusion’s RPA Express, you can automate the manual work of integrating core systems such as Citrix, Oracle, and SAP. Say goodbye to time-consuming tasks like entering credentials and navigating application interfaces.

Automation Anywhere is a leading Robotic Process Automation platform that offers a comprehensive suite of RPA, cognitive, and analytic technologies. Their Community Edition is free and tailored for small businesses, developers, and students. Unlock the full potential of Automation Anywhere’s products, including RPA, AI-powered IQ Bot, and the Bot Store.

Autonom8 has built a SaaS platform that allows you to truly digitize customer-facing workflows quickly.  They call these workflows customer journeys.  A8’s platform brings together learning (ML) and Conversations (NLP) to make these journeys agile and flexible.  And they deliver it through a low-code SaaS platform, taking away the biggest pain in the traditional enterprise software delivery cycle – project timelines running into months.  With A8’s platform, IT teams can respond to Business Requirements in a few days.  And with true SaaS-based pricing – that takes care of the vagaries of your business.

Kofax provides an intelligent automation software platform that helps transform information-intensive business processes. By combining RPA, cognitive capture, process orchestration, mobility, and analytics, Kofax enables organizations to reduce manual work, minimize costs, and improve customer engagement. Their RPA Design Studio offers a powerful design tool for building efficient processes.

Robot Framework is an open-source RPA framework suitable for both test automation and RPA. It offers a generic automation platform that can be integrated with various other tools, providing flexibility and extensibility. Built on Python, Robot Framework supports a modular architecture and is widely used in test automation.

TagUI is a free and open-source command-line tool for digital process automation. With TagUI, you can automate desktop web actions, mouse movements, and keyboard inputs effortlessly. The latest version introduces exciting features such as TagUI live mode, OCR-based clicking, and the ability to run flows with options.

Automai specializes in automation solutions for load testing, performance monitoring, regression testing, and business automation. Their RPA platform leverages AI, smart image recognition, machine learning, OCR, and robotic automation to handle high-volume and repetitive tasks efficiently. Empower your business with Automai’s automation expertise.

Another Monday offers an end-to-end RPA software suite known as AM Ensemble. This comprehensive suite covers all phases of automation, from process analysis to bot management. With AM Muse, a smart process analysis tool, users can easily navigate through workflows and gain valuable insights. Experience seamless automation with Another Monday.

Pegasystems ‘ Pega Robotic Automation platform enables organizations to automate large tasks, optimize work, and increase business productivity. It seamlessly integrates with legacy systems, closing data integration gaps without requiring changes to underlying technology investments. Benefit from fully-unified business process management and support for enterprise applications.

Linx is a low-code platform that allows you to connect backend systems, apps, and customers. With Linx, you can innovate new services, automate processes, and orchestrate data across multiple systems effortlessly. It provides a user-friendly IDE for creating and debugging processes, integrating databases, applications, web services, and more.

Automagica is an open-source RPA platform that automates tedious manual tasks on any screen. It offers a comprehensive suite for monitoring, control, scheduling, version control, collaboration, and more. Built on Python and Google’s TensorFlow, Automagica can easily incorporate the latest developments in computer vision, NLP, OCR, and machine learning.

Robocorp is a cloud platform for robotic process automation and open-source RPA tools. It provides a collection of open-source libraries and tools for RPA developers, ensuring well-documented and actively maintained core libraries. Robocorp is designed to work seamlessly with Robot Framework and Python, empowering software robot developers.

Taskt , formerly known as sharpRPA, is a free and open-source RPA solution powered by the .NET framework in C#. It offers a user-friendly interface for building and designing process automation without the need for extensive coding. Taskt excels at automating tedious and repetitive tasks, with features like OCR and image recognition.

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Sony’s move to acquire Bungie

Sony’s acquisition of Bungie is a strategic move aimed at strengthening their gaming portfolio. With Bungie under their umbrella, Sony gains access to a wealth of technology and expertise that can be leveraged to create innovative new games. In addition, the acquisition is expected to boost Sony’s sales revenue, as Bungie’s games have a loyal fanbase.

Bungie’s history and accomplishments

Bungie was founded in 1991, and their first game, Marathon, was released in 1994. However, the studio is perhaps best known for their work on the Halo franchise, which has sold over 65 million copies worldwide. Bungie’s success with the Halo franchise made them a highly sought-after studio, and in 2007, they split with Microsoft and became an independent company.

Sony’s gaming portfolio

Sony has a strong gaming portfolio that includes the PlayStation console and a wide variety of games. However, they face stiff competition from other companies, including Microsoft and Nintendo. Diversifying their gaming portfolio is important for Sony to remain competitive in the industry.

The impact of the acquisition on the gaming industry

The acquisition of Bungie by Sony is expected to have a significant impact on the gaming industry. One of the most immediate effects is increased competition between Sony and Microsoft’s Xbox. Additionally, the acquisition may lead to more exclusive games for Sony’s platforms, which could attract more customers.

Potential challenges for Sony and Bungie

While the acquisition of Bungie by Sony presents many opportunities, there are also potential challenges. One of the biggest challenges will be integrating Bungie into Sony’s culture and managing potential conflicts between Bungie and Sony’s existing teams. Another challenge will be meeting consumer expectations with new games and ensuring that they live up to the high standards set by both Bungie and Sony.

Conclusion

In conclusion, Sony’s decision to acquire Bungie is a significant move in the gaming industry. The acquisition allows Sony to expand its gaming portfolio, gain access to Bungie’s technology and expertise, and increase sales revenue. It also has the potential to lead to more exclusive games for Sony’s platforms and increased competition with Microsoft’s Xbox. However, the acquisition is not without its challenges, including integrating Bungie into Sony’s culture and meeting consumer expectations with new games. It will be interesting to see how this acquisition plays out and the impact it has on the gaming industry.

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Table of Contents

1. Introduction
2. What is Gesture Gaming?
3. Advantages of Gesture Gaming
4. Applications of AI in Gesture Gaming
5. Popular AI Projects on Gesture Gaming
   1. Project Soli
   2. Leap Motion
   3. Intel RealSense
   4. Microsoft Kinect
   5. Myo Gesture Control Armband
   6. XTR3D
   7. SoftKinetic
   8. EyeSight Technologies
   9. Control VR
   10. Thalmic Labs’ MYO Gesture Control Armband
6. Limitations of Gesture Gaming
7. Conclusion
8. FAQs

1. Introduction

Gesture gaming has been a popular topic in the gaming industry for several years. With the advancement of AI, gesture gaming has become more accessible and widespread. The integration of AI technology in gesture gaming has opened up new possibilities and created new experiences for gamers. In this article, we will explore 10 popular AI projects that have made significant contributions to gesture gaming.

2. What is Gesture Gaming?

Gesture gaming is a type of gaming where physical movements are used to control game characters. In other words, instead of using traditional buttons and joysticks, players use body movements to interact with the game. The technology behind gesture gaming is based on sensors that detect body movements and translate them into commands that the game can understand.

3. Advantages of Gesture Gaming

Gesture gaming has several advantages over traditional gaming. Firstly, it provides a more immersive gaming experience, as players feel like they are physically part of the game. Secondly, it is more intuitive, as players use natural body movements instead of complex button combinations. Lastly, it is more inclusive, as players with disabilities can participate in gaming using gestures.

4. Applications of AI in Gesture Gaming

AI has been instrumental in making gesture gaming more accessible and widespread. AI technology can accurately detect and interpret body movements, making it easier for players to interact with the game. It can also adapt to the player’s movements, making the gaming experience more personalized. Additionally, AI can improve the accuracy of gesture recognition and reduce latency, making the game more responsive.

5. Popular AI Projects on Gesture Gaming

There are several popular AI projects that have made significant contributions to gesture gaming. Let’s explore them below.

1. Project Soli

Project Soli is a Google project that uses radar technology to detect hand movements. It is a small sensor that can be embedded into devices such as smartwatches, phones, and gaming consoles. It can detect precise hand movements and translate them into commands that the game can understand.

2. Leap Motion

Leap Motion is a hand-tracking device that uses infrared cameras to track hand movements. It is a small, USB-powered device that can be placed on a desk or attached to a VR headset. It provides accurate hand tracking and allows players to interact with games in a more natural way.

3. Intel RealSense

Intel RealSense is a camera-based sensor that can detect and track hand movements. It uses depth-sensing technology to provide accurate tracking and is integrated into many devices, including laptops, tablets.

4. Microsoft Kinect

Microsoft Kinect is a motion-sensing input device that uses a camera to detect body movements. It was originally developed for the Xbox gaming console but has since been integrated into several other devices. It provides accurate and responsive tracking and allows for a more immersive gaming experience.

5. Myo Gesture Control Armband

The Myo Gesture Control Armband is a wearable device that uses electromyography to detect muscle movements. It can detect hand gestures, arm movements, and finger movements, making it an ideal device for gesture gaming. It is compatible with several gaming platforms and can provide a more personalized gaming experience.

6. XTR3D

XTR3D is a gesture recognition software that uses 3D cameras to track body movements. It can detect and recognize a wide range of gestures, making it ideal for gesture-based gaming. It can be integrated into several devices, including gaming consoles, laptops, and smart TVs.

7. SoftKinetic

SoftKinetic is a depth-sensing technology that can detect and track hand and body movements. It uses 3D cameras to provide accurate tracking and can be integrated into several devices. It provides a more immersive gaming experience and allows players to interact with games in a more natural way.

8. EyeSight Technologies

EyeSight Technologies is a gesture recognition software that uses 2D cameras to detect and track hand movements. It can be integrated into several devices, including gaming consoles and smart TVs. It provides accurate and responsive tracking, making it an ideal device for gesture-based gaming.

9. Control VR

Control VR is a motion-capture technology that uses sensors to detect and track body movements. It can be used to control game characters using natural body movements, making the gaming experience more immersive. It can be integrated into several devices, including gaming consoles and VR headsets.

10. Thalmic Labs’ MYO Gesture Control Armband

Thalmic Labs’ MYO Gesture Control Armband is a wearable device that uses electromyography to detect muscle movements. It can detect hand gestures, arm movements, and finger movements, making it ideal for gesture-based gaming. It provides accurate tracking and can be integrated into several gaming platforms.

6. Limitations of Gesture Gaming

While gesture gaming has several advantages, it also has some limitations. Firstly, it can be physically tiring, as players need to continuously move their bodies to control the game. Secondly, it may not be as precise as traditional button-based gaming, as it relies on body movements that can be imprecise. Lastly, it may not be suitable for all types of games, as some games may require more complex control mechanisms.

Conclusion

Gesture gaming is a fascinating application of AI in the gaming industry. It has several advantages over traditional gaming, including providing a more immersive and intuitive gaming experience. There are several popular AI projects that have made significant contributions to gesture gaming, including Project Soli, Leap Motion, and Microsoft Kinect. While gesture gaming has some limitations, it has the potential to transform the gaming industry in the years to come.

The post Enhance Your Gaming Experience with These 10 AI Gesture Recognition Projects first appeared on AITechTrend.

This was a tweet made by Tesla CEO Elon Musk a long time back in April. Additionally, in his talk at Tesla Autonomy Day (Link to Talk), Elon Musk said:

“LiDAR is a fool’s errand, and anyone relying on LiDAR is doomed. LiDARs are expensive sensors that are unnecessary. It’s like having a whole bunch of expensive appendices. Like, one appendix is bad, well now you have a whole bunch of them, it’s ridiculous, you’ll see.”

Almost every self-driving car company makes use of a LiDAR sensor. Uber, Waymo, and Lyft except for Tesla, all use LiDARs.

But, why Tesla so heavily relies on vision, what makes cameras so powerful and what can we accomplish from them, are all going to be discussed in this blog.

Cameras, LiDARs and RADARs

Self-driving cars and other advanced robot systems make use of several different sensors. These are Cameras, LiDARs, RADARs, IMUs, and GPS.

A camera is an optical instrument that captures a visual image. In simple terms, cameras are boxes with a small hole that allow light through to capture an image on a light-sensitive surface. They allow robots to see and visualize the environment similar to human vision.

LiDAR stands for Light Detection and Ranging. A LiDAR sensor sends out beams of infrared light into its surroundings and by capturing the reflection of those beams creates a point cloud (set of points in space) data. LiDARs help robots to scan their complete surrounding environment. The working of LiDAR is shown on the right. (Credit: Wikipedia)

RADAR (Radio Detection and Ranging) sensors work similarly to LiDARs. Instead of light, they send out radio waves to derive information about the environment. IMU stands for Inertial Measurement Unit and is used to record the physical movement (angular speed, velocity, reference position, and orientation) of the car. GPS stands for Global Positioning System and is used to geolocate the physical location of the robot.

Making sense of Images

Computer Vision is the field of Computer Science that deals with how computers can be made to gain a high-level understanding from digital images and videos. It tries to automate the tasks that the human visual system can do.

In recent years, Computer Vision has taken great leaps and development. These recent breakthroughs are powered by innovations in Deep Learning technology (both hardware and software). Deep Learning is a field of Machine Learning that makes use of Artificial Neural Networks, a biologically inspired mathematical model of the human brain, to learn patterns in data by going through different examples. The high availability of data (more examples) and powerful computing resources (GPUs) have allowed all the innovations that we see today.

The most common tasks that Computer Vision can accomplish are to recognize (Object Classification), detect (Object Detection), and segment (Instance Segmentation) as can be seen in the image above. Apart from these mainstream tasks, Computer Vision is also a major contributor to Spatial Intelligence. Spatial Intelligence refers to the intelligence that enables us to successfully perceive and derive insights from visual data. In other words, it is the ability to reason about space. To build truly intelligent robots that can perform real-world tasks like navigation, path planning, and object manipulation, spatial intelligence is the first step to achieving all these.

3D Object Detection

There have been numerous state-of-the-art developments for the 2D Object Detection task. Some recent advances include YOLOv5, FasterRCNN, and SSD networks. Their performance on the 2D Object Detection task is remarkable and even surpasses humans in some cases. But, to develop spatial intelligence, we require these networks to work in 3D. By extending the prediction to 3D, one can capture an object’s size, shape, position, and orientation in the real world.

Detecting 3D bounding boxes from a single image is a difficult task. A single image of a scene very well contains a lot of visual information but misses a key component, depth. Humans exhibit what is called stereoscopic vision. We use the images captured by both of our eyes, to retrieve the depth information of the scene. Hence, to compensate for the missing depth, computer systems make use of other depth-sensing technology like RGBD camera images and point cloud data captured from LiDARs. However, research has also been focused on deriving depth information from multiple or even a single RGB image

VoxelNet, PointNet, and Point Pillars are some of the algorithms that make use of solely Point Cloud data to do 3D Object Detection. Frustum Point Net and Multi-View 3D are some of the techniques that make use of images along with point cloud data. Finally, Single Shot 3D and Real-Time Monocular 3D are some techniques that use multiple and single images respectively. The image on the right shows a technique called SFA3D, which uses only LiDAR data

Bird’s Eye View

Autonomous Driving and Navigation require an accurate representation of the environment around the robot car. The environment includes static elements such as the road layout and the lane structures as well as dynamic elements such as pedestrians, cars, and other road users. To perform Path Planning and Navigation, the autonomous car is required to accurately know its surroundings (space). This information is best available in the form of a top-down view or bird’s eye view.

Measurements from various sensors like LiDARs and RADARs are required to be fused to lift the 2D perspective to 3D space Bird’s Eye View. However, just like 3D Object Detection, there do exist certain techniques that make use of only surrounding cameras to generate the BEV. There also exist certain challenges to accomplish this task. One challenge is the knowledge of the camera parameters and knowledge of the road surface and its height. Another challenge is the data collection itself, as to utilize Deep Learning techniques, corresponding data between a front view and a bird’s eye view is required, which can be captured using Drones and other simulation-based techniques. One interesting way to collect the data for the same is from GTA V, by toggling between frontal and bird’s eye view at each game time step. The image above illustrates the game (Credit: Surround Vehicles Awareness Github).

Some of the recent works exploring this problem are: View Parsing Network makes use of synthetic data generated from the CARLA self-driving car simulator and UNetXST network that uses synthetic data generated from VTD (Virtual Test Drive) simulation environment. Apart from using synthetic datasets, multi-sensor datasets like Lyft, Nuscenes also make it possible to do the same task. One interesting approach from Nvidia, Split Splat Shoot makes use of the Lyft and Nuscenes dataset to generate Bird’s Eye View scenes. The image on the right shows a Visualization of the Driving Scenario, the surrounding cars, pedestrians, and traffic lights as can be seen in a Tesla car (Credits: Tweet by Tesla_Adri)

Visual SLAM

SLAM stands for Simultaneous Localization and Mapping. SLAM is a method used by autonomous agents to build a map of an unknown environment and localize itself on the map as well. It is the technology that powers the intelligence in current robots, like Vacuum Cleaner.

Vacuum Cleaners make use of this technology to determine which areas require cleaning, how much to move towards them, and which areas the robot has already visited. Making use of images and video for the SLAM algorithm is what constitutes Visual SLAM.

The SLAM process consists of several different steps. The goal of the complete process is to use the information collected from the environment (images in the case of Visual SLAM) to update the position of the robot. The features extracted from the images are called landmarks. An Extended Kalman Filter (EKF) is the heart of the SLAM process. When the position of the robot changes, new landmarks are extracted from the robot environment. The robot then tries to associate these new landmarks to the landmarks it has previously observed. EKF keeps track of position while the robot moves and observes its environment. The image above demonstrates the working of a SLAM algorithm Kimera-VIO (Credits: Kimera VIO Github).

Visual SLAM algorithms are classified into two categories. Sparse methods match feature points extracted from images, like PTAM and ORB-SLAM. Dense methods use the overall brightness and pixel intensity values, like DSO and SVO.

Spatial AI

Spatial AI and 3D Intelligence are the way to building the next generation of smart robots that truly interact with their environments. The Computer Vision research applied to robots will progressively converge to a general real-time geometric and semantic Spatial Intelligence. All this intelligence stems from the visual information that the robot receives from camera images.

However, there are still avenues of research required to achieve this and deal with all the relevant issues. And, after dealing with all these issues, we could truly harness the potential of image data.

References

1. Why Tesla won’t use LiDAR? Medium Article by German Sharabok
2. How Self-driving Cars Work: Sensor Systems blog by Udacity
3. Camera Wikipedia
4. Computer Vision Wikipedia
5. Everything You Ever Wanted To Know About Computer Vision Medium
6. What is Spatial Intelligence? Blog
7. Objectron Media Pipe
8. Monocular Bird’s Eye View Segmentation for Autonomous Driving Medium
9. What is SLAM? MathWorks Blog
10. SLAM for Dummies
11. From SLAM to Spatial AI YouTube

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iAffirm, a 501 (c) 3 non-profit training therapists Adaptive therapy techniques, supported by Third-I technology, to increase efficacy for modifying self-limiting and/or harmful core beliefs that negatively impact behavior and quality of life. 

Current research reveals, through EEG sensors, that a positive emotion resonates differently from a negative emotion, and thereby can be used during a therapy session to accurately access an established, faulty belief [1]. The benefits include not only identification of core beliefs but also assistance in the process of reframing them to help clients quickly adapt to their changing world, both personally, nationally, and globally.

Shortage of Therapists

As true in a number of industries, therapists are in short supply. Hence, any method to speed results without sacrificing quality and safety, is welcomed.  Trained therapists are seeking to find the why of a person’s behavior, suffering, and inability to thrive.  Third-I quickly supports the therapist and works well in addressing perceptions developed as a result of our ever-changing world, inflicting new stress on humans at every turn. Also, because Adaptive Therapy resolves an issue in one session compared to possibly years, the cost of therapy is greatly reduced.

Pandemic Stress

The global pandemic has added a new dimension to individual stress levels that have now become chronic which, if not addressed, will produce more illness, disease and raise the cost of healthcare.  Prior to the pandemic, it was not in the consciousness of the average person that anything could stop their life, alter their life, or that illness could take the life of loved ones so suddenly.  As a result, we considered ourselves relatively safe because we believed we had a considerable amount of control over our lives.  Overnight, that changed for everyone.  So, what belief did we suddenly adopt from the pandemic?  While we each are different in our encoding of a belief based upon location, culture, family, past experiences, training, and education, etc., most people perceive the pandemic as a new limiting factor in their lives. 

Some would have replaced, “I have control over how I live my life,” to “I have no control over how I live my life,” or “I’m at the mercy of germs,” or even, “My whole life is up in the air,” “I have to stay home to be safe,” or for medical staff, “I’m sacrificing my family for my patients,” and those unwilling to do so, have left healthcare.

How long do these beliefs last?  Until something better comes along to replace it.  Of course, these beliefs might moderate due to new opportunities, but for the most part, people are stuck with their new beliefs.

For example, those that have adopted, “I have to stay home to be safe,” feel a negative feeling when they do venture out, that ushers them quickly back home and back to safety.  

Stress at Every Turn

Also, something has radically changed in our world in the last few years.  It’s the frequency and intensity of the trauma.  Most of us, in childhood and young adulthood, experienced a few traumas that shaped the way we viewed the world, ourselves, others, and how we perceive others view us. However, today, there are traumas every day.  Even if one avoids the news, traumas like the pandemic have touched everyone. Mask-wearing, vaccination, social distancing is also traumatizing people. And then there is the weather.  You don’t have to watch the news to know that climate change is affecting the weather causing record damage, loss of life, and suffering.  Road closures closed federal lands, and smoke makes evident the devastation that fires are causing during the extended season.  Evacuations for more powerful storms that drop record rain across a larger landscape also can’t be ignored as major stressors in people’s lives. 

What if you do watch the news?  Well then, you are being traumatized every day as stories of war, gun violence, assassinations, inflation, political divide, poverty, drought, loss of biodiversity, pollution, Covid-19, and so much more, mostly bad news.

Consequences of Prolonged and Ongoing Stress

Most people seek an Adaptive therapist because they don’t feel well physically or emotionally because of stress that is no longer manageable.  Up to 90% of doctor visits in the USA are stress-related [2] [3]. Stress is a factor in five out of six leading causes of death, including heart disease, cancer, stroke, upper respiratory disease, and accidents [3] [4] [5] [6] [7] [8].

What this means is that people need to seek the help of someone that can teach them how to reduce their stress. People do not like to visit a therapist for counseling because they are afraid of being labeled as inadequate, mentally unstable, or even defective.  However, reframing the counseling experience with a stress test, part of Third-I’s vision, will improve adoption by clients understanding they need help reducing their stress (external) vs exploring what’s “wrong” with them (internal).

Third-I will be launching its beta version in the first quarter of 2022 with trained therapist adoption for testing and feedback.

About:  iAffirm, a 501 (c) 3 nonprofit is dedicated to research and education of Adaptive Therapy techniques and tools, including Third-I. As part of its mission is to make stress-related therapy more accessible along with grants to financially assist any underserved population, to improve the lives of millions.  https://iaffirm.org;

*This article has been reviewed by CYC Biomedical Consulting, LLC

Sources:

1. Rahm T, Heise E, Schuldt, M. Measuring the frequency of emotions—validation of the Scale of Positive and Negative Experience (SPANE) in Germany (2017). PLoS One, 12(2): e0171288.
2. Salleh MR. Life event, stress and illness (2008). Malays J Med Sci, 15(4):9-18.
3. The American Institute of Health: https://www.stress.org/americas-1-health-problem
4. Stansfeld, S A, Marmot, MG (Eds.). Stress and the heart: Psychosocial pathways to coronary heart disease (2002). BMJ Books
5. Soung NM, Kim, BY. Psychological stress and cancer (2015). J Anal Sci Technol, 6 (30): 1-6.
6. Booth J, Connelly L, Lawrence M, Chalmers C, Joice S, Becker C, Dougall N. Evidence of perceived psychosocial stress as a risk factor for stroke in adults: a meta-analysis (2015). BMC Neurology, 15 (233): 1-12.
7. Pedersen A, Zachariae R, Bovbjerg D. Influence of psychological stress on upper respiratory infection—a meta-analysis of prospective studies (2010). Psychosomatic Med, 72 (8): 823-832.
8. Day A, Brasher K, Bridger RS. Accident proneness revisited: The role of psychological stress and cognitive failure (2012). Accidents Analysis & Prevention, 49: 532-535.

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Our artificial intelligence services turn data into useful information. With personalized analytics and easily accessible reporting tools like dashboards and indicators, you can see real-time results, identify growth opportunities, and make informed decisions.

Artificial Intelligence for Customer Insights

Companies use CRM technology to uncover the right customers and personalize their experiences in real-time. Nurturing customer relationships is as much about understanding individual customers as it is about knowing your customers. Insights in CRM are used to design the most relevant products and services to drive brand loyalty and drive top-line growth. Getting the most from CRM is about getting insights from your data. Insights derived from AI can uncover all sorts of insights, from customer lifetime value to correlation of historical trends with current data to engagement patterns and trends.

How AI Helps

Thanks to AI-powered tools, quality control is as simple as scanning barcodes with a camera. Or, you can use object and image recognition to detect defects in products or make automated quality control adjustments. With machine learning capabilities, robots can reduce the workload of human labor, decreasing costs and saving time.

Bringing AI to your product and service means speed and cost savings. With insights into your customers’ buying patterns and sentiments, you can adjust to meet them where they are. Or, you can change how products are sold to maximize profits. No matter what your next steps are, be sure to work with an expert and ask questions to avoid getting bogged down in the hype of the AI trend.

What to Know When Utilizing AI

AI tools can reduce time spent on administrative tasks, empowering you to focus on growth. As machine learning and data science advance, the use of AI will be a no-brainer for hospitals, providing technology to bolster patient care. Data analytics and AI will help optimize hospital staff performance through predictive tools and predictive tools and provide on-the-go support for medical professionals. AI offers unprecedented transparency into operations and patient services. Integrating and applying AI services will help increase revenue, help reduce costs, improve patient outcomes and ultimately improve the quality of care. By employing the right artificial intelligence, hospitals will be able to make informed decisions, improve patient care and drive growth. Ovid Therapeutics 1.

The Value of Data

Data is the new oil. Every company needs data to drive growth, but few have the bandwidth to commit to managing the volume and variety of data they have today. Despite the fact that most companies invest in data analytics software, few are able to harness their data to create actionable insights that help grow the bottom line. In addition, most large organizations have struggled to put together a holistic data strategy that addresses their organizations’ business goals. And yet, many companies are committed to advancing digital transformation, which relies heavily on data to drive innovation, growth, and innovation.

The Importance of the Data Architecture in AI

The industry is moving to a new era of rapid innovation with advancements in the use of advanced technology and increased usage of artificial intelligence. CIOs need to transform business models and rework existing technologies to leverage the power of AI.

Companies that are looking to implement AI should take the following steps:

Saturate your data with AI-related use cases: If you want to leverage AI technology, you must first identify which use cases will be the most beneficial to your business and focus your efforts on that.

Developing data models is the first step.

Create a data hierarchy using hierarchical dimensions (e.g., top-to-bottom, left-to-right, left-to-right-middle, bottom-to-top) that represent common data dimensions.

The Importance of Data Analysis

From analyzing product and customer feedback to improving patient outcomes, data analysis and data visualization is the key to success. Businesses rely on data to drive progress, innovation, and growth. It’s time to break away from a spreadsheet-driven world and re-write your data. Everything starts with data analysis, whether you’re thinking about a possible merger or buying a competitor, or evaluating how well you’re performing in today’s competitive landscape.

From customer surveys to converting traffic into leads and improving patient outcomes, AI can help you cut through the clutter and make data-driven decisions.

Conclusion

Building a strong product, improving customer experience, and establishing a competitive edge through innovative technology is no longer enough to succeed in today’s competitive market. Both the product and customer experience need to be top-notch in order to stay relevant and generate growth. Insight AI is an analytical approach to delivering insights on critical business and technology issues.

The post Insight Artificial Intelligence: How To Make The Most of AI Technology first appeared on AITechTrend.

What is artificial intelligence?

Computers use machine learning and artificial intelligence to learn and anticipate user interactions and deliver a seamless experience. Machine learning and AI are coming to the home with Amazon Echo, Google Home, and other voice-activated smart devices that allow users to play music, get weather, get news, and more, using only their voice.

Other examples of AI that can be found in our homes include the Nest Cam Indoor security camera, which uses AI and machine learning to take pictures and watch videos continuously. In the workforce, AI is going to dramatically transform the way we work.

How AI will change the way we work

Enterprise software giant SAP is looking to put AI into the hands of professionals who are not AI experts, allowing them to design, train and deploy AI within their organizations. SAP announced last month that they will begin rolling out the complete software suite of products, SAP S/4HANA (also known as SuccessFactors), powered by the HANA database, which supports Artificial Intelligence.

By 2020, the average company will invest $30-50 million in artificial intelligence. Google’s technology is moving fast and behind the scenes, thousands of people are working in companies to build this technology. They say, it’s taking up more and more of the work of companies that are starting to adopt it, but they are still early in its development.

What are the benefits of AI?

• It is expected that AI will have a positive impact on almost every job. Industries including healthcare, retail, media, manufacturing, and finance stand to gain by implementing the technology.
• AI can save people and businesses money by reducing the time it takes to identify the right person, place, and context for a given message and by automating routine processes.
• It is also expected to improve access to healthcare by connecting doctors and patients with the right information and boosting the effectiveness of hospital visits and surgeries.
• Companies like Amazon, Google, and IBM are also using AI to streamline their businesses and become a leader in the market.

What are the risks of AI?

Aside from the potential loss of human jobs, some worry that AI can put people at risk.

As reported in 2016, Google employees protested their company’s working conditions by threatening to organize a company-wide walkout. AI has also been linked to suicides.

A recent article by tech analyst Mary Meeker noted that deaths caused by artificial intelligence-based software were predicted to grow 300% in the next five years.

“Alarming. One, two, three, four, five suicides a week by someone with no history of mental health issues before. …I think the only thing more disturbing than this phenomenon is the callousness it reveals about the tech industry,” a community member in the area observed.

Conclusion

You are a member of the business community, a key leader in your company, and the creator of the growth, vitality, and revenue that will move your company forward. Take the time to explore the ways AI can benefit your business and implement the strategies that will take your business to the next level.

The post The Impending Impact of Artificial Intelligence on Business first appeared on AITechTrend.

AI in Business

Below are the main areas where artificial intelligence (AI) can be beneficial to businesses: Increasing Business Revenue Artificial intelligence can leverage digital technology to drive revenue for your business in many different ways.

Some examples of AI in Business are:

• Remote location targeting
• Smart CRM systems
• Personalized marketing campaigns
• Predictive pricing and supply chain management
• Advertising decisions
• Customized product recommendations
• Better Customer Service AI can also enhance customer service. For example, AI-powered chatbots can improve customer support by using machine learning to personalize the customer service experience. Customized Customer Experiences AI can also help create customer experiences customized to your needs.

AI in Marketing

As an emerging marketing technology, the ability to use machine learning and AI is driving a new age of marketing in which brands use automation to analyze customer data, enrich with natural language processing (NLP), automate activities and services, and provide personalized communication that pushes traditional barriers to entry.

Businesses are applying AI to automate tasks, improving customer experience and engagement, ensuring the effectiveness of marketing programs, and improving employee productivity and efficiency.

AI in Customer Service

One of the biggest benefits that AI can bring to the customer service industry is its ability to predict customer behavior. The next time you are stuck in a traffic jam and can’t find a parking spot at the mall, know that the traffic app on your phone has the perfect solution for you. So, where AI provides only predictions that improve customer experience in the near term, we should think about how it could improve the experience and satisfaction of customers in the long term.

Customer Happiness Another expected advantage of AI in customer service is that it can be trained to anticipate customer needs before they even have them.

AI in Sales

Artificial intelligence in sales is used to predict your customers’ needs, and respond to these needs when it would be the best time to do so. The resulting automated phone calls and chatbots provide you with a better understanding of the potential client and more importantly help in deciding how to engage them more effectively. This also saves your time and increases your accuracy in decision-making.

In addition, there are also chatbots that can help in searching for specific terms and phrases that your customers are searching for. These chatbots then connect with you automatically to provide you with the relevant information that you need to provide to your customers.

AI in Operations & Logistics

Artificial intelligence in logistics means advanced software, which helps companies improve efficiency by reducing shipping costs, time, and errors.

Amazon has developed AutoRip, an AI-powered robotic service that digitally copies CDs and audiobooks and delivers them to Amazon customers’ doors for free.

Oracle has developed an AI-powered solution for shopping cart abandonment in retail stores. The solution automatically detects items customers have abandoned and alerts store personnel.

Shop.org, a supermarket company, has replaced card scanners with facial recognition software in selected stores. The facial recognition software detects customers who are shopping with expired or invalid cards.

Conclusion

An ability to process data at the edge is one of the core elements needed to achieve significant business intelligence and data mining solutions. The last few years have seen the emergence of edge computing technology, that enables the processing of large amounts of data at the endpoints, increasing the available storage capacity on the devices themselves and reducing the computing and transmission of the data.

However, technology advancements are continuously causing hardware shortages, which are not improving with time. So it is important for the companies to leverage other ways of storing and processing the data.

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What is RFID?

RFID is short for Radio Frequency Identification. It works by attaching RFID tags to objects such as credit cards, passports, and package labels. These tags emit radio waves from the tag to a reader, which picks up the signals and displays the information in real-time. This is similar to barcode readers, but with added advantages such as longer range and reduced downtime. When choosing between barcode readers and RFID readers, the main difference is when RFID is being used and when barcode readers are used. In most instances, barcode readers only process barcodes and convert the data into readable text. RFID has a wider range of uses and is always used on identification tags, making barcodes less commonly used.

The Advantages of RFID

Although there are advantages to using RFID systems, the downside is that they require a lot more staff to install and maintain. For example, when you install RFID-enabled stockroom inventory, you will need to hire a staff member to maintain the inventory. You will also need to train that staff member. When you employ RFID-enabled stockroom inventory, you will also need a staff member who will be responsible for creating and managing the RFID log. And there will be costs involved with that. Also, RFID equipment is only compatible with a few channels, such as Pass Key, Card Key, and ZWave. As such, if you want to incorporate other systems into the system, such as barcode scanning, you will need to buy additional equipment.

The Disadvantages of RFID

Ruggedness and Safety: RFID systems are as effective as they are vulnerable, requiring a level of protection for tags and readers. Generally, radio frequency (RF) scanning systems include a passive antenna and receive the radio waves from another radio transmitter. The antennas do not require physical protection, but if they become an attractive target for an enemy’s weapons, these systems can be damaged or disabled. Newer RFID technologies include optical scanning and scanner-less systems, which provide far more protection. This can be especially helpful for cargo containers that will be loaded and unloaded multiple times, where the radio frequency signature will change and could be very expensive to replace.

The Future of RFID

RFID is expected to be the long-term technology of choice for a wide variety of uses in the future. It is already used for medical identification, marketing, security, and quality control. When fully developed, it could even allow cars to move without drivers.

Conclusion

RFID technology is one of the most convenient technologies used to improve the way we perform day-to-day tasks. With its precise location tracking and a large inventory, RFID is an ideal solution to minimize inventory costs.

The post RFID Disadvantages and Advantages: What You Need to Know first appeared on AITechTrend.

“This is exactly when Artificial Intelligence [AI] can provide early detection of potential falls,” says Dr. Ashutosh Saxena, Founder and CEO of Caspar.AI. Dr. Saxena continues: “Human-centered technology from ambient sensors in the apartment home can be used to detect incidents such as falls without the use of pullcords or pendants. AI learns resident movements and knows when to signal a community manager for assistance.”

On her website, Florida Elder Lawyer Beth Prather points out the challenges that arise when residents fail to wear their alerting pendant. She goes on the mention that the monthly cost of a single-feature pendant can be expensive. Comments along the same line can be found at Caring.com: Because wearables are not always worn there can be gaps in protection for residents. Caring Senior Services points out that some devices must be removed to recharge and that some devices are uncomfortable for residents to wear during sleep.

Wearable devices fail to consistently alert since residents forget to wear the device or they remove it

Says Lutheran Life President and CEO Sloan Bentley: “We strive to implement the best technology for our resident’s safety and well-being. We have found that wearable devices fail to consistently alert the team of situations since residents forget to wear the device or remove during dressing and grooming.”

The Concerns with Wearables:

• Residents do not wear them all the time.
• Wearables sometimes need to be removed to charge.
• Wearables are often removed for sleep.
• Wearables are almost always removed for the shower or bath.
• Management of wearables creates additional work for community staff – Lost pendants, testing, etc.

The answer is a series of ambient sensors in the apartment home that bring human-centered technology into the retirement community. Such a system is available from Caspar.AI. Based on seven patents, the Caspar.AI sensors track residents in their apartments and can alert community staff in case a resident is inactive due to a fall. No wearables are required. Paired with that is the ability for residents to use voice command to call for help if needed.

Don’t be lulled into the belief that wearables bring 24/7/365 protection for residents. They don’t. But Caspar.AI does!

Contact: Joe Anderson, info@caspar.ai

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