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Thankfully, there’s a tool that brings light to the whole process, and with the help of AI, provides a projection of the delivery date.

How to use AI for tracking?

An online parcel tracking tool has integrated AI, allowing users to benefit of all the insights it can bring. Ordertracker is an innovative package tracking tool that allows consumers to view their orders in real-time. The system uses AI to provide accurate delivery information such as delay predictions, delivery updates, and more. It can be used by consumers to independently track their orders over various retailers and courier services.

The Advantages of Using Ordertracker

The post-purchase experience is one of the main sources of either pleasure or pain for most retailers. Those that are able to ship out orders on time and ensure they arrive safely are able to retain consumers more efficiently. At the same time, those that use faulty shipping methods, lose packages, or fail to deliver will end up losing more customers than they gain.

With Order Tracker, the benefits are twofold, the consumer is able to keep an eye on their order, and the brand or retailer is able to offer more reliable support. Order Tracker uses AI to track packages from more than 1,200 supported shipping companies with 100% accuracy. For consumers, this means that locating their order at any point in its journey is as simple as entering the tracking number online. For retailers, this means that delivery times can be improved thanks to detailed analytics that are provided in real-time for each shipping company.

How tracking could help Ecommerces

A study has revealed that over 88% of consumers consider real time tracking as crucial, but in reality, these functions are still not being utilized, even if the benefits of implementing a tracking solution for ecommerce are quite considerable. Here’s some of the benefits of adding tracking pages to online stores :

Reducing customer support by up to 60%, answering all the WISMO queries

Where Is My Order, or it’s acronym WISMO, is known as the most asked question in Ecommerce, by implementing transparent tracking services, these queries could be reduced to almost 0.

Reassuring customers with transparency over the post purchase process

It has been proved that when customers are provided with real-time tracking, their tolerance toward delays is greater. Tracking also solves one of the main barriers when ordering online, especially from an independent or relatively new store. The lack of confidence toward the service, and its legitimacy.

Optimizing delivery times by getting reports from the different carriers

With an overview over the whole delivery chain, store owners have access to additional insights allowing them to test and optimize their deliveries, by switching from a courier service to another and this way improve their delivery delays.

Re-Converting and Upselling existing customers

As tracking is one essential step when shopping online, most customers will track their parcel independently if there is no solution presented to them. Allowing the tracking event to happen on your store is guaranteeing that your converted customers will visit your website again, creating new reconversion opportunities for stores. On average, a customer tracks its parcel 2,7 times during the shipping process, this would provide store owners with almost 3 new opportunities to reconvert their paying customers with new or related products.

How to Use Ordertracker

To use Ordertracker all consumers need to do is enter the package tracking number from their order into the website’s search box. Ordertracker will provide the tracking data for the specific package, and with the help of its AI, generate a timeline of the entire delivery process and notify you on the status of your package along with the expected delivery delay. The delivery dates are calculated using insights from 1000 previous orders that were delivered in the same area. Getting automatic updates requires entering an email address and setting an account on the platform. The AI tracking service can send you push notifications whenever the status of your packages changes, or when the package arrives in your city.

If there is a shipping disruption in a specific area, or the order was delayed at some point for just any reason, Ordertracker will be able to consider these changes and keep the consumer updated. The tool works with local and international delivery services making it a great solution for tracking packages all over the world.

Keeping Up With Packages

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Artificial Intelligence (Ai) And Deep Learning

The horizon of what repetitive tasks a computer can replace continues to expand due to artificial intelligence (AI) and the sub-field of deep learning (DL). 

Artificial intelligence gives a device some form of human-like intelligence.

Researchers continue to develop self-teaching algorithms that enable deep learning AI applications like chatbots.

To understand deep learning better, we need to understand it as part of the AI evolution:

See more: Artificial Intelligence Market

Partly to eliminate human-based shortcomings in machine learning, researchers continue to try to create smarter ML algorithms. They design neural networks within ML that can learn on their own from raw, uncategorized data. Neural networks — the key to deep learning — incorporate algorithms based on mathematical formulas that add up weighted variables to generate a decision.  

One example of a neural network algorithm is all of the possible variables a self-driving car considers when making the decision if it should proceed forward: is something in the way, is it dangerous to the car, is it dangerous to the passenger, etc. The weighting prioritizes the importance of the variables, such as placing passenger safety over car safety.  

Deep learning extends ML algorithms to multiple layers of neural networks to make a decision tree of many layers of linked variables and related decisions. In the self-driving car example, moving forward would then lead to decisions regarding speed, the need to navigate obstacles, navigating to the destination, etc. Yet, those subsequent decisions may create feedback that forces the AI to reconsider earlier decisions and change them. Deep learning seeks to mimic the human brain in how we can learn by being taught and through multiple layers of near-simultaneous decision making.

Deep learning promises to uncover information and patterns hidden from the human brain from within the sea of computer data. 

AI with deep learning surrounds us. Apple’s Siri and Amazon’s Alexa try to interpret our speech and act as our personal assistants. Amazon and Netflix use AI to predict the next product, movie, or TV show we may want to enjoy. Many of the websites we visit for banking, health care, and e-commerce use AI chatbots to handle the initial stages of customer service.

Deep learning algorithms have been applied to:

Customer service: Conversational AI incorporates natural language processing (NLP), call-center style decision trees, and other resources to provide the first level of customer service as chatbots and voicemail decision trees.

Conversational AI incorporates, call-center style decision trees, and other resources to provide the first level of customer service as chatbots and voicemail decision trees.

Cybersecurity: AI analyzes log files, network information, and more to detect, report, and remediate malware and human attacks on IT systems.

Financial services: Predictive analytics trade stocks, approve loans, flag potential fraud, and manage portfolios.

Health care: Image-recognition AI reviews medical imaging to aid in medical analysis

Law enforcement: 

Track payments and other financial transactions for signs of fraud, money laundering, and other crimes

Extract patterns from voice, video, email and other evidence

Analyze large amounts of data quickly

See more: Artificial Intelligence: Current and Future Trends

We do not currently have AI capable of thinking at the human level, but technologists continue to push the envelope of what AI can do. Algorithms for self-driving cars and medical diagnosis continue to be developed and refined.

So far, AI’s main challenges stem from unpredictability and bad training data: 

Biased AI judge (2023)

: To the great dismay of those trying to promote AI as unbiased, an AI algorithm designed to estimate recidivism, a key factor in sentencing, produced biased sentencing recommendations. Unfortunately, the AI learned from historical data which has racial and economic biases baked into the data; therefore, it continued to incorporate similar biases.

AI consists of three general categories: artificial narrow intelligence (ANI) focuses on the completion of a specific task, such as playing chess or painting a car on an assembly line; artificial general intelligence (AGI) strives to reach a human’s level of intelligence; and artificial super intelligence (ASI) attempts to surpass humans. Neither of these last two categories exists, so all functional AI remains categorized as ANI.

Deep learning continues to improve and deliver some results, but it cannot currently reach the higher sophistication levels needed to escape the artificial narrow intelligence category. As developers continue to add layers to the algorithms, AI will continue to assist with increasingly complex tasks and expand its utility. Even if human-like and superhuman intelligence through AI may be eluding us, deep learning continues to illustrate the increasing power of AI.

See more: Top Performing Artificial Intelligence Companies

Top 10 Courses And Certifications In Artificial Intelligence

A fundamental establishment in the standards and practices around artificial intelligence (AI), automation and cognitive systems is something which is probably going to turn out to be progressively important, paying little heed to your field of business, skill or profession. There are so many courses and certifications for individuals who need to jump straight into coding their own artificial neural networks, and naturally, accept a specific degree of technical ability. Others are valuable for the individuals who need to figure out how this innovation can be applied by anybody, paying little mind to prior technical expertise, to tackling real-world issues. Let’s look at some of the best AI courses and certifications which can help in improving your knowledge and skills in the field of artificial intelligence.  

If learning Machine Learning is at the forefront of your thoughts, at that point there is no looking further. Made by Andrew Ng, Professor at Stanford University, more than 1,680,000 students and experts worldwide have joined up with this program, who have evaluated it profoundly. This course gives a prologue to the core ideas of this field, for example, supervised learning, unsupervised learning, support vector machines, kernel, and neural networks. Draw from various case studies and applications and get hands-on to apply theoretical ideas to practice. Before the end of the classes, you will have the certainty to apply your insight into real-world situations.  

Artificial intelligence in Finance is an online course created by CFTE and Ngee Ann Polytechnic for experts to comprehend the utilizations of Artificial Intelligence and Machine Learning in financial services. The course pursues a comparable configuration to CFTE’s Fintech Foundation Course.  

This course is made for people who are keen to learn about techniques and strategies of artificial intelligence to take care of business issues. After the essential themes are understood you will go over how AI is affecting various industries just as the different tools that are engaged with the operations for creating efficient solutions. By the end of the program, you will have various methodologies added that can be utilized to improve the performance of your company.  

It has two three-month programs that enable you to ace the abilities important to turn into an effective Machine Learning Engineer. It’s unquestionably one of the more career-centered programs and like the Stanford course, covers the core ML principles and furthermore plunges deeper into the domain of predictive modelling. It’s beginner-focused however, anticipate an enthusiastic test. A one-to-one technical mentor is accessible. Likewise reasonable for those on a financial budget, as access is charged on a month to month basis, making it conceivably less expensive if you can finish the course quicker.  

If you need to kick off a profession in AI, at that point this specialization will enable you to accomplish that. Through this variety of 5 courses, you will learn the fundamental points of Deep Learning, see how to construct neural networks, and lead fruitful ML projects. Alongside this, there are chances to work on case studies from different real-world businesses. The practical assignments will enable you to rehearse the concepts in Python and in Tensorflow. Furthermore, there are discussions from top pioneers in the field that will give you inspiration and help you to comprehend the situations in this profession.  

Join up this certification to pick up mastery in one of the fastest developing areas of computer science through a progression of lectures and assignments. The classes will assist you in getting a strong comprehension of the core principles of artificial intelligence. With an equivalent accentuation on practical and theory, these exercises will instruct you to manage real-world issues and think of appropriate AI solutions. With this certification in your pack, it is sheltered to state that you will have a high ground at job interviews and other opportunities.  

MIT partners with e-learning stage GetSmarter to address the developing interest among business experts to get a comprehension of what precisely artificial intelligence is and how it will affect business. This online AI course is for all intents and purposes centered and follows a comparative pattern to the MIT Fintech Certificate in which students were first given a prologue to the subject and then given a capstone project to apply their comprehension.  

Offered by IBM, this introductory course will help you learn the basics of artificial intelligence. With this course, you will realize what AI is and how it is utilized in the software or application development industry. During the course, you will be presented to different issues and worries that encompass artificial intelligence like morals and bias, and jobs. Subsequent to finishing the course, you will likewise exhibit AI in real life with a smaller than usual project that is intended to test your insight into AI. In addition, in the wake of completing the project, you will likewise get your certificate of completion from Udacity.  

How Artificial Intelligence Impacts Business

AI isn’t new. People use it every day in their personal and professional lives. What is new is are new business offerings thanks to two major factors: 1) a massive increase in computer processing speeds at reasonable costs, and 2) massive amounts of rich data for mining and analysis.

This report from Harvard Business Review reflects the nascent use of AI in business, with the many respondents in the exploration phase. 

Artificial Intelligence in Business: The Awakening

InfoSys in its survey report Amplifying Human Potential: Towards Purposeful Artificial Intelligence reported that the most popular AI technologies for business were big data automation, predictive analysis, and machine learning. Additional important drivers include business intelligence systems and neural networks for deep learning.

Artificial intelligence in business brings AI benefits – and challenges – into business areas including marketing, customer service, business intelligence, process improvement, management, and more.

Major Use Cases for Artificial Intelligence in Business

The biggest use cases driving AI in business include automating job functions, improving business processes and operations, performance and behavior predictions, increasing revenue, pattern recognition, and business insight.

3. Predict performance and behavior. AI applications can predict time to performance milestones based on progress data, and can enable customized product offers to web search and social media users. Predictive AI is not limited to traditional business: Disney Labs, Caltech, STATS, and Queensland University partnered to develop a deep learning system called Chalkboard. The neural network analyzes players’ decision-making processes based on their past actions, and suggests optimal decisions in future plays.

4. Increase revenue. Companies can increase revenue by using AI in sales and marketing. For example, Getty Images uses predictive marketing software Mintigo. The software crawls millions of websites and identifies sites that are using images from competitive services. Mintigo manages the huge sales intelligence database, and generates actionable recommendations to Getty sales teams. Northface uses IBM Watson to analyze voice input AI technology and recommend products. If a customer is looking for a jacket, the retailer asks customers what, when, and where they need the jacket. The customer speaks their response, and Watson scans a product database to locate two things: 1) a jacket that best fits the customer’s stated needs, and 2) cross-references the recommendation by weather patterns and forecasts in the customer’s stated area.

6.  Business insight. AI can interpret big data for better insight across the board: assets, employees, customers, branding, and more. Increasingly AI applications work with unstructured data as well as structured, and can enable businesses to make better and faster business decisions. For example, sales and marketing AI applications suggest optimal communication channels for content marketing and networking to best prospects.

Based on the HBR report, predictive analytics is a leading business use of AI, followed closely by text classification and fraud detection.

AI Business Concerns

For all its benefits, AI projects are often costly and complex and come laden with security and privacy concerns. Don’t let these issues blindside you: carefully research the business challenges around AI, and compare the costs of adopting an AI system against losing its benefits.

·  AI is expensive. Advanced AI does not come cheap. Purchase and installation/integration prices can be high, and ongoing management, licensing, support, and maintenance will drive costs higher. Build your business case carefully; not just to sell senior management, but to understand if the high cost is worth the benefits – especially if a big business driver is cost reduction.

·  AI takes time. Give installation plenty of time in your project plan, and build your infrastructure before the system arrives. High-performance AI needs equally high-performance infrastructure and massive storage resources. Businesses also need to train or hire people with the knowledge skills to manage AI applications, and complex AI systems will require training time and resources. Many businesses will decide to outsource some or all their AI management; often a good business decision but an added cost.

·  AI needs to be integrated. There may also be integration challenges. If your AI project will impact existing systems like ERP, manufacturing processes, or logistics systems, make sure your engineers know how to identify and mitigate interoperability or usability issues. Businesses also need to adopt big data analytics infrastructure for predictive and business intelligence AI applications.

·  AI has security and privacy concerns. Cybersecurity is as important for AI applications as it is for any business computing – perhaps more so, given the massive amounts of data that many AI systems use. Privacy issues are also a concern. Some of AI’s most popular use cases — ranging from targeted social media marketing to law enforcement — revolve around capturing user information. Businesses cannot afford to expose themselves to security or privacy investigations or lawsuits.

·  AI may disrupt employees. Some positions will benefit from AI, such as knowledge workers who give up repetitive manual tasks in favor of higher level strategic thinking. But other employee positions will be reduced or eliminated. Although businesses must turn a profit, employee disruption is awkward, unpopular with the public, and expensive. According to Infosys, companies with mature AI systems make it a point to retrain and redeploy employees whose positions were impacted by AI automation.

Deploying AI systems is a big project, but is ultimately a business technology like any other system. Carry out due diligence. Research and build your expertise and infrastructure. Then deploy, use, refine, and profit.

Eruditeai: Pioneering Education Through Artificial Intelligence

Technology has the potential to significantly improve the education system globally. One such company that is transforming the way education is delivered through artificial intelligence (AI) is EruditeAI​.

EruditeAI​ ​delivers​ ​free​ ​private​ ​tutoring​ ​powered​ ​by​ ​peer-to-peer​ ​learning​ ​with AI. The company’s​ ​product​ ​ERI, ​is​ ​a​ ​dedicated​ ​chat​ ​system​ ​for educational​ ​use​ ​that​ ​incorporates​ ​AI​ ​by ​mapping​ ​students’ knowledge and intelligent matching, ​and​ ​generate​s ​feedback​ to​ ​improve​ ​the tutoring​ ​quality​ ​of​ ​peer​-tutors​ ​to​ ​a ​professional level. The company’s​ ​philosophy​ ​is​ ​to​ ​build​ ​AI​ ​technologies​ ​that​ ​augment​ ​humans​ ​as​ ​opposed​ ​to replacing​ ​them. ​​This​ ​requires​ ​EruditeAI ​to​ ​integrate​ ​AI​ ​technologies​ ​in​ ​a Human-in-the-Loop​ ​context. So, it becomes important to have​ ​the​ ​UX​ ​and​ ​interface​ ​of​ ​the system​ ​to​ ​work​ ​in​ ​harmony​ ​for​ ​the​ ​human​ ​and​ ​AI​ to work ​in​ ​a tight​ ​closed​ ​loop.  

The Force Behind EruditeAI

Patrick​ ​Poirier,​ ​President of EruditeAI​,​ ​was​ ​a​ ​high​ ​school​ ​dropout and ​was​ ​able​ ​to​ ​bounce back through​ ​private​ ​tutoring. He ​earned​ ​four​ ​University​ ​degrees​ ​in​ ​Commerce, Computer​ ​Science, ​​Psychiatry, ​​and​ ​Machine​ ​Learning. ​Patrick ​realized​ ​that although​ ​private​ ​tutoring​ ​is​ ​very​ ​effective, ​it​ ​is​ ​very​ ​expensive, ​​hence​ ​the mission​ ​of​ ​EruditeAI​ ​is​ ​to​ ​provide​ ​tutoring​ ​to​ ​learners​ ​entirely​ ​free​ across​ ​students ​worldwide. Just​ ​like​ ​all​ ​startups,​ ​EruditeAI​ ​went​ ​through​ ​ups​ ​and​ ​down​ ​along​ ​the​ ​way. With ​incremental​ ​refinements, ​​and ​iterations, the company ​presented their ​work​ ​at​ ​the​ ​United​ ​Nations​ ​twice​ ​in​ ​2023, ​​demonstrating​ ​that​ ​it​ ​is​ ​possible​ ​to combine​ ​commercial​ ​goals​ ​and​ ​social​ ​impact​ ​using​ ​deep​ ​technology. ​​In 2013, EruditeAI​​ ​started ​building​ ​educational​ ​games and ​moved​ ​into​ ​an​ ​intelligent tutoring​ ​system, ​and​ ​​into​ ​a​ ​peer-to-peer​ ​model after two years.  

Innovating Around Education

Patrick,​ ​with​ ​his​ ​background​ ​in​ ​Neuroscience,​ ​brings​ ​a​ ​fresh​ ​outlook​ ​on​ ​AI technology​ ​and​ ​Education. ​He​ ​rethought​ ​the​ ​entire workflow​ ​of​ ​private​ ​tutoring​ ​in​ ​order​ ​to​ ​completely​ ​eliminate​ ​cost​ ​to​ ​students using​ ​a​ ​combination​ ​of​ ​not​ ​only​ ​technology, ​​but​ ​human​ ​paradigms​ ​such​ ​as peer-to-peer​ ​tutoring. One​ ​of​ ​Patrick’s​ ​main​ ​contributions​ ​was​ ​to​ ​integrate​ ​a​ ​company​ ​culture​ ​that attracts​ ​high​-quality​ ​AI​ ​expertise. ​ “All​ ​our​ ​staff​ ​have​ ​the​ ​option​ ​to​ ​collaborate​ ​with​ ​University​ ​researchers​ ​at​ ​McGill University​ ​(MILA),​ ​Polytechnique​ ​University​ ​(IVADO),​ ​and​ ​Concordia​ ​University through​ ​our​ ​existing​ ​partnerships.​ ​This​ ​setup​ ​enables​ ​us​ ​to​ ​give​ ​back​ ​to​ ​the industry​ ​through​ ​published​ ​research​ ​but​ ​also​ ​offers​ ​a​ ​technical​ ​research​ ​challenge that​ ​some​ ​crave” says Patrick.  

Awards and Accolades

Most​ ​recently, ​EruditeAI ​won​ ​the​ ​Social​ ​Impact​ ​Startup​ ​Prize​ ​by​ ​CIC​ ​of​ ​the Coopérathon​. ​ ​The company was ​the finalist​ ​of​ ​the​ ​​AIconics​​ ​award​ ​for​ ​best​ ​innovation​ ​in Deep​ ​Learning.  

Investment and Collaboration to Upgrade Education Challenges Acknowledge So Far

Commenting on challenges, Patrick said, as​ ​with​ ​any​ ​startup,​ ​we​ ​made​ ​our​ ​fair​ ​share​ ​of​ ​mistakes, ​​in​ ​our​ ​case,​ ​although​ ​we had​ ​serious​ ​accounting​ ​issues​ ​at​ ​some​ ​point,​ ​our​ ​current​ ​problems​ ​are​ ​now​ ​more related​ ​to​ ​the​ ​difficulty​ ​of​ ​obtaining​ ​large​ ​​dataset​ ​to​ ​train​ ​our​ ​AI technology. ​​Not​ ​every​ ​company​ ​benefits​ ​from​ ​having​ ​large​ ​user​ base​ ​such​ ​as Google​ ​and​ ​Facebook. But with​ ​time,​ ​money,​ ​and​ ​an​ ​attractive​ ​product​ ​the​ ​real problem​ ​can​ ​be solved. Patrick​ ​often​ ​jokes​ ​that​ ​entrepreneurship​ ​is​ ​a​ ​disease​ ​similar​ ​to​ ​gambling addiction.​ ​The​ ​ups​ ​and​ ​down​ ​have​ ​a​ ​strong​ ​effect​ ​on​ ​your​ ​brain​ ​chemistry​ ​leading to​ ​rearrangement​ ​of​ ​your​ ​neural​ ​pathways.​ ​After​ ​a​ ​long​ ​period​ ​of​ ​struggle,​ ​even the​ ​smallest​ ​bit​ ​of​ ​good​ ​news​ ​can​ ​feel​ ​so​ ​much​ ​better.​ ​This​ ​addiction​ ​however,​ ​is critical​ ​to​ ​ensure​ ​​entrepreneurs​ ​have​ ​the​ ​resilience​ ​to​ ​bring​ ​their​ ​innovation to​ ​the​ ​finishing​ ​line.  

Going Ahead

Although​ ​EruditeAI​​ ​is​ ​doing​ ​very​ ​well​ ​now​ ​given​ ​the​ ​market​ ​hype​ ​of​ ​AI,​ ​the company​ ​expect there​ ​might​ ​be​ ​a​ ​decrease​ ​of​ ​interest​ ​and​ ​funding​ ​in​ ​the​ ​next​ ​24​ ​months​ ​due​ ​to unrealistic​ ​expectations​ ​of​ ​what​ ​AI​ ​can​ ​deliver. ​However,​ ​they ​are​ ​confident​ ​that some​ ​AI​ ​companies​ ​will​ ​survive​ ​and​ ​thrive​ ​despite​ ​market​ ​conditions, ​​just​ ​like eBay​ ​and​ ​Amazon​ ​succeeded​ ​after​ ​the​ ​dotcom​ ​crash​ ​of​ ​2000.

How Artificial Intelligence Is Transforming Business

Artificial intelligence has a wide range of uses in businesses, including streamlining job processes and aggregating business data.

Researchers aren’t exactly sure what artificial intelligence means for the future of business, specifically as it relates to blue-collar jobs.

AI is expected to take digital technology out of the two-dimensional screen and bring it into the three-dimensional physical environment surrounding an individual.

This article is for business owners and employees who are looking to understand how the use of artificial intelligence transforms the business sector.

You probably interact with artificial intelligence (AI) on a daily basis and don’t even realize it.

Many people still associate AI with science-fiction dystopias, but that characterization is waning as AI develops and becomes more commonplace in our daily lives. Today, artificial intelligence is a household name – and sometimes even a household presence (hi, Alexa!).

While acceptance of AI in mainstream society is a new phenomenon, it is not a new concept. The modern field of AI came into existence in 1956, but it took decades of work to make significant progress toward developing an AI system and making it a technological reality.

In business, artificial intelligence has a wide range of uses. In fact, most of us interact with AI in some form or another on a daily basis. From the mundane to the breathtaking, artificial intelligence is already disrupting virtually every business process in every industry. As AI technologies proliferate, they are becoming imperative to maintain a competitive edge.

What is AI?

Before examining how AI technologies are impacting the business world, it’s important to define the term. “Artificial intelligence” is a broad term that refers to any type of computer software that engages in humanlike activities – including learning, planning and problem-solving. Calling specific applications “artificial intelligence” is like calling a car a “vehicle” – it’s technically correct, but it doesn’t cover any of the specifics. To understand what type of AI is predominant in business, we have to dig deeper.

Machine learning

Machine learning is one of the most common types of AI in development for business purposes today. Machine learning is primarily used to process large amounts of data quickly. These types of AIs are algorithms that appear to “learn” over time.

If you feed a machine-learning algorithm more data its modeling should improve. Machine learning is useful for putting vast troves of data – increasingly captured by connected devices and the Internet of Things – into a digestible context for humans.

For example, if you manage a manufacturing plant, your machinery is likely hooked up to the network. Connected devices feed a constant stream of data about functionality, production and more to a central location. Unfortunately, it’s too much data for a human to ever sift through; and even if they could, they would likely miss most of the patterns. [Related: Artificial Insurance? How Machine Learning Is Transforming Underwriting]

Machine learning can rapidly analyze the data as it comes in, identifying patterns and anomalies. If a machine in the manufacturing plant is working at a reduced capacity, a machine-learning algorithm can catch it and notify decision-makers that it’s time to dispatch a preventive maintenance team.

But machine learning is also a relatively broad category. The development of artificial neural networks – an interconnected web of artificial intelligence “nodes” – has given rise to what is known as deep learning.

Did You Know?

Machine learning is useful for putting vast troves of data – increasingly captured by connected devices and the Internet of Things – into a digestible context for humans.

The future of AI

How might artificial intelligence be used in the future? It’s hard to say how the technology will develop, but most experts see those “commonsense” tasks becoming even easier for computers to process. That means robots will become extremely useful in everyday life.

“AI is starting to make what was once considered impossible possible, like driverless cars,” said Russell Glenister, CEO and founder of Curation Zone. “Driverless cars are only a reality because of access to training data and fast GPUs, which are both key enablers. To train driverless cars, an enormous amount of accurate data is required, and speed is key to undertake the training. Five years ago, the processors were too slow, but the introduction of GPUs made it all possible.”

Glenister added that graphic processing units (GPUs) are only going to get faster, improving the applications of artificial intelligence software across the board.

“Fast processes and lots of clean data are key to the success of AI,” he said.

Dr. Nathan Wilson, co-founder and CTO of Nara Logics, said he sees AI on the cusp of revolutionizing familiar activities like dining. Wilson predicted that AI could be used by a restaurant to decide which music to play based on the interests of the guests in attendance. Artificial intelligence could even alter the appearance of the wallpaper based on what the technology anticipates the aesthetic preferences of the crowd might be.

If that isn’t far out enough for you, Rahnama predicted that AI will take digital technology out of the two-dimensional, screen-imprisoned form to which people have grown accustomed. Instead, he foresees that the primary user interface will become the physical environment surrounding an individual.

“We’ve always relied on a two-dimensional display to play a game or interact with a webpage or read an e-book,” Rahnama said. “What’s going to happen now with artificial intelligence and a combination of [the Internet of Things] is that the display won’t be the main interface – the environment will be. You’ll see people designing experiences around them, whether it’s in connected buildings or connected boardrooms. These will be 3D experiences you can actually feel.” [Interacting with digital overlays in your immediate environment? Sounds like a job for augmented reality.]

Did You Know?

AI is predicted to take digital technology out of the two-dimensional screen form and instead become the physical environment surrounding an individual.

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