Moore’s Law, a computing term from the ‘70s, states that computing power doubles approximately every 2 years. Since the origin of this law, the changes in computers’ power and capabilities are staggering, and they’re not about to stop. As a result of these advances in computer power, AI has been able to evolve, leading to new developments in society and technology.

Calibrating Cryptocurrency Market

Currency has been around for thousands of years, and the drive to obtain more has propelled society, resulting in innovation, cultural revolutions, and wars. Now, a new type has emerged and opened more avenues for at least innovation if not revolution. Cryptocurrency is a high-tech exchange that has highs and lows, replicating the same pitfalls and opportunities as cash currency. To manage the rapid rise and fall of prices, developers turned their sights to AI. In what way could AI affect this market?

As more predictive capabilities of AI were refined, research into these algorithms revealed that such a program could manage the chaos and find patterns within it. Developers leveraged AI, and programs emerged that navigate through the muddy playing field of the market. The result is High Speed Trade (HST) algorithms, programs that use AI to detect patterns within the chaos, revealing predictions.

These HST programs predict when to buy as prices rise and then sell or sell short as prices fall. Far better than humans at predicting when the edge of the cliff will appear, AI creates a buffer in the system, blunting peaks but also leveling out losses. Thanks to the advancing predictive capabilities of AI, this new form of currency has begun to evolve into a more mainstream version.

National Defense

National security and defense have always been an arms race to gain dominance with the newest weaponry. Today, drone technology is the modern weapon of choice.

Weaponizing drones would make them an ideal fighting force because they are unmanned, disposable, and plentiful. Therefore, today’s scramble to discover AI capable of directing the drone, targeting without collateral damage, and assuming decision making for reconnaissance and attack missions could alter the power dynamic of tomorrow.

Cyber-Crime Prevention

An ever-increasing amount of cyber-attacks are designed to entice users to fall for scams. While some criminals may have discovered ways to use AI to generate data that can be converted for nefarious purposes, others are looking into ways that AI can be used to fight back. How can AI target cyber-crime?

AI countermeasures sift code and backtrack through countless loops. AI has the capability to keep up and thwart cyber-crimes; it’s an ideal hunter for the cyber criminals whose goals are obfuscation and escape through the vast network.

Powering The Future

As researches rise to the challenge to find new applications for tech that makes predictions and manage massive amounts of data, AI will only get smarter. The question for researchers of the future will be, “What can’t be done with smarter and more powerful computers?”

The 2019 Loebner Prize winner has been announced! While once again there is no recipient of the grand prize, a feat reserved for the AI that passes the Turing Test, the annual event nonetheless inspires and excites those who await singularity. The Loebner prize is offered up every year to an AI program that can beat the Turing test, a measurement of the ability for AI to mimic human thinking and response. Every year, contestants enter their AI designed to replicate human behavior in typed conversation, visual, and auditory interaction.

In the world of AI, the quest to meet the high hurdle of passing the Turing test is historic. To date, no-one has claimed the $100,000 grand prize for meeting all 3 requirements or even 2 of the $25,000 prizes for meeting any one requirement.

This Year’s Winner

Each year since 1991, a smaller, $2,000 - $4,000 prize has been awarded to the AI program that comes closest to beating any one criteria of the Turing test. This year will be the first time that one person has won a Loebner prize for a 5^th time and the first time it has been won 4 consecutive times by the same person with the same program.

This year, that prize belongs to Steve Worswick and his increasingly humanlike Mitsuku chatbot.

Meet Mitsuku

Mitsuku is an incredibly human-like chatbot that emulates the personality of an 18-year old woman in Northern England. Anyone with a web connection can freely chat with Mitsuku and ask her anything at all and she will respond. She (it?) does a good job emulating human responses, recognizing modern colloquialisms, computer-abbreviations like LOL, and current events. Ask about her favorite football team, and she’ll ‘happily’ tell you about Leeds United. In an ironic twist, ‘Terminator’ is her favorite movie.

While Mitsuku has been improving year over year, there are still recognizable differences between the chatbot and a human on the other end of the text. Mitsuku has a hard time recognizing common misspellings or transposed letters, and conversations have a finite endpoint even if the person interacting with ‘her’ tries to continue the conversation.

The Quest Continues

Mitsuku did its best to fool the 2019 Loebner Prize judges, even despite the program’s willingness to respond to a specific query in which she will admit to being AI. And, interestingly, this year there was a twist; the test was integrated into a public event on AI, allowing over 200 children to interact with the AI chatbots. A total of 17 bots from 8 countries were featured at the event.

Still, none of the AI entered into the contest was successful at fooling humans in all three categories. So ends another year without a grand prize or runner-up Loebner prize winner. However, all is not lost, and in fact, far from it. Each year that goes by, the contestants bring the world closer to an AI system becoming so advanced that it passes the Turing Test. We’ll just have to wait and see…what will happen in 2020!

Big data continues to grow exponentially creating a critical need for solutions that can make sense and extract valuable information from it. For example, the Internet is full of a wide variety of constantly growing text sources— blog posts, forum posts, chats, message boards, item and services reviews, etc. If leveraged correctly, this data can provide valuable clues on your customers’ satisfaction, their pain points, and may help to explain past customer behaviors or predict the future ones.

Artificial Intelligence (AI) gave birth to new solutions that leverage speech and text analysis bringing valuable insights into new business areas. By taking a holistic approach to AI – analyzing content across unstructured data, text, video, imagery and audio – data scientists and software developers are building new tools that help address real business needs.

Imagine a tool that analyzes customer calls and chats; automating and speeding up customer complaint analysis.

Recent advances in AI, namely Neural Nets —a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns— have lowered the computational requirements needed for many important text analysis tasks. By leveraging Neural Nets and natural language processing algorithms, businesses can use text analysis, the automated process that allows machines to extract and classify information from text, such as tweets, emails, support tickets, product reviews, survey responses, etc. This enables businesses to collect important customer data and help reduce customer service costs without losing valuable quality.

One such example is a project that we are working on with a leading software solution provider focused on the customer experience. They needed a text analysis solution that would have the capability to summarize customer call history for each user. The summary allows them to minimize the time spent on repeat problems and provides automated resolution reminders. This solution was achieved by combing several text analysis tools including finding key words, generating titles, solving classification problems, and creating short summaries – all in a comprehensive AI solution. The final solution structures data and significantly reduces customer service costs without losing valuable quality.  

Making Sense of Your Data using MVP and AI First

Many companies are faced with the challenge that the complexity, potential impact, available mathematical methods and technology might be too overwhelming for current systems or resources. In situations like this, we recommend two methodologies: MVP and AI first.

The MVP approach stands for minimal valuable prediction, a well-known minimal valuable product concept often used by software developers but applied to Data Science. The idea is to focus on delivering a minimum viable prediction as fast as you can and iterate from there.

• Focusing only on the most-pressing problem you want to solve
• Instead of assembling all your data, assemble only the data that correlates with that problem
• You’ll work “backwards” as you identify other related data, essentially following the data breadcrumbs that lead to actionable outcomes

This approach is faster, cheaper and has a much higher success rate than typical big data projects in that it starts with small data sets and incrementally scales as you uncover actionable insights ensuring you are on the right track before committing more resources.

As the name suggests, AI first concept suggests that you begin a project by formulating a business task and choosing an approach. After that, follow by asking yourself: what data do we need? What data do we have? Which data pieces are crucial and which ones can be substituted? Next, think about the technology and the properties of your future architecture; does it support the chosen AI approach? Is it flexible to support possible future changes? At every step of this process we iterate and come back to the original business question. This approach requires an organizational mindset shift and is dramatically different than trying to incorporate AI into an existing system.

By leveraging both MVP and AI First methodologies for any of your AI projects, you will produce results faster, cheaper, and without the risk of big-bite data approaches.

Polina Reshetova, a Data Scientist at EastBanc Technologies, earned her PhD in complex systems data analysis. Over the past 5 years, she has been developing machine learning algorithms and predictive analytical techniques.

September means it’s time for The Loebner Prize, the annual recognition for advances in AI. This award is meant for any AI that achieves or exceeds human capacity, passing the Turing test, and to date, none have won. The Loebner Prize Originating in 1990 by Hugh Loebner, each year a winner stands to receive a grand prize of $100,000 for advances in AI within textual, visual, and auditory categories.

In addition to the grand prize, there are two $25,000 purses for the first AI that judges cannot distinguish from a real human in at least one of the categories. We are still awaiting winners for all of these. Bronze Prize Winners Since the Loebner prize was first offered, there have been 14 separate winners of the annual ‘best of’ prize, 3 of these winners claiming the prize in 4 separate years each. They won $2,000 – 3,000 as the entry closest to meeting the Turing test requirements. • Joseph Weintraub was the first winner of the annual $2,000 prize, and he went on to win 4 of the first 5 years of the Loebner prize.

His 1991 bot submission, “Whimsical Conversation,” was built to converse in small talk and non-sequitor sentences to appear more human. Primitive by today’s standards, Wintraub’s bot was remarkably advanced at the time. Judges identified the bot as a computer, but they also identified some of the human participants as computers. Weintraub won the bronze prize of $2,000. He went on to steadily improve his chatterbot over the following years, winning again in 1992, 1993, and 1995 with his renamed, “PC Therapist” program. • Bruce Wilcox won the Loebner Bronze prize in 2010, 2011, 2014, and 2015. Leading up to these wins, Wilcox started by writing interpreter programs and then moving to games programming in the late 1970’s and 1980’s, through 2012. In 2010, Wilcox’s chatbot, Suzette, fooled 1 of the 4 judges into believing that it was human on the other end of the conversation and won him the bronze prize.

An improved version, Rosette, won in 2011. His most recent version, Rose, won 2nd place in 2013 and then won the bronze prize in 2014 and 2015. • Steve Worswick is the only Loebner prize winner to win 4 awards with the same program, Mitsuku. In addition to the recent 2018 win, this program also won the Loebner bronze prize in 2013, 2016, and 2017. Worswick has worked on the program since 2005, and it continues to advance. Mitsuku is available to chat through Mousebreaker games online. Very convincingly, this AI portrays itself as an 18-year-old woman from England and can very accurately chat with humans on the other side, hundreds of thousands of times a day.

During the most recent Loebner prize competition, 2 of the 4 judges ranked it as the best bot in the competition, making it the winner of the highest prize awarded. Will 2019 Bring A Winner? No one has ever won a silver prize or the Loebner grand prize as of yet. Will this be the year that an AI can fool all the judges into believing they interact with a human? Even if the answer remains no, the winners of the bronze category will still create excitement for and demonstrate the progress made in AI. Stay tuned!

Artificial intelligence has the capability to revolutionize the healthcare industry, reports Forbes. 

Perhaps one of the biggest opportunities for AI (Artificial Intelligence) is the healthcare industry. According to ReportLinker, spending on this category is forecasted to jump from $2.1 billion to $36.1 billion by 2025. This is a hefty 50.2% compound annual growth rate (CAGR).

Read the article on Forbes

Scientists are using artificial intelligence to determine the size of exoplanets, reports Phys.org.

Using a machine learning technique, a team of Instituto de Astrofísica e Ciências do Espaço researchers constrained the radius of an exoplanet with known mass. 

Read the article on Phys.org

According MIT Technology Review, computer vision algorithms power everything from self driving cars to medical imaging, now researchers have shrunk the technology down so it can run on a small scale device. 

Researchers have shrunk state-of-the-art computer vision models to run on low-power devices.

Read the article on MIT Technology Review

According to ZD Net, as artificial intelligence evolves the AI factory is becoming a possibility. 

For a number of years, industry thought leaders have been talking about the concept of the IT or software factory -- or software industrialization -- in which code is produced in an automated, building-block effect

Read the article on ZD Net

Everything comes with a price and with online business comes an ever-growing customer base. Businesses often fail to provide the right experience to each and every customer. Resulting in negative feedback all across social media and even worse - approximately 86% of buyers will make their buying decisions based on the experience with any business. To avoid these situations Artificial Intelligence came up with a solution - automated chatbots. Chatbots are capable of providing 24/7 customer service without costing you an arm and a leg. In fact, chatbots have been saving a huge sum of money for businesses according to Juniper research, businesses will be saving an estimated $11bn by 2025.

How Chatbots Improve Customer Service?

Customers today, expect an immediate response - more than 80% of your customers would like to have a real-time response to their queries. As per Hubspot, real-time means less than 10 minutes.

So let’s take a realistic look at the number of queries pending in your inboxes; can you provide a real-time response to these queries without automation? Chatbots are your best bet to meet the increasing demand for customer service that is immediate, accurate and “always-on”.

Chatbots 2.0

Not only AI chatbots help you cater to customer queries instantly but they also help you identify actual issues that require human support - the rest of these queries can easily be resolved through self-service options like website help page, FAQs and search results.

As per Forbes, chatbots today are far more advanced, error-free and accurate than they used to be.

Talking About Numbers

• According to salesforce the most popular CRM solution, chatbots have successfully improved customer satisfaction rate by up to 35%.
• The 2016 Gartner research predicted that 80% of all businesses around the globe will opt for chatbots by 2020 - which seems to be nearly accurate as 90% of all customers have rated instant response from business as important or very important in a recent study.
• 90% of all customer queries received by any business in the healthcare, banking and eCommerce industry will be catered by chatbots in 2022 - saving 70 cents per customer interaction. (Juniper Research)
• Not only 67% of your customers enjoy using chatbots all around the world, but actually prefer them over FAQs, search engines and human support agents for various reasons.

Most of the online consumers when asked why would they use chatbots and the answer most commonly found was “to get an immediate response in emergencies”. Next in line was to get a resolution of their issues and complaints. There is a complete study on how consumers use chatbots and how they are transforming customer service and other areas of business.

The Takeaway

Chatbots are smart, instant, cost-effective and user-friendly. A single chatbot is capable of responding to thousands of queries simultaneously and can actually provide a quick resolution to 69% of your customers, who are merely looking for a quick response to their simple questions.

A chatbot integrated into your website and social media can:

1. Improve your customer service response time
2. Boost your brand’s reputation
3. Improve your customer feedback
4. Give you opportunities to sell more to your customers
5. Encourages them to talk about your service to others
6. Review your brand positively on social media and review sites.

AI chatbots are not just a passing trend that the tech industry will get over. They are providing great value to businesses and customers both and will save companies an approximate $8 billion by 2022.

Usama Noman is Founder and CEO of Botsify.  Botsify is a platform for people and businesses to make their own smart Chatbots without knowing how to code.

People themselves know their businesses better than anyone and as experts on business cases they can automate tasks like FAQ's, Customer support, filling up a form, and collecting data from people. 

We aim to change the conversation in Business, Education, and Human Interface with any tech gadget. We automate conversations/ use-cases so that a person can now have a Computer talk/ show/ take instructions from the person across the screen. We are disruptive in our mission to be the best and are bringing new offerings in voice too!

Usama started Botsify working out of his living room stealing hours whenever he could get a chance and made the product from the ground up. During the early days, Usama acted as the sole engineer, designer, business developer, and support for the entire startup. Usama has been a pivotal part of several previous startups and development teams and is the front runner at Botsify. He holds a Bachelor's Degree in Computer Science from FAST NUCES - Karachi, bagging the silver medal and published a paper in IJACS on sentiment analysis on Amazon Reviews along the way.

With breach attempts and cyberattacks increasing, many companies say artificial intelligence (AI) is a necessity in identifying and thwarting threats, and they are devoting bigger pieces of the budget for AI’s role in cybersecurity. “It’s a fundamental tool going forward due to the approaching reality of the 5G-enabled world, where massive amounts of data will need to be analyzed in real time,” says J. Eduardo Campos, co-founder with his wife, Erica, of Embedded-Knowledge Inc. (www.embedded-knowledge.com) and co-author with her of From Problem Solving to Solution Design: Turning Ideas into Actions. 

“5G will empower machine-to-machine communications, and the new wireless technology will be faster, carry more information per second, and interconnect sensors, devices, and computers at large scale.

“With more data flowing at higher speeds, only AI solutions will be able to handle such high volume of transactions while monitoring applications and sensors at the edge of companies’ networks.”

Campos offers some reasons AI is an effective cybersecurity tool for businesses:

• System-entry protection. AI systems can scan the retina and fingerprints for biometric logins, identifying small changes in patterns — a more secure point of entry than traditional passwords provide. “Hackers cracking passwords open Pandora’s Box,” Campos says. “Passwords are vulnerable to cyberattacks, and personal information such as credit cards are easily compromised. Changing passwords alone isn’t a solution. Biometric systems lower your risk of breaches because biological characteristics are hard to duplicate.”  
• Enhanced threat detection and attack prevention. Cybersecurity firms are training AI systems to detect malware and viruses by using special algorithms. “This enables AI to use pattern recognition, which helps identify malicious software and isolate them,” Campos says. “AI systems are being trained to recognize ransomware before it encrypts. The predictive analytics AI uses are much faster than a manual approach.”
• Time and cost saving. The average overall time to detect threats and respond to breaches is reduced by up to 12%. “This time reduction occurs by repeatedly scanning for anomalies that show threat patterns,” Campos says. “AI used in fraud detection has saved some companies millions.”
• Natural language processing. This is a subfield of computer science, information engineering and AI related to programming computers to process natural language data and narrow down the most pertinent information. “AI-powered systems can collect data for reference by scanning articles and studies on cyber threats, helping organizations prepare effective strategies,” Campos says. 

“There is still no guarantee against a cyberattack,” Campos says. “But AI certainly takes cybersecurity a step further, and businesses of all sizes are taking notice at a time when threats are always knocking at the door.” 

Eduardo Campos is co-author with his wife, Erica, ofFrom Problem Solving to Solution Design: Turning Ideas into Actions. Campos spent 13 years at Microsoft, first as a cybersecurity advisor, then leading innovative projects at the highest levels of government in the U.S. and abroad.  His consulting firm, Embedded Knowledge Inc. (www.embedded-knowledge.com), works with organizations and entrepreneurs developing customized business strategies and forming partnerships focused on designing creative solutions to complex problems.

Artificial Intelligence is slowly taking over our day to day lives - especially when it comes to the workplace and using tech to enhance and fast-track tasks.

There are many sectors in which AI can help improve services - specifically national health services, banking and legal services. Not only do some of the biggest names in tech debate over the future of AI and how it continues to make life easier and better for many, but we are now seeing some of the biggest tech companies now recruiting heavily in AI.

But, who is recruiting for AI roles the most and is making big steps in looking toward the future?

With AI-related jobs more than doubling over the past three years and job postings related to AI increasing by 119%, RS Components has analysed job posts from some of the world’s biggest tech companies to discover who has the highest percentage of AI-related job openings.

Microsoft leads the way with 1,964 AI job openings, equating to 36% of the total jobs they have on offer. With Bill Gates being one of the world’s richest people still, this is no surprise - Microsoft still leads the way with some of the most innovative and thought-provoking technological inventions.

Nvidia follows in second place with 837 of AI job openings, equating to 33% of total jobs they have on offer. The computer game company designs graphic processing units for the gaming and professional markets, so using systems and analytics such as AI helps with processes and development of new games.

A former Google Exec has predicted that AI will replace 40 per cent of jobs in the next 15 years. The Google Exec stated that AI will allow entire new industries to be built from the ground up with automation in mind. AI will be cheaper than human employees, however, it will also create new roles, as well as replace current ones.

Popular social media platform Facebook and streaming platform Netflix make it into the top ten with Facebook offering 191 jobs in AI, 6% of the total, and Netflix offering 35, also making up 6% of the total jobs they have on offer. Both companies are growing rapidly and are having to set new trends to keep up with technology, so it's only right that they are in the top 10 companies that are hiring in AI the most.

The largest tech company in the world, Apple, comes in at number 12 with 129 AI jobs on offer, only 3% of their total 4,574 jobs available. Apple is one of the most innovative companies in the world - alongside Google - so it may come as a surprise that they are in 12th place. This could be due to the fact that they are forward-thinking and hired the majority of their AI roles a few years back.

Another innovative company in the technology business is Bezos' e-commerce platform, Amazon, which comes in 15th place offering 297 roles in AI, 2% of its total 18,781 jobs on offer.

It’s clear that the technology sector prioritises hiring in AI, but which sectors will be next to drive up the market and start boosting their recruitment in AI?

Take a look at RS Components’ interactive campaign here which highlights all of the companies which are recruiting in AI.

Top Ten Global Companies with highest % of AI Jobs:

At present many businesses are deploying the use of AI-enabled chatbots and have discovered them to be the future of engagement between an organization and its customers.

AI enabled chatbots offer many benefits to a business and are revolutionizing the customer service industry; they act as interactive agents in the daily operation of an organization while improving sales processes.

In addition, AI enabled chatbots also help organizations solve problems with the aim of building brand loyalty.

Reasons why businesses need AI - Enabled chatbots

AI enabled chatbots are working because most organizations have discovered that they are capable of enhancing the customer's experience and also doing the following:

• Chatbots are more efficient in some specialized task: There are so many tasks that can be done quickly and more efficiently by chatbots than by humans. A task such as ordering pizza, hiring a cab, and checking weather conditions can be done efficiently using a chatbot, businesses can also use chatbots in automating tasks like inventory ordering and management.
• Chatbots provide better service on tablets and smartphones: At present, the world is moving towards an immersive mobile phone future, and the numbers of people who own mobile phones are now above those who own laptops and PCs. Chatbots on mobile are helping to create more streamlined app interfaces which enable users to buy, compare, browse and get support all from a single interface.
• Chatbots can help businesses scale up operations: Chatbots also have the ability to help a business scale up its operation; this is because they reduce human error. Whereas a human can handle a limited number of conversations, chatbots can handle multiple conversations at a time. Therefore employing the use of chatbot to complement human effort can boost business and help scale up its operation.
• Take loads off from customer support team: For a business that gets lots of inquiries from customers on a daily basis, the use of chatbots can help take loads off the customer support team. By acting as the first point of contact, chatbots can help to screen calls from customers and redirect to human agents only when required.
• Chatbots can assist customers in getting the right products: If you operate a business that sells goods and services which are similar to each other, chatbots can help customers in deciding the best product choice for them.
• Chatbots are also a prudent investment: If your products are directed to millennials who prefer to make comparisons before buying a product. Chatbots can help them make comparisons and ease them into a purchase decision.
• Promotes interactive marketing campaign: The use of chatbot also helps to promote an interactive marketing campaign; this is because they do not present a passive user experience. Also, the availability of chatbots on platforms like Facebook Messenger and others means that you can get in touch with more people at once.
• Drive organizational efficiency: The use of chatbots also helps businesses to save money from backend support. Instead of employing more people to perform repetitive and mundane tasks, chatbot business solutions can help automate processes and streamline tasks.

Finally, as the world moves towards a digital future and more conversational way of doing things, we can expect that chatbots will continue replace human assistance and deliver better more efficient customer service.

I am not going to go into the long term future of AI because that would be highly speculative. I would rather focus on the short term future of AI, much of which is already taking place. For the purpose of this article I want to focus on AI-powered hyper-contextualization and how that impacts our realities. AI means that we can crunch insane amounts of data points together in order to map out and ultimately predict behavior. When it comes to content, this hyper-contextualization allows content to be curated according to personal taste. We already see this in social media for instance with curated feeds according to personal. political and religious preferences.

The result is that we become exposed to content that aligns with how we already think. So rather than be challenged by different lines of thought that force us to reconsider our points of view, these points of view are reinforced. Gaps between groups become wider and more challenging to bridge because the common ground is lost.

Now when you take it a few steps further, we can envision a world where content is curated at a sentence level to match audience preferences. Imagine reading an online article in which every sentence is devised to match your preference in tone, style, political alignment, biases etc.

Human thought has a binary nature. Right and wrong. Up and down. Forward and backward. Thought evolves through polarities. What happens to thought once you minimize the dialogical nature of ideas and make them monologues, with each idea further corroborating past behavior. tendencies and biases. I don't know what happens, but it certainly does not look like something positive to me.

In sharing lives with other humans, we run into conflicts constantly. Unlike AI, people are not necessarily consistently able to smartly predict what we are going to do next. As AI evolves, predicting where we are going to go before we even type an address on a map navigator, or what we want to buy for our home before even beginning a search in a marketplace, we become more and more unaccustomed to having explain how we think, what we want, and why we want it. AI can create the illusion that the world is made to the taste of each individual. Psychologically this could easily foment a scenario of social withdrawal and lack of desire to engage with others, even more so in adversarial situations.

No need to drive because the car will get you there. No need to enter the destination because it already knows based on your previous behavioral patterns, calendar, searches, and other data points. We have not seen the full ramifications of this reality, but the technological conditions for this scenario are already feasible and available. What’s left?

As we disengage from manual tasks there is a lot more bandwidth to think, structure, plan, architect. But do we have the educational framework to make use of this new bandwidth in a positive way? Or will we use this extra bandwidth to consume more, worry more, I am curious to see how we will evolve emotionally, spiritually, socially and politically to keep up with the ever-increasing level of technological transformation.

I do approach it with optimism and recognize the positive transformation potential that AI brings but believe that our attitude, flexibility, and discipline are crucial towards developing a healthy relationship with this new world that AI is opening up.

Gabriel Fairman, CEO of Bureau Works 

Music has and will always be an important part of society as long as human beings exist. However, as society changes in many aspects, music also evolves to meet its new needs and demands. For quite a while now, AI has been a buzzword in the technology space. It is increasingly becoming a talk of almost every industry primarily due to its ability to offer automation services, ease responsibilities and offer innovative workflows. The entry of this new technology into the music industry is important due for a few reasons. Although to some it may sound like cheap science fiction, it is true that we can have robots capable of creating songs, playing music and AI-enhanced robots writing song lyrics. Such practices are not new in the music industry.

Since 1951, the music industry has been trying to leverage on AI. The first time when AI entered into the music industry began when Alan Turing, a computer scientist recorded computer-generated melodies. Although the recording was filled with various disturbances, it was an important step towards developing an AI-enabled music business. Nowadays, AI trains itself to analyze various composition types through reinforcement learning, an approach which is a massive improvement from the time of Alan Turing. Through learning continuously, this technology is capable of extracting the characteristics of a music thesis in its entirety. You might think that the ability of AI to compose different innovative pieces of music is a big achievement, but its ability to write lyrics is even cooler than you can imagine. By training AI models with a large number of datasets that contain random music lyrics and compositions, AI can easily write music lyrics and make compositions.

Although some people have ill-advised opinions about AI, thinking it will replace artists, the truth is actually the opposite. While some may see it as a threat to creativity and musicians, it can play a crucial role in the music business which may end up being highly advantageous; if properly applied of course. In fact, AI may help musicians and employees with their work. For example, as indicated by the early manifestations, AI can satisfy the ever-increasing demand for music and promote understanding of what listeners want. In the current big data era, AI can help musicians understand the music market, and in the process develop music that’s in demand and has the capacity to reach people who actually want to listen.

The experience of the listener is an area that has suffered. When it comes to the music audience, there are many ways in which their experiences can be enhanced and revolutionized altogether. With cutting-edge tech such as AI, live performances can be taken to the next level by the artist and in the end will enhance the listener’s experience. This increases the musicians’ chances of success. This technology has also made it easy for music streaming platforms to sell their music as the listeners can simply hum a song to find the artist who sang it. Similarly, AI and technology in general will bring a lot of difference in the music industry through education. With different technologies, music students have many tools which not only allow them to stay connected but also assure them of space for collaboration on different projects.

In summation, AI is changing the music industry making it easy for stakeholders in this sector to carry out various activities. As technology changes, it is expected that the music industry will change as well to allow listeners and viewers to experience the best that is made possible by technology.

Machine Learning has been developed under the umbrella term of ‘Artificial Intelligence’. Essentially, it’s set to change the way businesses operate as know it. It’s already been adopted across many industries including healthcare, law, education and retail.

Logistics companies and industrial business, in particular, are enjoying the benefits that machine learning and AI can bring to their efficiency and production. Perhaps one of the biggest businesses to adopt this new technology is the world’s largest e-commerce marketplace, Alibaba.

What Can Machine Learning and AI Bring to Warehouse Management?

For those industries that are truly open to embracing new developments in technology, machine learning and AI can be revolutionary. It effectively means that robots are able to take on tasks that would usually be assigned to humans. This kind of technology greatly improves the productivity of a business, as robots are able to complete tasks at a faster pace than humans. There’s also less margin for human error, such as a parcel being delivered to the wrong address, for example.

Furthermore, machine learning algorithms can be used to forecast demand. It’s proving to be far more effective than existing methods that had no way of calculating demand over time. This means that a warehouse would be better equipped for coping with busier periods such as Black Friday of Christmas.

How Has Alibaba Implemented It?

The Chinese company Alibaba has a total of $248 billion transactions – more than eBay and Amazon combined! So, it’s safe to say that any company as influential as Alibaba must be entirely confident in artificial intelligence in order to use it. They now have the world’s largest automated warehouse – whereby some 700 robots do all of the work. These robots pick out the stock to send to customers and are now responsible for 70% of the work in the warehouse. Alibaba now claims that because of this technology, it will be eventually delivered to anyone in China within 24 hours and 72 hours for internationally.

Additionally, the robots are able to carry up to 500 kilograms above them as they make their way around the warehouse. Every robot is fitted with sensors, so they avoid colliding with one another. They also include a Wi-Fi feature so they can be summoned at any time by the employees.

Supply Chain Management

For a huge company like Alibaba, supply chain management is crucial. Thanks to app developers, machine learning makes it possible to discover patterns in the chain using algorithms. The computer is able to analyse the existing chain and advise on which areas could be improved. Due to the nature of the computer, it’s also able to identify such flaws far quicker than manual intervention by an external assessor. Alibaba can then control inventory levels, production planning, quality and transport management.

The Future of Machine Learning in Warehouses

Alibaba is not the only business bringing automation to warehouses. Amazon and food delivery service Ocado also use robots to transport parcels around their fulfilment centres. With more and more investment being pumped into the technology, it’s likely that machine learning will be utilised more in warehouses and factories across the globe. Its potential to deliver additional value to businesses, and therefore customers, cannot be ignored. For this reason, machine learning and artificial intelligence are predicted to become an essential element in future supply chains.

Artificial Intelligence (AI) is responsible for technological advancements affecting many diverse aspects of society. Most of this development is focused on achieving economic or social benefits for the world’s population. As is often the case with powerful tools, there are also individuals and groups that would use the capabilities of AI and the related field of machine learning (ML) for nefarious purposes. We will take a look at a few ways where this use of technology has led to new issues and concerns by cybersecurity professionals. 

Conducting Spear-Phishing Attacks

Spear-phishing is a widely used method of performing cyber attacks and the ability to automate these attacks can make them exponentially more dangerous. IBM’s development of a highly targeted and evasive attack tool called DeepLocker is powered by AI. The company purposely hid malware in a video conferencing application and had DeepLocker unlock the program when prompted by facial recognition of a specific individual. 

IBM designed DeepLocker to understand how AI and malware can be used for new types of spear-phishing attacks. Its success indicates that this technology in the wrong hands can be used to cause havoc in many unexpected and detrimental ways. 

Identifying System Vulnerabilities

The United States Department of Defense has purchased technology from a private company that possesses self-healing capabilities and is optimized to employ machine learning techniques to discover system vulnerabilities. While this particular piece of software is under government control, there are certainly similar tools being developed by cyber criminals with the intention of finding exploitable vulnerabilities in the systems that society depends on every day.

Software vulnerabilities have always been a prime target of hackers. By delegating the labor and time-intensive tasks of identifying weak points to AI-powered programs, the hackers can spend more time sharpening the weapons with which to take advantage of vulnerabilities found by their artificially intelligent tools.

Controlling Autonomous Vehicles

The potential to use AI and ML techniques to hack into autonomous vehicles is a concern that needs to be addressed before the wide adoption of these machines. The ability to fool the vision and collision avoidance systems of these vehicles could lead to catastrophic results as traffic signs are ignored or rules of the road disregarded. 

Consumer drones can be weaponized and controlled by an application that uses ML to continually update their ability to avoid capture. These techniques could lead to new types of terrorist attacks that will be much harder to detect and prevent.

Impersonating Individuals

The ability to use machine learning to impersonate individuals in various ways opens up new avenues through which cybercriminals can exploit their victims. The creation of fake voice recordings and videos using AI are making it increasingly hard to determine between reality and an impersonation.

Using impersonation techniques, one may be tricked into providing personal details that otherwise would never be made public. This can lead to compromised systems or accounts and can be extremely detrimental in many ways.

These are just a few of the ways that the technologies of AI and ML may be used with malicious purpose. Society must be aware of the double-edged potential of these disciplines to bestow benefits on society or cause significant harm.