PyRobot is an open-source robotics framework that Facebook developed with Carnegie Mellon University. It is designed for easy configuration, so AI researchers can get a fully functioning robot up and working within a few hours.

“PyRobot is a lightweight, high-level interface on top of the Robot Operating System (ROS),” Abhinav Gupta, research manager, and Saurabh Gupta, research scientist at Facebook, explained in a blog post. “It provides a consistent set of hardware-independent midlevel APIs [application programming interfaces] to control different robots. PyRobot abstracts away details about low-level controllers and interprocess communication, so machine learning experts and others can simply focus on building high-level AI robotics applications.” Some of the difficulties with programming robots are a challenge that Facebook wants to take on and fix.

What is PyRobot?

PyRobot is a python package designed for experimental research in robot learning. It is a high-level interface that is on top of the Robot Operating System (ROS). As the name implies it is designed to be programmed in the popular and versatile Python language. This allows researchers to focus on building high level applications using affordable robots and hardware. This effectively lowers the entry barrier into building and customizing robots.

PyRobot abstracts functions like position, velocity and torque to control joints. It also includes path planning, kinematics and visual simultaneous localization and mapping (SLAM). This level of abstraction allows developers to program robots with very few lines of Python code. Facebook will provide pre-trained models of navigation, grasping and pushing algorithms. There are more advanced functions such as IoT, which will shift responsibility to the developers.

In recent times Facebook has expanded its focus into AI and machine learning. In December 2018, Facebook open-sourced the PyText natural language platform. The intent was to make it easier to deploy Natural Language Processing (NLP) systems. During the same month, Facebook also open-sourced DeepFocus, an AI-powered system for more realistic VR images.

Beyond the concept of abstraction, PyRobot is designed to function with a wide range of different robots. There are two robots that PyRobot works with so far. These include LoCoBot, an arm robot that utilizes a base and Sawyer, a single arm commercial robot. PyRobot uses a common API with them that can command both with the same code. The ultimate goal is add additional approved robots over time that will work using the same API. The diversity in robot hardware is a reality in robotics research that creates many challenges.

“The cost of hardware and the complexity of specialized software has limited the scale of robotics research,” Facebook’s AI researchers said. “With lower barriers to entry, researchers can deploy several robots that collect data and learn in parallel, for example. By providing a common framework across different hardware, PyRobot will lead to development of benchmarks in robotics (similar to other areas in AI) and quantify the pace of progress.”

The release and advancement of PyRobot is significant for Facebook because robotics plays a huge part in the battle for dominance in AI. Will Facebook be able to unify a common platform for robots the same way it has for friends? Only time will tell.

When it comes time that an AI passes the Turing Test, life as we know it will shift. There will be significant ethical ramifications to which we currently don’t have ways to address. However, we better figure it out soon because this day is coming faster than you think.

The Turing Test, developed by English computer scientist, Alan Turing, in 1950, exists to determine if – when – a machine behaves in a way that makes it indistinguishable from a human being. It’s the moment when machines stop being tools and become sentient; it’s when you can’t tell if you’re talking to a human—or a computer.

What Is The Next Step

In 2018, Google’s Duplex system so convincingly mimicked human speech that it is considered to have passed the Turing test in this one aspect. Google considers this a major milestone in the development in AI, and it is certainly a huge step forward.

Speech is one thing, but what happens when a machine is so lifelike that it appears human in every way? Sci-Fi TV shows, movies, and even video games have grappled with this question for years. Those have all been like our rehearsals for the real play, which may open on the world stage sooner than later.

Ethical Quagmire

The ethical questions start almost immediately: If we relegate these super-advanced machines to the role that Alexa and Siri fill now, are we oppressing sentient beings, or just using machines and computers in the same way that we do now?

If these machines truly are indistinguishable from humans in the ways that they communicate and interact, then what will be the right thing to do when Roomba tells us that it doesn’t feel like vacuuming the floor, or our GPS gets mad at us when we take a wrong turn? Do we need to consider the feelings of AI? Should AI be granted rights?

Emotional Entanglement

The ethics only grow more complicated. If there are feelings involved, can a human and machine develop a relationship (familial or romantic)?

If we use drones with AI that passed the Turing Test like the one shot down in the Middle East in June, 2019, do we hold an ethical responsibility to retrieve the being or accept the loss of property?

Is it a thing or an entity?

If these are entities and we keep them working for us, are we exploiting them?

Fears and Fascination

The implications of our advancing scientific achievements are certainly exciting, but also frightening. Some decry the day when AI passes the Turing Test, fearing the answers to one or any of these questions. Others recognize that these questions represent major breakthroughs in human scientific, technological, and social development.

While we wait for the day when an AI passes the Turing Test, we have plenty to occupy ourselves in preparation for its arrival. These and other, deep questions that challenge our society, human nature, religions, and culture must be considered. …Maybe there is an algorithm that can help with that…

It seems like news sites report about self-driving cars almost constantly:  they’re coming, they’re getting better, they caused an accident; people love them, people refuse to get in one, people say that they’ll never trust them.

Going back a hundred years or so, newspapers had very similar headlines about the automobile. Technology enthusiasts lauded the automobile as the greatest thing ever; traditionalists said that it was a fad that would put carriage drivers out of work.

What isn’t really reported about self-driving vehicles is just how much they can potentially change our world. Autonomous vehicles aren’t just cars; there may be fleets of self-driving tractor-trailers, and there are already autonomous tractors in farm fields. The impact to our daily lives and our economy is staggering.

Vastly Different Road Habits

When self-driving cars are mixed with traditional automobiles, the impact won’t be as significant; stop lights will still stop traffic, and cars will still bunch up like a giant accordion in traffic jams. But as driverless cars replace the last manually operated cars, the transit time from point to point on the same roads we drive today will be a fraction of what it is today.

Rush hour traffic will virtually disappear as autonomous vehicles with instant reactions make busy intersections nearly 100% efficient by interlacing cross-traffic, eliminating the need for stop lights. Traffic on the highways will cruise by incidents on the side of the road efficiently without the accordion-effect.

An Economic Shift

The economic impact of autonomous vehicles is hard to predict but cannot be ignored. As driverless vehicles become more efficient at driving, identifying hazards correctly, and reacting faster than humans, insurance claims go down and the very need for auto insurance may be something our grandkids talk about like we do the rotary phone.

The cost of long-haul drivers will be all-but-eliminated as driverless big-rigs carry cargo over the road 24 hours a day, with no risk of driver-fatigue. Cost of goods go down as deliveries arrive faster and with less spoilage of perishable goods. Combine that with fleets of autonomous tractors and combines harvesting crops day and night in efficient, satellite-controlled routes with no farmer in sight. These major industry changes would shift economics within these markets as well as impact others.

Unforeseen Social Changes—And Benefits

Autonomous vehicles will certainly impact other aspects of society, maybe even eliminating personal cars altogether. Would future generations even need to purchase vehicles if reliable, safe, and efficient transportation comes from fleets of driverless Uber-like services, able to pick us up in less time than we spend searching for our car keys now? The average person would save the money spent on vehicles to spend on other durable goods, further shifting our economics.

The elephant in the room, however, is the huge force and place the auto industry maintains in society and the economy. Do the gains from autonomous vehicles forecast the end of the auto industry, and could this even be withstood?

Looking back a century at the parallel example, the traditionalists come into focus. They were right, but then the auto industry grew to encompass and employ scores more labor forces. Perhaps history will repeat itself, or perhaps the future will follow a different path, evolving instead of replacing one industry for another.

It takes years of training to become a doctor and with good reason. The volume of information doctors must obtain and retain requires at least that amount of time. So much depends on knowledge and analysis in the medical field that transferring that knowledge to a medical student happens over a period of years, including several that allow the new doctors to practice and apply the knowledge as Residents.

If only all that information could be directly transferred in a quick upload…

Artificial Intelligence Works For The Medical Field

While a data upload doesn’t apply to humans, artificial intelligence in the health care industry has been able to do just that. The massive volumes of information about human health can be uploaded into machines that sift, sort, analyze, and predict, i.e. diagnose, medical conditions.

Much of practicing medicine is rote memorization of classes of symptoms that relate to specific illnesses, or traits of diseases that match particular viral or bacterial organisms. A good chunk of time in medical school is spent memorizing names, identifiers, and reactions to pathogens. It’s a data download. So, add into the practice the use of machines capable of taking the data and finding patterns, and now there are applicable uses for artificial intelligence in the medical field.

Medical Research Is The Front Line Of Defense

Breakthroughs in research are leaps in human progress that make us live longer, stronger, and better. When we conquer a disease and discover a cure or find the source for an illness, we evolve and expand our lifespan. Smallpox, penicillin, AIDs, cancer, and more have all been topics of research that saved human lives and contributed to improving the human condition. It’s these and other types of searches for answers that will save us all.

Unfortunately, the searches take time. Longitudinal studies take place over years or even decades. During that stretch of time, massive amounts of data are collected, processed, stored, cataloged, etc. Researchers must disseminate meaning from it all, and depending on how long the study runs, they may even need to find ways to pass along the information to the next round of researchers taking the reins.

Research also takes resources. Collecting samples, growing and studying cells, accounting for instruments and implements, all become costly and may risk outcomes if supplies run short.

Faster Research Results Save Lives Sooner

Given these circumstances and parameters of research, the use of artificial intelligence has the potential to make a huge impact to the medical field. AI doesn’t fatigue, retire, or forget like its human research counterparts. If anything, machine learning speeds up the timeline between connecting data points and finding outcomes.

Machines churn massive amounts of data in less time and with less energy than a human being, and, there may be less resources using virtual simulations. Moreover, machine learning can assess the data. Programs can sift data to find patterns to make predictions.

For example, machines can churn data and find a pattern, like maybe a pathogen that only affects people with a certain recessive gene. Now, it’s possible to predict who might be at risk.

The implications of artificial intelligence in medical research are astounding. Machine-powered research has the capacity to speed up and make discoveries that save lives.

Artificial intelligence can be used to help humans live more healthy lies, reports Considerable.

Read the article on Considerable

Artificial intelligence is being deployed in business settings to revolutionize business models, reports Forbes. 

Read the article on Forbes

An AI trained in poker has beaten the 4 time world champion poker player, reports Science. 

Read the article on Science

According to Futurism, this summer Singularity University is focusing on artificial intelligence topics at its annual conference. 

Read the article on Futurism

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.

Cloud Computing allows for data to be stored in a decentralized fashion, allowing access to those with the right security credentials, no matter the device. As a result of the portable nature of file storage and sharing, a new type of user has cropped up: the Nomad, one who rejects the need for hardware and who is a direct by-product of the benefits of cloud computing which uses far less hardware per user than individual PCs or even centralized servers for a company

– And it’s no surprise that Millennials are leading the charge when it comes to mainstreaming this form of work and lifestyle. Millennials are more mobile than any generation before; it’s not a far stretch for Millennials to become Nomadic users—in many ways, they always have been.

Millennials have grown up with technology, blending it into their lives almost constantly. Portable movies on small, inset DVD players in the car salvaged long family car trips, eliminating fights from the back seat; music stored on small, portable devices allowed large quantities of music files to create instant access to songs any time, freeing teenagers from the confines of radio broadcasts; and of course, cell phones made communication portable, making the era of pay-phones and waiting to make calls obsolete.

Notice that the key word here is portable. Millennials are accustomed to technology allowing instant access and being available at their fingertips at any time. Therefore, when this generation entered the workforce and their new employers walked them over to a cubicle with a tangle of cords from monitors, PCs, and desk phones, it’s no wonder that they balked at and rejected the traditional office.

And others followed suit; Gen X employees--no strangers to technology and equally engaged albeit as adopters rather than native users of portable tech--agreed and soon joined the movement for a looser, less restricted style of workplace. Companies began to evolve and respond by allowing less stringent policies about working remotely. It became time to find a way to disconnect from the office while still connecting to the work; corporate America entered the Cloud.

The effect of cloud computing eliminated a need for hardware or even centralized servers for a company. Employees could work from anywhere. It was no longer necessary to have four walls and an outlet. Work wasn’t restricted to a 9-to-5 day. A company could hire its workforce from anywhere in the world.

With the portability of work, many Millennials (soon to be followed by Gen Z) and even some Gen Xers became Nomadic users, logging in and working from anywhere. Some even took the concept to an extreme, choosing to live as true Nomads, traveling the country or even the world while still holding down a job, even giving rise to a new form of lifestyle, a Vandweller.

All thanks to the Cloud, it’s no longer necessary to have a street address in order to work for a living…you just need an IP address.

There are some who liken adopting new technology to slowly dipping a toe into the waters, and then there are those who cannon-ball into the deep end, the early-adopters. Both approaches to technology represent the state of mind when it comes to risk versus reward; how much risk would you take for what amount of reward?

For a closer look at risk tolerance, let’s explore the advent of cloud computing that revolutionized storage and tested the mettle of users: would you trust the nebulous Cloud or allow your suspicions to keep you tied to a drive?

Media streaming and file sharing advanced so much that a typical user easily maxed-out the storage capacity of typical devices (SSD or HDD). Also, cell phones introduced cameras that recorded and took pictures in bursts, requiring better methods for users to access and keep larger files.

Thus the Cloud was born

The ubiquitous Cloud freed the average user from the constraints of hard ware. Even though computer drives surpassed the gigabyte to give way to the terabyte, these hard ware storage options still lacked the ability to store growing digital libraries of movies, videos, photos, and music or directories packed full of documents, presentations, and spreadsheets. Not to mention the devices’ susceptibility to corruption and the risk of sudden, random drive-crashes resulting in permanent data loss. Throw in the difficulty sharing files from one drive to another, and the Cloud was the superior solution—for some.

For others, they believed the Cloud posed a huge risk of data breaches from weak information security, dangerous threats in the Information Age. Until they had proof that the Cloud was safe, they would not adopt. They were risk adverse when it came to their personal data.

And risks did exist. The nebulous nature of Cloud storage – accessible to anyone with the Internet -- introduced uncertainty about who was uploading which types of files and when. The ability for cyber criminals to unleash a virus or exfiltrate data justified many trepidatious users to steer clear of the Cloud.

Still, the bold pioneers of Cloud computing recognized that like anything to do with data, security was the key. Breaches were bad for business, so successful products included security systems and authentication procedures. Savvy Cloud storage services had appropriate measures in place to protect data. Those who embraced the Cloud valued real, immediate advantages of better data management and felt confident dismissing unrealized threats. The reward of accessing data from anywhere revolutionized their business and personal computer use was worth it

Then there were those in the middle who only stored “safe” data on the Cloud, nothing that would cause concern should a breach occur. They maintained storage of personal data on their drives. These users were willing to tolerate some risk, but not with all their files.

It all comes down to potential. The early adopters saw the potential benefits of the Cloud as worth the risk, while the reluctant users saw potential threats that detracted from any reward.

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. 

So I will hit you with a statistic - on average, experienced recruitment consultants can analyze a resume in 6 seconds. This lends to the belief that these consultants scan and look for key information to make a decision to do a deeper dive into a jobseekers career history.

Compared to human recruiters, Artificial Intelligence can read an entire resume word for word a million times faster while looking for a good level more of information that enables it to make an accurate match against a job in order to shortlist. So it begs the question, does resume length matter in the hiring process when trying to get past AI first?

Well, there are limits. Would a two-page resume rank higher than a one-page resume, or even still would a three-page resume trump them all? There are many factors to consider here such as:

Resume Format: Large gaps, layout design, and text size are not a way of making a resume into two pages and claiming the AI hasn’t been fair to you, as AI strictly goes by information, not by blank spaces and large words. This isn’t a college term paper - AI will know if you’ve made the periods on the page a larger size than the rest of the text.

Rubbish In Rubbish Out: What is the quality of what’s written on the resume? Yes we could all write two pages of non-specific garbage that again, we could claim is a long written resume, but this translates to a lot of nonsense for AI which will be disregarded. AI works on good inputs; so if a resume has good content, clear dates, relevant companies, skills, and experience this will play the dominant role within the success of the candidate, not necessarily the length of the resume itself.

Realistic Boundaries: If a resume is 10 pages long, the likelihood it will be more successful than that of a two or three-page resume that also has good content, is pretty slim. However, if a resume is literally a paragraph long, then no matter how good that paragraph is, it’s not going to be enough for the AI to deem it relevant.

To conclude on this point, the reality is that a resume should be no shorter than 1 page of good content and ideally two pages in order to give enough information for the machine to make an accurate match and shortlist. In some sectors such as creative design, of course a resume may be much longer to display the breadth of your experience, but don’t fret, as long as you have good content on your resume, AI won’t judge you for expatiating over your experience.

Things that really matter other than content are dates, as AI uses this to scope how much time you have been doing something to know whether you are relevant for certain roles or not. Some AI is smart enough to know that dates are legacy, so if you have a long work history, be conscious of the fact that if you list jobs you had 10 years ago, some matching technology will use this to find roles that you may be too senior for today.

So to conclude - does resume size matter? Yes, but, if you follow the above parameters, you will get the most out of your job-seeking experience and appeal to recruiters and AI matching technology alike.

Arran James Stewart is the co-founder and CVO of blockchain recruitment platform Job.com. Relying on a decade worth of experience in the recruitment industry, Arran has consistently sought to bring recruitment to the cutting edge of technology. Arran helped develop one of the world’s first multi-post to media buy talent attraction portals, and also helped reinvent the way job content found candidates through utilizing matching technology against job aggregation. Arran is currently launching the first blockchain recruitment platform with Job.com – which aims to be the most secure, efficient, and transparent hiring process ever. As a first-mover in online recruitment technology with a decade of experience in recruitment, Arran’s expertise has been featured in Forbes, Reuters, Wired, and Hacker Noon, among other publications.