Mediaboss Marketing

By Lior Akavia, CEO and co-founder of Seebo

Four years ago, Elon Musk famously predicted that artificial intelligence will overtake human intelligence by the year 2025.

Were headed toward a situation where AI is vastly smarter than humans and I think that time frame is less than five years from now, he told the New York Times.

Musk has also repeatedly warned of the potential dangers of AI, even invoking the Terminator movie franchise by way of illustration.

And yet, the very same Elon Musk recently unveiled the prototype for a distinctly humanoid Tesla Robot, which he hopes will be ready in 2022. Speaking to an audience at Teslas AI Day in August, Musk quipped that the robot is intended to be friendly, and added that it will be designed to navigate through a world built for humans alluding to his previous, apparently still-extant concerns.

Of course, Musks fears about AI arent shared by everyone. Fellow tech entrepreneur Mark Zuckerberg has distinctly different views on the matter. On the other hand, Musk isnt alone, either; Stephen Hawking once famously warned that AI could ultimately spell the end of the human race.

So what can we take away from this confusing discourse about AI? Is artificial intelligence the savior of humanity? Or are we about to get conquered by an army of drones?

The truth is (probably) a lot less theatrical but arguably no less dramatic.

The misleading thing about these types of high-profile, philosophical debates about AI is that we actually have a long way to go before what Hawking referred to as full artificial intelligence is even developed let alone mass-introduced into the marketplace.

Undeniably, however, the vast potential of AI is as much recognized by experts as it is taken for granted by the general public. Machine learning and other forms of AI are already defining many aspects of our daily lives, from the way we communicate with others to our ability to get to work on time, to how we shop, work, and even acquire knowledge.

In unveiling his Tesla robot, Musk offered a pretty succinct summary of the core benefits of AI in general, asserting that the robots purpose will be to take over unsafe, repetitive, or boring tasks that humans would rather not do.

That summary is applicable to almost any AI application you can think of: taking over tasks that humans either never really enjoyed doing, or werent ever that great at in the first place. A classic example is food assembly lines: humans get tired, bored, make mistakes, and have potentially dangerous accidents all things that robots either dont experience at all, or (in the case of accidents) experience less often, with costs measured in terms of financial losses rather than human lives.

But a far better illustration of this reality is in the world of data. In the days before big data became a buzzword, there was hope that the explosion of information would immediately usher in an era of true enlightenment. Finally, human beings could have all the data they needed at their fingertips to make the optimal decisions every time.

Of course, thats not what happened. Instead of being liberated by big data, we became hostages to it. From the spam clogging our email inboxes to the blur of graphs, charts, and tables that to this day form the core challenge for almost every business.

Then came artificial intelligence, and with it, the key to unlocking the potential of that ocean of data. And herein lies both the immense promise of AI, as well as the fear of Terminators and robot-driven unemployment: AI, particularly in the form of machine learning algorithms, is infinitely better at analyzing data than human beings are.

While philosophical debates between tech heavyweights naturally make the headlines, the current daily reality is far more benign. In practice, AI is mostly being used to empower humans, not sideline them.

Take the food manufacturing example above. Yes, its true that many food assembly lines are now dominated by machines rather than people, much in the way the Industrial Revolution did away with other menial jobs. But just as the Industrial Revolution paved the way for a more prosperous future, rather than one of mass unemployment (as many feared at that time as well), the Industrial Artificial Intelligence Revolution is enhancing and improving the lives of food manufacturing teams, rather than rendering them redundant.

Using AI, food manufacturing teams are better able to excel at their jobs which of course benefits them, their employers, and ultimately the consumers who benefit from a greater quantity and better quality of product.

Ive seen this firsthand. My company, Seebo, is part of this Fourth Industrial Revolution. Our proprietary Process-Based Artificial Intelligence is enabling global leaders in the food industry to reduce production losses like waste, yield, and quality, saving them millions each year. At the same time, theyre using our technology to become more sustainable: cutting emissions, reducing energy consumption overall and significantly reducing food waste.

And as with many other applications of machine learning AI, its all about the data. In the case of food manufacturers, it means using Seebos AI to reveal the hidden causes of these food production losses, high emissions, and so on insights that were previously unavailable due to the complex nature of food manufacturing data. Armed with those insights, process experts and production teams are able to make the right decisions in real time: to know when to adjust the process or maintain certain set points that they may otherwise have neglected or overlooked.

Of course, as the saying goes, with great power comes great responsibility.

From the wheel to the printing press to nuclear power, technological advancements always have the potential for good or bad. In that sense, AI is no different; where it differs is that its full potential is largely unknown. Weve still yet to tap into the full potential of this technology, so it often feels like a sort of black magic.

But I do believe that the current trajectory is very much for the good but more to the point, we dont have a choice.

Humanity today faces two simultaneous global challenges. First, a population crisis with the global population set to swell 25% by the year 2050 on the one hand, while on the other hand many countries (most notably China) face a rapidly aging population. And second, a rising climate crisis, as countries and industries struggle to cut carbon emissions while maintaining the productivity necessary to sustain those growing and aging populations.

In this struggle, artificial intelligence is perhaps our greatest ally. Ive seen up close its potential to empower better decisions, bridging the gap between seemingly opposing goals like reducing emissions while producing more, not less.

Far from conquering us, AI is humanitys best chance of overcoming some of our greatest food manufacturing challenges today.

Lior Akavia is the CEO and co-founder of Seebo, an industrial Artificial Intelligence start-up that helps tier-one manufacturers around the world to predict and prevent quality and yield losses. He is a serial entrepreneur and innovator, focused on the fields of AI, IoT, and manufacturing.

Read the original:
Artificial Intelligence in the Food Manufacturing Industry: Machine Conquers Human? - Food Industry Executive

Retention of students is an issue for academic institutions across the globe, given limited resources and tight budgets. In some countries, the average dropout rate is around 45%. Accordingly, measures are being taken to find a solution to this problem. Experts say that such strategies are most effective if applied in a students first year of the opted course.

The importance of artificial intelligence (AI) and machine learning (ML) can be vital here. Using AI-enabled devices, instructors can suit everyone's needs and requirements on a case-by-case basis which means each learner gets desired attention. AI in education is an emerging field that can be broadly classified into two subfields: Educational Data Mining and Learning Analytics.

Educational data mining helps learners learn and identify the settings where they perform well, as well as give deeper insights into the understanding of educational phenomena. In the future, AI-enabled applications will become common in universities that will integrate with other techniques to track the behavior of students, for instance finding the students risk of abandoning their studies so that timely action can be taken.

To keep track of students and courses, educational institutions retain vast amounts of data. The data contains information about students, their grades, faculty performance, etc. This data is very precious for the process of data mining in the educational sector as it serves as the basis for training any AI-ML model. Educational institutions that have adopted AI-ML have observed an increase in their efficiency because of the timely decisions taken by them.

Learning analytics is a new realm in education concerning AI, that can be considered as data collection about learners, analysing it, and reporting learners and their contexts. The goal is to understand and optimise learning and make this field more efficient. This involves using data visualisation, social network analysis, modelling and prediction of educational data using AI-ML techniques.

The challenge for academic institutions is the low performance when a significant number of students try hard to manage their studies and are forced to change their majors, or dismissed from the program, or have their graduation delayed. Teaching practices that are enabled with technology identify struggling students and produce rich data to detect at-risk students and find solutions for them. Besides improving the accuracy of prediction of AI-ML models, it is very important to improve the accuracy of prediction of failing students, who require immediate attention and support.

To handle at-risk students, the traditional approach which most educational institutions have been following is to collect the data about learners and work towards remediation. The actions could be in the form of moral and psychological support, counselling, mock tests, etc. The new generation is growing up with AI-ML-based learning systems; therefore, this is the need of an hour for an education system that prepares students for the data-driven society in which they live.

Dr Akhter Mohiuddin is an Associate Professor of Data Sciences, Great Lakes Institute of Management, Gurgaon. Views expressed here are his own

Visit link:
Artificial Intelligence can read a students data to tell you if hes going to be a topper or a dropout - EdexLive

Cybers intro music has clips from various movies. The first is from WarGames, a 1983 film where a hacker squares off against an artificial intelligence thats in control of the nukes. Almost forty years later and AI is beating people at Starcraft 2, which is not quite the organization of a nuclear war but can still feel scary.

But how smart are these systems really? Is AI, or machine learning as practitioners prefer to call it, the next big thing or just another in a series of promises about the future that hasnt quite materialized? What are the actual dangers of these systems?

Here to help us answer this question is Os Keyes. Keyes is PhD student at the University of Washingtons Department of Human Centred Design & Engineering and an occasional Motherboard contributor. Their area of expertise is, broadly, how technology constructs the world we live in.

Its a wide-ranging conversation that covers everything from Henry Kissinger to Human Centipede and the hard limits of artificial intelligence.

Read more:
The Promise and Terror of Artificial Intelligence - VICE

Technology has changed numerous aspects of the manner in which you have currently chosen to end up living your life, but one of the biggest impacts that it has had has to do with the world of art. Drawing something used to require a fair amount of skill, but the advancement of neural networks and the like has given rise to new art forms that dont require any actual physical drawing or painting skills although they are equally as demanding from a creative point of view.

With all of that having been said and now out of the way, it is important to note that one of the most revolutionary technologies that lots of people are talking about in this regard is Pixray. This is a website that makes it so that you can draw virtually anything you want as long as you input it correctly. The way this works is that the website uses AI to use your input and turn it into a visual work of art that might change how we make art in the first place.

Previously, a lot of work was being done to make AI better at recognizing faces. That got to the point where AI could be used to create brand new faces that no one has ever seen before with all things having been considered and taken into account. However, the thing that sets Pixray apart is the fact that it goes beyond that by allowing you to input any and all text you choose and use the AI to create an image the accurately corresponds to that text.

For example, a real estate developer could potentially use this AI to create a visual representation of something they want to build at some point. Artists could also use this as a starting point to develop newer and better ways of expressing themselves which might bring about a brand new cultural revolution if you think about how it can benefit such individuals from a lot of points of view.

See more here:
How Pixray Uses Artificial Intelligence to Make Drawing Art Easier - Digital Information World

Ever since Tesla started its journey as a carmaker, the auto industry has never been the same. The old model of selling higher trims and more options is about to collapse. The new model is to keep the car running for as long as possible and make profits from software subscriptions and services. This way, the cars will retain their value for longer, while models can remain in production long enough for the development costs to be covered.

In this new territory, Tesla is still the undisputed king. Its nimble lineup endures for years with little changes in the technical department, and new features are added every quarter while the car owner sleeps in his bed. Some of them are free of charge, but for others the user must pay, upfront or through a subscription, and that generates an important revenue stream for Tesla.

Now, Stellantis wants a piece of the pie too and wants its cars all fitted with artificial intelligence (AI) software, starting as soon as 2024. The automaker presented its software strategy on Tuesday and said it expects to have 34 million connected vehicles on the streets by 2030, up from 12 million now.

Starting from 2024, Stellantis will deploy three new tech platforms powered by artificial intelligence named STLA Brain, STLA SmartCockpit, and STLA AutoDrive, respectively. For that, the automaker will extend existing ties with technology giant Foxconn, as well as those with Alphabets Waymo. BMW will also be onboard with this endeavor, specifically for the STLA AutoDrive autonomous driving platform.

According to Stellantiss CEO Carlos Tavares, the software business is expected to generate high margins, like the ones in the tech industry. These high margins are less common in the traditional automotive business. Stellantis plans to generate around $4.5 billion (4 billion euros) in additional annual revenues by 2026 and around $23 billion (20 billion euros) by 2030 from software-enabled product offerings and subscriptions.

Not only the three software platforms will make money for Stellantis, but they will also bring value to customers, through longer service and higher resale values. The services and subscriptions will also be uniquely brand-specific, to further differentiate the companys 14 brands. Stellantis strategy will include over-the-air software updates that will enhance vehicle capabilities. For instance, Dodge owners will be able to receive performance upgrades, while Alfa Romeo vehicles could get a sportier driving experience.

Read the original post:
Stellantis Bets Big on Artificial Intelligence, Wants To Beat Tesla at Its Own Game - autoevolution