AI vs Machine Learning: What’s the Difference?

| July 15, 2019

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Due to record-pace globalization, today’s product development and marketing teams now face challenges that could only be imagined 10 years ago. And for global companies, the most productive solutions to these challenges are surpassing human brain power. Artificial Intelligence (AI) isn’t a singular technology, but rather a category of technologies and tools that global companies are increasingly relying on for competitive advantage. One of these is machine learning. But what precisely is machine learning, and how does it differentiate from the umbrella of AI? Here’s some data to help you decide which solution is best for your go-to-market strategy.

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Fruition Partners, A CSC Company, is a global technology-enabled services firm focused on elevating service management to the cloud. The company combines practical experience with technology-enabled tools and services to help organizations attain success throughout the entire Service Management process.

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These Mindblowing Theories About Human Consciousness Will Change How You Look At The World

Article | October 21, 2020

Consciousness—it’s one of the biggest questions out there. One thing that people today have in common with those from the earliest ages is questioning consciousness and our own existence. It’s taken different forms through the years, but the questions are largely similar at their core and the answers are still at large after all this time. The good news is that while we don’t have the answers yet, or even a timetable for when we might get those answers, we know more now than we have at any other point in human history. It’s easier to share information than it ever was in the past, and in this era, even an average person can study the big questions about life without the requirement of a formal education or access to a university. But in this age where it’s easier to ask questions, what kind of answers are we actually being led towards? We could be in a simulation—but not in the way you think One of the more modern theories on consciousness proposes that we might be living in a simulation. And modern really is the right word to describe this one, because it would have been an unthinkable idea even 20 years ago. However, as computing has grown stronger and stronger over the years, a key question was raised by these advancements: Is it possible that somewhere, computers are already powerful enough to run an entire universe? And if that’s the case, are we living in one of these simulations? While this sounds outlandish, it’s certainly a theory that has at least some support. That includes support from Elon Musk, who says we probably are living in a simulation. Don’t think, however, that we’re living in some version of the Sims catered to an alien audience. Games might be the first thing that comes to mind for us when simulations are brought up, but a more serious answer is quite a bit different from that idea. Rather than a game, such a simulation may be for, to put it simply, historical purposes. That is to say, instead of some advanced alien civilization running their own simulated universe, it may be advanced humans from the future simulating the lives of their ancestors. But this simulation of the past would be real enough that for the simulated person on the other side, everything feels real and there’s no way to tell that it is a simulation. This isn’t just an idea from science fiction, as much as it might sound like one. It was proposed by Nick Bostrom, an Oxford professor. There’s a lot of possible reasons why a future society might want to run a simulation in this way, ranging from studying history to preserving the records of the past. If you don’t think this would be possible from a technical perspective, just consider the jump in quality between early computers and the computers of today. Computing has already improved exponentially within our lifetime. In the very far future, this growth may have continued to heights that would have been unimaginable previously, just like computers today would have been unimaginable to someone used to the first computers. Quantum mechanics could be part of the explanation We don’t know much about how the brain works. While there’s been a lot of scientific progress since the questions around the nature of consciousness were first raised, there’s still a long way to go in figuring out just what makes the brain tick so to speak. Quantum mechanics, however, is good at explaining these kinds of things that don’t operate along the regular laws of physics. It’s hard to explain exactly how quantum mechanics work also, but we do know a bit more about them than we know about the brain. Essentially, if you break things down to a small enough level, they begin to respond differently. Some of the laws and theories that would have dictated their behavior previously begin to behave more loosely. Take a toothpick for example. You can move it around or drop it or throw it and it follows the same laws of physics. And if you snapped it in half, those halves would also follow the same rules. However, if you kept doing this until you reached a certain tiny, microscopic level, things would get weird. But just saying that the brain might work on quantum mechanics doesn’t actually explain much. After all, that statement says nothing about what these mechanics may actually do, and more importantly, what that means for us. Fortunately, though, more detailed theories on the subject do exist. It’s been said that quantum mechanics could explain these different quantum laws working with our brain to create consciousness from a “fourth dimension” around us. Quantum laws may also dictate that particles behave differently depending on if they’re being observed or not. Of course, the definitions are complex. Observation is a general term that doesn’t literally mean looking at something in the context that the word would come up in a regular conversation. But at least in theory, it’s possible that much of how we experience the world has to do with our brain observing and interacting with particles around us at the quantum level. These observations may be a basic building block behind everything—a source code, so to speak, for the universe at large. Universal consciousness remains a theory Universal consciousness might be the oldest theory on this list. It predates the more modern ideas mentioned with quantum mechanics and the simulation theory, but there’s enough anecdotal evidence surrounding the subject to at least consider it. It’s not complicated such as quantum mechanics. On the other hand, it’s probably the easiest theory to understand between the three. It’s the idea that essentially we come from the same place, or that consciousness itself is an extension of the universe. This belief has been seen in religions from differing times and places, with Buddhism notably claiming that consciousness is around us everywhere. It’s not just Buddhism that has reflected these ideas, however. There’s many anecdotal stories over the years of people who have been close to death or have medically died and believed that during these experiences, they’ve become one with the universe or something else along those lines. Of course, these stories won’t hold up in the opinion of the scientific community and it’s obviously hard to study this kind of phenomenon in a meaningful way. But to consider a subject like consciousness, something that we don’t understand, entirely using the same scientific methods used for other things may be a mistake. After all, the concept of the universal mind has been around since at least 480 B.C., when it was introduced by Anaxagoras, a philosopher from before the time of Socrates. While this much time passed doesn’t necessarily mean the theory is true, a lot of people have put their belief behind it between that time period and now. Optimism about the future Earlier in this article, we mentioned Elon Musk’s belief that humanity is living in a simulation. It’s not the only time Musk has spoken about things that would be considered outlandish by a lot of people. He’s spoken of other things that might as well sound like something out of a science fiction novel, such as the threat of artificial intelligence. When Musk did speak about AI, however, he had a notable quote that didn’t have to do directly with that specific subject matter at all. Rather, it was a general outlook on philosophy and life. “You kind of have to be optimistic about the future. There’s no point in being pessimistic,” Musk said. “I’d rather be optimistic and wrong than pessimistic and right.” It’s philosophical advice worth keeping in mind. The fact of the matter is, we don’t have the answers. There’s various places to draw the answers from, whether it’s conventional theories or these newer modern ones about simulations and quantum physics, or even religions which have been around for hundreds or thousands of years. Whatever you do believe about the mind, or even if you don’t believe anything at all and you’re just waiting to see what answers scientists come up with in the future, keep your head up. When the answers aren’t around yet and all of them could be wrong, you can only keep a positive outlook on things and hold a hope that your preferred theory is one with truth behind it.

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AI TECH

Artificial Intelligence 2020 Stories: The Great, the Glowing and the Gross Truths

Article | October 21, 2020

2020 has been an unprecedented year where we have seen more downs than ups. COVID-19 has impacted every aspect of our lives. But when it comes to digitisation and Artificial Intelligence, we have seen some impactful developments and achievements. As we approach the end of 2020, it is worth to look back at these AI stories to highlight the truths and discuss what it means for AI future direction. The Great Truth: Artificial intelligence played a crucial role in the detection and fight against COVID-19. Indeed, we have seen the emergence of the use of AI at hospitals to evaluate chest CT scans. With the use of deep learning and image recognition, COVID patients were diagnosed thus enabling the medical team to follow the necessary protocols. Another application was the triage of COVID-19. Once a patient has been diagnosed with COVID, AI has been used to predict the likely severity of the illness so the medical staff can prioritize resources and treatments. COVID has highlighted the need to deploy intelligent autonomous agents. As a result, we have seen both robots used at hospitals to diagnose COVID-19 patients and drones deployed to monitor if the public is adhering to social distancing rules. Another major AI contribution in the fight against COVID-19 is in the area of vaccine and drug discovery. Moderna’s vaccine that has been approved by US Food and Drugs Administration has used machine learning to optimise mRNA sequencing. The above is a proof that AI can make great contribution to mankind if it is used for “good”. The Glowing Truths: Some impressive AI results have been achieved. However, to leap forward a holistic and sustainable approach is needed. 2020 has seen some great AI achievements and leaps forward. The first example is Deepmind’s AlphaFold. The model scored highest at the Critical Assessment of Structure Prediction competition. The algorithm takes genetic information as inputs and outputs a three-dimensional structure. The model has impressively addressed a 50-year-old challenge of figuring out want shapes proteins fold into known as the “protein folding problem”. While Deepmind’s AlphaFold is a great achievement, it is noted by some scientists that it is unclear how the model will work with more real-world complex proteins. Thus, more work is needed in this area. The second example is OpenAI’s GPT3. The model is a very large network composed of 96 layers and 175 billion parameters. The model has shown impressive results for several tasks such as NLP questions & answering and generating code. However, it is noted that the model does not have any kind of reasoning and does not understand what it is generating. Furthermore, its large size makes it very expensive. It is also unsustainable carbon footprint wise; its training is equivalent to driving a car to the moon and back. While both AlphaFold and GPT3 models are both impressive achievements, there are some philosophical challenges/ questions that need to be addressed/ answered. The first question is about games/ simulated worlds vs. real world examples. Most often algorithms/models succeed in simulated world but fail in real world as the environment is more complex. How can we close the gap? How can we make the AI models succeed with complex tasks? I guess the first step is to apply AI to a real-world example with varied complexity levels. The second question is about the structure and the size of AI models. Do models have to be big? Can we come up with a new generation of algorithms/ models that are smaller is size and have more efficient computations? Well to answer this question we have to take a pause on deeplearning and explore new venues. The Gross Truths: Ethics and bias remain the main drawbacks of Artificial Intelligence. Over the last year, we had several prominent examples of AI ethics and bias issues. The first example relates to facial recognition: after several calls against mass surveillance, racial profiling and bias, and in light of Black Lives Matter movement starting in the United States, several tech companies such as Microsoft banned the police from using its facial recognition technology. The second example relates to the use of an algorithm to predict exam results during COVID-19 period: after accusations and protests that the controversial algorithm was biased against students from poorer backgrounds, the United Kingdom government was forced to ditch the algorithm. In the absence of regulations and tightened frameworks, ethics and bias will continue to be the main concerns surrounding the use of artificial intelligence. Looking into the future, AI adoption will continue to accelerate, and we will probably see more breakthroughs achieved by only if we start looking at the subject in a holistic and sustainable view. Focusing models on real world problems and reducing the models carbon footprint will be a major step forward. We need to move away from thinking that “more” is always “more”. Sometimes “more” is “less”.

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Health care of tomorrow, today: How artificial intelligence is fighting the current, and future, COVID-19 pandemic

Article | October 21, 2020

SARS-COV-2 has upended modern health care, leaving health systems struggling to cope. Addressing a fast-moving and uncontrolled disease requires an equally efficient method of discovery, development and administration. Artificial Intelligence (AI) and Machine Learning driven health care solutions provide such an answer. AI-enabled health care is not “the medicine of the future,” nor does it mean robot doctors rolling room to room in hospitals treating patients. Instead of a hospital from some future Jetsons-like fantasy, AI is poised to make impactful and urgent contributions to the current health care ecosystem. Already AI-based systems are helping to alleviate the strain on health care providers overwhelmed by a crushing patient load, accelerate diagnostic and reporting systems, and enable rapid development of new drugs and existing drug combinations that better match a patient’s unique genetic profile and specific symptoms.

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AI TECH

CAN AI REPLACE ‘GUT FEELING’?

Article | October 21, 2020

Artificial Intelligence is empowering business leaders to make better, data-driven, and insightful decisions. It has undergone several evolutions since it burst into the business scene in the 1950s, to the point where several thinkers have already painted a machine that replaces human scenarios for the future. Our view on the future of work has evolved into a zero-sum game, where the result is an either-or. In my opinion, the view that AI will play a dominant role in the workplace is a little extreme. The fundamental assumption around AI replacing human workers is that humans and machines have the same characteristic. Totally untrue!. AI-based systems may be fast, consistently accurate, and rational, but they are not intuitive, emotional or culturally sensitive. Humans possess these qualities in abundance, and it is one of the reasons why we continue to surprise the world with our advancements. Intuition is the Mother of Innovation If we are living comfortable lives today, it’s because some business leaders chose their gut feeling over data analytics on numerous occasions. Some historical examples have been: 1: Henry Ford, facing falling demand for his cars and high worker turnover in 1914, doubled his employees’ wages, and it paid off. 2: Bill Allen was the CEO of Boeing in the 1950s, a company that manufactured planes for the defence industry. One day, he woke up to the idea of building commercial jets for a sector that was non-existent – civilian air travel. Allen convinced his board to risk $16 million on a new transcontinental airliner, the 707. The move transformed Boeing and air travel. 3: Travis Kalanick faced serious pushback when Uber instituted surge pricing. His move seemed to anger and alienate everyone. Travis stayed the course, and Uber modified its surge policy whenever appropriate. Now, dynamic pricing is an accepted aspect of this business and many others. So the question is, should a competent professional trust their gut feeling or make data-driven decisions? DATA V/S GUT Top professionals have repeatedly confirmed that gut feeling is one of the main reasons for their success. Leadership often gets associated with quick responses in unprecedented situations and lateral thinking. Experienced leaders are not only fearless about their instincts but are also proficient at making others feel confident in their judgment. Also, going with our instinct can help us make decisions quickly and more accurately since we tend to make choices based on experiences, values, and compassion. Malcolm Gladwell calls this ‘thin slicing’ in his book, “Blink”. Thin-slicing is a cognitive manoeuvre that involves taking a narrow slice of data, what you see at a glance, and letting your intuition do the work for you. However, he does warn that some decisions are exempt from this rule; it only applies to areas where you already have significant expertise. Artificial Intelligence and machine learning can support leaders to see complex patterns that can lead to new understanding in this fast-moving, digital era. The contention is that ‘human gut’ feeling can go hand in hand with AI – each supporting the other to achieve balanced outcomes. A Joint Venture Between Head and Heart Many see AI as an aid to human intelligence, not a replacement. To be one-step ahead in the AI era, professionals must learn to balance human and machine thinking. Organizations will have to showcase the ability to use the correct information at the right time and take action. It’s about using your instinct to take advantage of data and transforming that information into timely business decisions. AI is not yet ready to replace the human brain, but it has matured into an effective co-worker. Will intelligent machines replace human workers sometime soon? I guess not. Both have different abilities and strengths. The more important question is: Can human intelligence combine with AI to produce something experts are calling augmented intelligence? Augmented intelligence is collaborative, and at the same time, it represents a collaborative effort in the service of the human race. Figuring out how to blend the right mix with the best of data-driven deliberation and instinctive judgment could be one of the most significant challenges of our time.Enable GingerCannot connect to Ginger Check your internet connection or reload the browserDisable in this text fieldRephraseRephrase current sentenceEdit in Ginger×

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Fruition Partners, A CSC Company

Fruition Partners, A CSC Company, is a global technology-enabled services firm focused on elevating service management to the cloud. The company combines practical experience with technology-enabled tools and services to help organizations attain success throughout the entire Service Management process.

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