There is no dearth of jobs for qualified people in the market. Especially, if you have the knowledge and desire to make a significant difference in the market. Technologies like Machine Learning (ML) and Artificial Intelligence (AI) have already established the foothold in the market. Both of these technologies have the power to reform the way businesses operate. The communication and human interaction to accomplish complex tasks are also evolved. As the business application of AI and MI is constantly increasing, the requirement of qualified people to handle the workload is also increasing. Everybody is willing to take their career to the next level with these innovations. It is true that there are ample opportunities for qualified people, but simultaneously you should also have the extra-ordinary capabilities to take the challenges as programmers to make a smooth and natural transition whenever and where required. Now, to sail across smoothly, you must look at the following:
An ability to adapt to machine and learning to a machine is Artificial Intelligence, as described in brief. But artificial intelligence is more than we know and perceived to be. There are 3 types of artificial intelligence. Let’s look at the first type of AI and broaden our knowledge about narrow artificial intelligence: Artificial Narrow Intelligence (ANI) Artificial Intelligence proved that technology could imitate the human brain and actions. Narrow artificial Intelligence or narrow AI is a specific technology that it can imitate the human action to accomplish a task, which is narrowly defined. These actions, for example, include speech recognition and voice assistants. It would be good to know that narrow artificial intelligence has cognitive abilities and emphasize a single subset of this ability, where there is a further scope to make a few advancements in this area.
Over the years as AI is developing and reforming, various businesses and IT decision makers are making significant investment on technologies powered by AI. As artificial intelligence has the capability to change everything within the organization and refine the way people work, it is extremely important to gain the control over the macro and micro level of your business and organization. With the change of artificial intelligence is changing keeping an eye on the way your business functions become crucial, as every moment your changes are refined, and you have fresh requirements. This is just a piloting and beginning phase of AI and the power and the impact are already felt around. As slowly the artificial intelligence would be moving forward, we are expected to see much greater and wider changes around.
Artificial Super Intelligence or ASI is that branch of artificial intelligence that has the capability to perform the tasks that are impossible for the human mind to think or do. It is that aspect of intelligence that is more potent and refined than a human’s intelligence. Human’s intelligence can develop effectively and can adapt to changes faster. Superintelligence is capable of outperforming human intelligence; it is extremely powerful in doing that. Superintelligence is twice as powerful as human brains to conceptualize or idealize. The human brain is made of neurons and is limited to some billion neurons. Superintelligence, therefore, challenges this trait, which knows no limit. Ever since 1970, when the term Artificial superintelligence was introduced, it has been referring to the capabilities of the computer that can outperform or even challenge the possibilities of the human mind.
Artificial General Intelligence (AGI) is far more advanced and improved over Artificial Narrow Intelligence. It is applicable to general-purpose only. It can smartly and efficiently be applied to do variety of tasks; simultaneously learn and improve itself. As compared to the human brain or human intellect, AGI is similar and can function productively without any errors. Things that Artificial Narrow Intelligence could not do, Artificial General Intelligence can learn and improve to efficiently perform various tasks. To link to the context that what AGI empowered application can do is that the intelligence of AlphaGo can be applied in various other areas apart from its main function to be able to play Go. Research is being carried out to explore the possibilities of Artificial General Intelligence.
The UK has a well-documented decades-long 20% labour productivity gap with the US, Germany and France. With Brexit potentially creating extra challenges in overcoming this competitive disadvantage, the UK could fall even further behind. But if you are an optimist it could also be a moment for the UK to take a giant leap forward as it has done in the past when confronted with no other choice. Britain has been very good at doing this recently but it could be even better and Brexit could galvanise a new era of even more productive collaboration between public institutions and private business. There are many sectors of the UK economy that have bright sparks of world class performance but McKinsey Global Institute Productivity research shows very clearly they are held back by vexing bottlenecks. We believe this can be overcome. We decided to begin working to advance some already very strong work on creating industry clusters.
AI permeation. Artificial intelligence (AI), largely manifesting through machine learning algorithms, isn’t just getting better. It isn’t just getting more funding. It’s being incorporated into a more diverse range of applications. Rather than focusing on one goal, like mastering a game or communicating with humans, AI is starting to make an appearance in almost every new platform, app, or device, and that trend is only going to accelerate in 2018. We’re not at techno-pocalypse levels (and AI may never be sophisticated enough for us to reach that point), but by the end of 2018, AI will become even more of a mainstay in all forms of technology. Digital centralization. Over the past decade, we’ve seen the debut of many different types of devices, including smartphones, tablets, smart TVs, and dozens of other “smart” appliances. We’ve also come to rely on lots of individual apps in our daily lives, including those for navigation to even changing the temperature of our house. Consumers are craving centralization;
Speaking at AI Expo in Amsterdam, BPU Holdings CTO Carlos Art Nevarez believes it’s time for machines to become emotionally intelligent. Machines are becoming increasingly smart thanks to artificial intelligence, but they still remain cold, logical, and lacking emotion. Worse still, they have a bias problem. “We are teaching the machine to synthetically emulate emotional intelligence to better relate to how you and I feel,” states Nevarez. “So many exciting applications present themselves to enhance healthcare analytics, market assessment, consumer and voter sentiment, and delivering customised content in the Internet of Things.” Nevarez recounted a time he was out with his son and they saw a person fall. His son laughed, but – when Nevarez explained the person could be hurt – his son became empathetic. Over time, his son recognised when to show empathy.
Research has found most consumers have interacted with AI and would prioritise businesses with human-like implementations. The research, from Capgemini’s Digital Transformation Institute, found close to three-quarters (73 percent) of consumers have interacted via AI. Satisfaction with those who have experienced AI interactions is slightly lower, at 69 percent. Over two-thirds satisfaction is quite surprisingly high, especially when you consider how dissatisfied people typically are with traditional automated systems. Just over half (55%) of consumers across all age groups want interactions to be a mix of AI and humans, while 64 percent want AIs to be more ‘human-like’ rather than ‘human-looking’. Interestingly, the fear surrounding AI intellect – likely instilled through sci-fi movies such as Terminator – appears to be decreasing.
A recent report on artificial intelligence (AI) by an Indian government think tank foresees the country as an AI hub for the developing world. Research analyst Shashank Reddy writes about the possibility of that happening. India is the latest country to join the race to lead the AI revolution, which is still in the making. The world’s richest – and most powerful – countries have long been in this competition. It cuts across all spheres of national power, from the economy to the military, because the idea is that leadership in AI will enable global dominance. The two biggest powers so far have been the United States and China, with each investing heavily in AI and its applications. The report – which has been drafted as a “national strategy on AI” – admits that India lags significantly behind the superpowers in fundamental research and resources. Compared to the United States, it has fewer researchers and only a handful of dedicated laboratories and university departments.
Robots will be paired with a versatile AI that can quickly adapt to unpredictable conditions when examining underwater infrastructure. Some of a nation’s most vital infrastructure hides beneath the water. The difficulty in accessing most of it, however, makes important damage checks infrequent. Sending humans down requires significant training and can take several weeks to recover due to the often extreme depths. There are far more underwater structures than skilled divers to inspect them. Robots have been designed to carry out some of these dangerous tasks. The problem is until now they’ve lacked the smarts to deal with the unpredictable and rapidly-changing nature of underwater conditions. Researchers from Stevens Institute of Technology are working on algorithms which enable these underwater robots to check and protect infrastructure.
UK Digital Secretary Matt Hancock is visiting France today where he’s set to announce measures for strengthening AI cooperation between the nations. Speaking to industry leaders around the world, many recognise the UK as a leader in AI research and talent from its class-leading universities. Since 2014, an AI startup has launched every five days on average in the UK. This strength has resulted in significant interest from global technology giants – including Google’s £400 million acquisition of DeepMind, and Facebook’s acquisition of Bloomsbury AI just earlier this week. Digital Secretary Matt Hancock said: “The UK is a digital dynamo, increasingly recognised across the world as a place where ingenuity and innovation can flourish. We are home to four in ten of Europe’s tech businesses worth more than $1 billion and London is the AI capital of Europe.
Thousands of scientists have signed a pledge not to have any role in building AIs which have the ability to kill without human oversight. When many think of AI, they at least give some passing thought of rogue AIs seen in sci-fi movies such as the infamous Skynet in Terminator. In an ideal world, AI would never be used in any military capacity. However, it was almost certainly be developed one way or another because of the advantage it would provide to an adversary without similar capabilities. Russian President Vladimir Putin, when asked his thoughts on AI, recently said: “Whoever becomes the leader in this sphere will become the ruler of the world.” Putin’s words sparked fears of a race in AI development similar to that of the nuclear arms race, and one which could be potentially reckless.
China is planning to upgrade its naval power with unmanned AI submarines that aim to provide an edge over the fleets of their global counterparts. A report by the South China Post on Sunday revealed Beijing’s plans to build the automated subs by the early 2020s in response to unmanned weapons being developed in the US. The subs will be able to patrol areas in the South China Sea and Pacific Ocean that are home to disputed military bases. While the expected cost of the submarines has not been disclosed, they’re likely to be cheaper than conventional submarines as they do not require life-supporting apparatus for humans. However, without a human crew, they’ll also need to be resilient enough to be at sea without onboard repairs possible. The XLUUVs (Extra-Large Unmanned Underwater Vehicles) are much bigger than current underwater vehicles, will be able to dock as any other conventional submarine,
During its annual WWDC event, Apple announced the launch of its CreateML tool alongside the sequel of its Core ML framework. CreateML aims to simplify the creation of AI models. In fact, because it’s built in Swift, it’s possible to use drag-and-drop programming interfaces like Xcode Playgrounds to train models. Core ML, Apple’s machine learning framework, was first introduced at WWDC last year. This year, the company has focused on making it leaner and meaner. Apple claims Core ML 2 is 30 percent faster using a technique called batch prediction. Quantization has enabled the framework to shrink models by up to 75 percent. This is how Apple describes Core ML: “Core ML lets you integrate a broad variety of machine learning model types into your app. In addition to supporting extensive deep learning with over 30 layer types, it also supports standard models such as tree ensembles, SVMs, and generalised linear models.
Not content with its impressive(ly creepy) Duplex demo, Google promises it’s not wanting to replace call centers with its latest AI demonstration. During the Google Cloud Next 18 conference, Google Chief AI Scientist Dr. Fei-Fei Li demonstrated a new AI system called Google Contact Center AI which – much like Duplex – sounded incredibly natural in its responses to human queries. Google seems to have learned its lesson from its Duplex demonstration and wanted to iterate that it’s not designed to replace human operators. Instead, the system could be used to replace the current dreaded automated messages you often hear when dialling a call center. “Press 1 for… press 2 for…” just writing it makes me shudder. Contact Center AI could be able to answer some basic questions about the business to provide answers quickly to callers and reduce the waiting times for those needing a human operator. When a human operator is necessary, the system could automatically transfer the caller to the correct department.
Treating cancer is a race against time. Each moment which passes is an opportunity for it to spread and become untreatable. How long it takes for radiation therapy plans to be created today can take days. Individual maps need to be created for each patient to determine where tumours need to be targeted. This lengthy process is frustrating for the patient, their loved ones, and medical professionals who’d love nothing more than to spend time saving lives instead of creating plans. Engineering researcher Aaron Babier and his team have stepped-in with AI-based software to automate the process and cut down how long it takes for a radiation therapy plan to be created from days to hours, potentially even minutes. The team – from the University of Toronto’s Department of Mechanical & Industrial Engineering – also includes Justin Boutilier, Professor Timothy Chan, and Professor Andrea McNiven. Each of the researchers sees radiation therapy design as an optimisation problem.
Amir Konigsberg is the current CEO of Twiggle, a business that enables e-commerce search engines to think the way humans do. Watch any recent interviews with Amir and he will tell you that consumers often abandon e-commerce experiences because the product results displayed are often irrelevant. To tackle this problem, Twiggle utilises natural language processing to narrow, contextualise and ultimately improve search results for online shoppers. Another business that is trying to improve e-commerce search is US-based tech start-up Clarifai. Clarifai’s early work has been focused on the visual elements of search and, as their website states, their software is ‘artificial intelligence with a vision’. They enable developers to build smarter apps that ‘see the world like you do’, empowering businesses to develop a customer-centric experience through advanced image and video recognition.
AI and robotics are going to shape our future. Next there are 10 issues that professionals and researchers need to address in order to desing intelligent systems that help humanity. Misinformation and Fake News: The flow of misinformation together with our natural inability of perceiving reality based on evidence (a phenomenon called confirmation bias) is a threat to having an informed democracy. Russian hackers influencing the US elections, Brexit campaign and Catalonia crisis are examples of how social media can massively spread misinformation and fake news. Recent advances in computer vision make possible to completely fake a video of President Obama. It is an open question how institutions are going to address this threat. Job Displacement: The scientific revolution in the 18th century and the industrial revolution in the 19th marked a complete change in society.
The accelerating pace of progress in AI development (driven particularly by the subfield of machine learning) is currently generating a frenzied mix of anxiety and excitement. Public debates between figures such as Elon Musk and Mark Zuckerberg over the threats of ‘superintelligent’ forms of AI have received extensive coverage, while optimists have argued that AI might be directed towards solving pressing global challenges. But these narratives can easily distract from the fact that various AI-related technologies are already in widespread use. Some of these, as Professor Alston’s report highlights, can have distinct implications for human rights today. Analysis of the intersections between human rights and AI-related technologies has been growing across a range of areas. Perhaps the most prominent have been predictions of significantly decreased employment in a various sectors due to automation.